BCA Indicators/Model

GAA DM Equity Country Allocation Model Update The GAA DM Equity Country Allocation model is updated as of October 31st, 2017. There are no significant changes in country allocations, but minor changes are the reductions in the overweight of Germany, Sweden and Switzerland in favor of Spain and Italy, which were already overweight, and Australia which was underweight, as shown in Table 1. As shown in Table 2 and Chart 1, Chart 2 and Chart 3, the overall model underperformed its benchmark by 73 bps in October, largely due to the underperformance (110 bps) of Level 2 model, resulting from the large underweight of Japan, which was the best performer in October. The underweight of Australia and Canada worked very well too, but not enough to offset the overweight in the euro zone countries. The strength of the USD against the euro also hurt the performance. Since going live in January 2016, the overall model has outperformed the benchmark by 247 bps, largely from the allocation among the 11 non-U.S. countries, which have outperformed their benchmark by 599 bps. Chart 1GAA DM Model Vs. MSCI World GAA DM Model Vs. MSCI World GAA DM Model Vs. MSCI World Chart 2GAA U.S. Vs. Non U.S. Model (Level1) GAA U.S. Vs. Non U.S. Model (Level1) GAA U.S. Vs. Non U.S. Model (Level1) Chart 3GAA Non U.S. Model (Level 2) GAA Non U.S. Model (Level 2) GAA Non U.S. Model (Level 2) Table 1Model Allocation Vs. Benchmark Weights GAA Quant Model Updates GAA Quant Model Updates Table 2Performance (Total Returns In USD) GAA Quant Model Updates GAA Quant Model Updates Please see also on the website http://gaa.bcaresearch.com/trades/allocation_performance. For more details on the models, please see the January 29th, 2016 Special Report, "Global Equity Allocation: Introducing the Developed Markets Country Allocation Model." http://gaa.bcaresearch.com/articles/view_report/18850. Please note that the overall country and sector recommendations published in our Monthly Portfolio Update and Quarterly Portfolio Outlook use the results of these quantitative models as one input, but do not stick slavishly to them. We believe that models are a useful check, but structural changes and unquantifiable factors need to be considered too in making overall recommendations. GAA Equity Sector Selection Model The GAA Equity Sector Selection Model (Chart 4) is updated as of October 31st, 2017. Chart 4Overall Model Performance Overall Model Performance Overall Model Performance Table 3Allocations GAA Quant Model Updates GAA Quant Model Updates Table 4Performance Since Going Live GAA Quant Model Updates GAA Quant Model Updates The growth component in the model has turned cautious on the global recovery. The aggregate cyclical sector overweight has been reduced to 2.5% from 8% last month. However, cyclical sectors such as energy, materials and industrials have seen an increase in overweight driven by favorable liquidity and momentum backdrop. On the other hand, financials and technology have been downgraded to underweight. Finally, as a result of the bearish outlook from the growth component, the model has turned overweight on utilities. For more details on the model, please see the Special Report "Introducing The GAA Equity Sector Selection Model," July 27, 2016 available at https://gaa.bcaresearch.com. Xiaoli Tang, Associate Vice President xiaoli@bcaresearch.com Aditya Kurian, Research Analyst adityak@bcaresearch.com

Highlights On Black Monday, October 19, 1987, equity bourses around the world plunged amid cascading bouts of selling, recording some of their largest single-day losses of the twentieth century. The plunge, exacerbated by derivatives transactions, and transmitted swiftly around the world, marked the first contemporary global financial crisis. BCA clients were well prepared. The Bank Credit Analyst steadily warned of increasing stock market vulnerabilities across all of 1987 even as it correctly predicted that the S&P 500 would most likely soar before eventually cracking. The Federal Reserve's immediate all-out effort to contain the damage ushered in a new central bank template for responding to quaking markets and helped give rise to the Greenspan put. While we do not fear a repeat of Black Monday, the U.S. equity market's long-term prospects are dramatically less appealing than they were in 1987. Investors should be prepared for an extended stretch of public market returns that pale beside the ones earned over the last 30-plus years. Feature 30 years ago today, Black Monday erupted around the world, reaching its nadir in New York, where relentless waves of selling drove the major indexes down 20%. The contagion had spread in a rapid relay from Hong Kong to Europe and then to New York, before fetching up in Auckland and other Asia-Pacific exchanges as Black Tuesday. The event was the centerpiece of what turned out to be sharp, albeit relatively brief, bear markets around the world (Charts 1 and 2). Confounding nearly every observer, however, the crash did not amount to much in a broader economic context and financial markets quickly regained their footing, with global equities vaulting to new highs in the '90s1 amidst speculative excesses that made the '80s' mania look demure. Chart 1Great Runs... bca.bcasr_sr_2017_10_19_c1 bca.bcasr_sr_2017_10_19_c1 Chart 2...And Sudden Stops ...And Sudden Stops ...And Sudden Stops Like all serious investors, BCA researchers are students of history. Black Monday was the first modern global financial crisis, and its 30th anniversary affords us the chance to study its run-up and aftermath for insights into future dives. It also gives us the chance to return to BCA's extensive archives and see how our forebears assessed conditions in real time. Their ex-ante analysis and forecasts were stellar, and reinforce the robustness of our approach. Their lagging ex-post performance highlights the need for investors to maintain a flexible mindset that can accommodate all possibilities. From Fear To Greed Black Monday marked the definitive end of a historically potent bull market (Table 1) that began, as the best ones do, in revulsion. Business Week's August 1979 cover story trumpeting the death of equities has become notorious, but the S&P 500 didn't bottom for three more years, during which it lost a quarter of its inflation-adjusted value. All told from the end of September 1968 to the end of July 1982, the S&P tumbled 62.5% in real terms (Chart 3). Inflation took a heavy toll on real growth over the 55 quarters of U.S. stocks' lost decade and a half (Chart 4, top panel), but the economy had expanded nonetheless, and stocks emerged from the ashes of the Volcker double-dip recession with a lot of ground to make up. Table 1A Bull With Speed And Stamina Black Monday, Thirty Years On: Revisiting The First Modern Global Financial Crisis Black Monday, Thirty Years On: Revisiting The First Modern Global Financial Crisis Chart 3A Lost Decade And A Half ... A Lost Decade And A Half ... A Lost Decade And A Half ... Chart 4...Despite Steady, If Unspectacular, Real Growth ...Despite Steady, If Unspectacular, Real Growth ...Despite Steady, If Unspectacular, Real Growth The ensuing five-year bull market (Chart 5, top panel) unfolded in two phases: the first, which burst out of the gate on a sudden repricing before taking a full year to catch its breath, had the support of earnings growth (Chart 5, middle panel) and re-rating; the second, which went on without pause for two and a half years, was all about re-rating (Chart 5, bottom panel). It finally ended in late August 1987, when skeptical investors could no longer stomach big gains derived entirely from multiple expansion, and stocks began to retreat in earnest in October, sliding 5% and 9% in the two weeks before Black Monday. Proximate triggers included sickly trade data, a competitive devaluation threat and proposed tax legislation that stood to make corporate takeovers a good deal more costly. The first two factors pushed the dollar down and yields up, as investors fretted that the Fed would be forced to raise rates (Chart 6), and the last pulled the plug on runaway speculation in takeover targets. Chart 5A Two-Act Bull Market A Two-Act Bull Market A Two-Act Bull Market Chart 6Be Careful What You Wish For Be Careful What You Wish For Be Careful What You Wish For The Echo Chamber, ... There is career safety in numbers, but portfolio danger. As the late Barton Biggs put it, there's no investment so good that it can't be destroyed by too much capital. Portfolio insurance may not have even been a good idea, as it didn't amount to anything more than a portfolio-sized stop-loss order, souped up with computer software and derivatives contracts. But by the fall of 1987, its widespread adoption had turned it into a very bad one. Portfolio insurance was developed in the late '70s by two finance professors who sought a method that would allow investors to participate in equity market gains while limiting their downside exposure. When stocks began to decline in the direction of a set downside limit, the portfolio insurance program would reduce net equity exposure via the sale of index futures. Once the market recovered and the program determined the coast was clear, it would unwind the futures positions. Although the technique had its flaws on a micro scale - futures trading wasn't costless, and there was considerable potential for whipsawing - it was doomed at the aggregate level because the index futures market wasn't deep enough to accommodate all the selling pressure that would be unleashed by a significant correction. ... Or, From Wall Street To LaSalle Street And Back Again There was more to Black Monday than portfolio insurance - the event was global, and the technique was not a factor on other bourses - but it helped to create a self-reinforcing spiral between the cash market in New York and the futures market in Chicago. Heavy selling of stocks in New York triggered heavy selling of index futures in Chicago, as insured portfolios sold futures to mitigate their direct cash exposures. The selling redounded back to New York as the futures buyers on the other side of the trade sold the underlying stocks to balance out their long futures positions2 and opportunistic investors seized the chance to front-run the mechanical portfolio insurers.3 The new sales pushed share prices even lower in New York, triggering more index futures selling in Chicago, and cinching the vicious circle. The View From Peel Street BCA, safely removed from the madding crowd in Montreal, foresaw something quite like the crash. The September 1986 and 1987 editions of our annual New York conferences bore the respective titles, "The Escalation in Debt and Disinflation: Prelude to Financial Mania and Crash?" and "Phase II in the Escalation of Debt, Disinflation and Market Mania: Prelude to Financial Crash?" Throughout all of 1987, the monthly Bank Credit Analyst warned of the U.S. equity market's increasing vulnerability and recommended that investors reduce exposure in a disciplined fashion ahead of the inevitable bust. The investment policy recommendation, issued in accord with prudent money management principles, differed from BCA's market forecast, which was for robust, potentially parabolic, gains before the bull market ended. BCA was not trying to have it both ways: it has long been a central tenet of our work that one's investment strategy can - and regularly should - be distinct from one's market forecast. We do not attempt to squeeze every last drop out of a bull or a bear market. Empirical evidence makes it abundantly clear that no one can consistently call tops or bottoms. In the words of turn-of-the-century trading legend Jesse Livermore: "One of the most helpful things that anybody can learn is to give up trying to catch the last eighth - or the first. These two are the most expensive eighths in the world.4" The opening paragraph of the March 1987 Bank Credit Analyst, published six months before the market peak, summarizes our ongoing advice: [I]nvestors who are overexposed should reduce positions to a level comfortable to ride out what will likely become a much more volatile phase of the secular bull market in stocks. ... At some point, it is likely that the U.S. stock market will experience a 1962-type correction - a sharp decline which comes out of the blue as a result of extreme overvaluation and excessive speculation. As then, it is unlikely to be associated with a credit crunch, as almost all post-war bear markets have been. ... At present, there is nothing in the data, either fundamental or technical, which suggests that such a shakeout is imminent. However, the key for investors in this bull market is to have positions which are sufficiently comfortable so that they can ride out sudden, dramatic corrections and participate in the long upward rise, which we feel has much further to go. (pp. 3-4) Eighteen months before the August 25th peak, the March 1986 Bank Credit Analyst's Section III was titled, "The Coming Financial Mania," and its strategy prescriptions were much more aggressive, even as it acknowledged the risks: Increasing volatility should be expected both because of the still lingering risks prevailing and the dramatic price movements in recent months. Hence, conservative investors should not overtrade. To fully capitalize on the ongoing revaluation of financial assets, it is important not to lose positions as a result of the necessary sharp corrections which will be experienced along the way. The stock and bond market potential over the next 2-3 years remains extraordinary. (p.11) The great dilemma for investors is, of course, how aggressively to play the game during the latter stages. The fascination, excitement and danger is the knowledge that vast fortunes are easily made right up to the end, but there is no reliable method to get out just before the crash. [...] Frequently the bubble goes on much longer and prices go far higher than anyone can imagine [...]. Yet, the vulnerabilities grow proportionately to the power of the manic phase. (p.26) Investment strategy in [a manic] environment must be based on the historically observed phenomenon that price appreciation generally accelerates to a climax or blowoff and that the hidden risks grow exponentially with price rises. Therefore, investors must constantly guard against the natural tendency to become increasingly greedy and careless in valuation standards as prices rise. (p.41) As good as BCA's near- and intermediate-term calls were in the run-up to the '87 crash, our longer-term calls were even better. We repeatedly argued that disinflation would be a secular trend, and that it would power secular bull markets in bonds and equities. Three decades on, with the Barclays Aggregate Index, the Barclays High Yield Index and the S&P 500 having produced real annualized total returns of 5%, 9.3% and 7.6%, respectively, the call has been vindicated (Table 2). As BCA foresaw, the harsh monetary medicine administered by the Volcker Fed to slay the inflation dragon has paid hefty market dividends. Table 2A Great Three Decades For Financial Assets Black Monday, Thirty Years On: Revisiting The First Modern Global Financial Crisis Black Monday, Thirty Years On: Revisiting The First Modern Global Financial Crisis The Trouble With The Austrians For all that BCA achieved ahead of Black Monday, and as correct as our long-term calls from the '80s turned out to be, it must be acknowledged that we missed the boat on getting back into equities after the crash. Part of the miss is understandable: one wouldn't expect the strategist with the most prescient call ahead of a downturn to be the first one to identity the beginning of the subsequent rally. The best investors are the ones with the supplest minds, however, and the BCA archives reveal a bias that may have gotten in the way of embracing more bullish near-term outcomes. To wit, one cannot read the 1988 and 1989 Bank Credit Analysts, and indeed, our original leaders' output, without detecting strong sympathies for the Austrian School of Economics (Box 1). BOX 1 An Austrian's Lonely Lot The Austrian School of Economics most saliently parts company with neoclassical economics in its adamant opposition to government intervention and its fraught relationship with credit. Instead of intervening to counter business cycles, Austrians would prefer to let busts run their course so as to cleanse the economy of the excesses embedded in booms. They occupy the Mellonian, purge-the-rottenness-out-of-the-system end of the continuum in opposition to the Debt Supercycle's unconditional forgiveness. Austrians regard banking and credit with some measure of suspicion, as Austrian Business Cycle Theory holds that artificially low interest rates are the raw material of destabilizing booms. Encouraged by central bankers seeking to steer an economy out of recession with a bare minimum of discomfort, borrowers take on debt to invest in projects that may not be able to pay their own way were it not for intervention. Once rates rise after policy accommodation fades, the economy slows and the extent of the malinvestment is revealed. The Debt Supercycle prescribes more of the hair of the dog to alleviate the suffering from malinvestment. The debt overhang is thereby never eliminated; it instead continues to silt up, requiring larger and larger interventions. Unchecked, the degree of intervention required to keep the plates spinning will eventually exceed capacity. This analysis is logically sound, but it so thoroughly contradicts the reigning orthodoxy that an investor who becomes emotionally invested in it is at risk of serially tilting at windmills. There is nothing wrong with the Austrian School per se. We rather like its outsider status, and actively seek heterodox inputs and perspectives so as to stay out of the ruts of the well-worn consensus path. Even its pessimistic bent has its uses; investors are surely exposed to enough cheerleading. Its prescriptions are so bracing, however, that a little goes a long way and real-world users should handle them with care. A popular pair of You Tube videos of actors portraying Keynes and Hayek issuing dueling raps about their respective ideologies (Keynes: I want to steer markets/Hayek: I want them set free!) provide an entertaining example of the Austrian-inspired investor's dilemma. Keynes, drink after drink in hand, is the exuberant life of the party, while the sallow Hayek stares into the bottom of his glass, unable to capture any other partygoers' attention. The simple conceit animating the video - Keynesianism is fun; Austrians are dour scolds - resonates deeply with elected officials. Voters love free drinks, but hate being told to eat their vegetables. The Austrian School, therefore, is a poor guide to the path that policy is likely to take. It also has the problematic effect of introducing an element of moral judgment into what should be a purely objective sphere. Investors should have a laser-like focus on what is most likely to happen and should strive to suppress extraneous notions about what should happen. The Debt Supercycle is a brilliantly incisive way of viewing the interaction between constituents' desires and officials' incentives, and has predicted the long-run direction of policy to a T. Only someone with a focus on money flows, informed by exposure to Austrian Business Cycle Theory, could have come up with it. In the hands of BCA editors in the late '80s, however, it seemed to feed a desire to see the American economy get its comeuppance. Setting aside that desire for punishment - and value judgments altogether - is the clearest way that we could have done better in the aftermath of the crash 30 years ago, when BCA essentially sat out the December '87 - July '90 equity bull market. We should strive to be dispassionate and unbiased observers of the economy and markets. After all, the process illustrated by the Debt Supercycle concept has surely helped put the wind at equities' back throughout the postwar era (Chart 7). Making sense of it without decrying it could help us to provide even better counsel. Chart 7Equity Investing Is An Optimists' Game Equity Investing Is An Optimists' Game Equity Investing Is An Optimists' Game Then And Now Does 2017 look like 1987? Is another crash lurking just around the corner? Our answers are "no," and "no." We think the resemblances between then and now are merely superficial. The good news is that the probability of a Black Monday-style crash is remote, and we think that even a run-of-the-mill bear market is not likely until our most reliable recession leading indicators, which are still dormant, begin to flash red.5 While that view may come as a short-term relief, 1987's long-term market outlook was vastly superior. While both today's bull market and the '82-'87 bull market began with forward earnings multiples at multi-year lows, the trough multiple in 1982 was in the low sixes, nearly two standard deviations below the mean (Chart 8). Even though it more than doubled by the August '87 peak, it only just reached what is now the mean level for the entire series. This bull market has seen the S&P 500's forward multiple rise to a full standard deviation above the mean. Valuation is not everything, of course. It is a lousy short-term indicator and only issues a reliable intermediate-term signal at extremes. Long-term returns correlate closely with the cyclically-adjusted P/E ("CAPE"), however, and it is currently at levels only previously reached ahead of the 1929 and 2000 peaks (Chart 9). The frothy CAPE portends a tepid long-run U.S. equity outlook. Chart 8Not A Lot Of Room To Grow Not A Lot Of Room To Grow Not A Lot Of Room To Grow Chart 9Not The Stuff Of Secular Rallies Not The Stuff Of Secular Rallies Not The Stuff Of Secular Rallies Both of the bull markets emerged from the ashes of nasty recessions (Chart 10), but the periods' primary economic threats were polar opposites, as were the policy settings adopted to counteract them. The Volcker Fed tightened monetary conditions to the point of pain in the early '80s, plunging the economy into a double-dip recession for the express purpose of eradicating the scourge of double-digit inflation (Chart 11). After the financial crisis, on the other hand, the clear and present danger was the potential for the credit bust to trigger a deflationary spiral. The Bernanke Fed pursued unprecedentedly accommodative policy in response. Chart 10Similarly Nasty Recessions ... Similarly Nasty Recessions ... Similarly Nasty Recessions ... Chart 11... But Opposite Inflation Backdrops ... But Opposite Inflation Backdrops ... But Opposite Inflation Backdrops The policy measures of the early '80s were an example of swapping near-term pain for long-term gain, and they set the stage for secular rallies in financial assets that continue to this day. Once inflation was removed from the equation, interest rates had to fall, and they did so for 35 years. The extraordinary accommodation in the wake of the crisis was an attempt to stave off hysteresis, which boils down to mitigating near-term pain as an insurance policy against long-term pain.6 It may well have worked, but there is no such thing as a free lunch, and the Fed's exertions have likely pulled forward much of the bond and stock markets' future returns. Black Monday And The Fed Put Before the October 20th open, the Fed issued the following statement: The Federal Reserve, consistent with its responsibilities as the Nation's central bank, affirmed today its readiness to serve as a source of liquidity to support the economic and financial system. Although it was only 30 words long, the statement packed a punch. It signaled the Fed's willingness to fulfill its function as the lender of last resort and may also have prodded skittish banks into fulfilling their responsibilities as intermediaries. Behind the scenes, the Federal Reserve Banks of New York and Chicago were doing their utmost to keep the system functioning. New York Fed president Corrigan was twisting lenders' arms to keep credit flowing so the crash would not infect the banking system and the real economy.7 Meanwhile, the Chicago Fed wasn't letting the letter of the law keep it from "help[ing to] engineer a solution" when one of the biggest derivatives market participants "ran short of cash.8" The statement, and the vigorous offstage exertions, countered the Fed's determinedly low profile. These were the days, after all, when monetary policy actions were still regarded as something akin to state secrets. Wall Street firms employed "Fed watchers," who were charged with studying the tea leaves to determine if the Fed had adjusted policy. As late as January 1990, the Bank Credit Analyst could devote an entire Section III to the question, "Has the Federal Reserve Eased?" Some of Alan Greenspan's comments in his memoir may reflect after-the-fact boasting or burnishing, but Black Monday can be viewed as a policy watershed. After it, the Fed's conduct of monetary policy has become transparent to the point of oversharing. More meaningfully for investors, it marked the origin of the "Greenspan Put," the widespread notion among market participants that the Fed would do its best to ward off or mitigate financial market downdrafts. Are ETFs The New Portfolio Insurance? Responsibility for the crash cannot be precisely apportioned among factors, but all post-mortem analyses agree that portfolio insurance played a leading role. While it may well have proven harmless if pursued on a modest scale by a limited number of players, it morphed into a destabilizing force once a critical mass of investors embraced it. On Black Monday, it became a paradox of safety akin to the paradox of thrift: prudent and rational when practiced by one individual, but a metastasizing disaster when followed by a crowd. A reasonable roadmap for someone trying to spot parallels between then and now is to identify market products that may have become overly popular. Wall Street's tendency to wring every last drop out of financing innovations, coupled with investors' tendency to move in herds, can lead to excesses. The latest innovation to achieve wild popularity is the ETF. Is it possible that ETFs could exert the same destabilizing influence as portfolio insurance if investors' ardor for them suddenly cools? We think not. As our Global ETF Strategy service has argued, the claims about passive investing's dangers are overheated.9 The notion that index tracking is undermining price discovery disregards the power of incentives. Passive investing strikes us as the best cure for passive investing: if so many people are pursuing it that index-trackers begin to drown out active investors, the prospective returns to active investing will soar and money will rotate out of index-tracking strategies in sufficient quantity to correct the imbalance. Chatter about a passive bubble also fails to consider the source of fund flows into index-tracking ETFs. The oft-repeated statement, "so much money is flowing into ETFs that it's distorting prices across the board," does not hold up to scrutiny. Away from Japan and Switzerland, where QE purchases of ETFs are being funded with new yen and franc notes, ETFs are not being purchased with new investment capital that has materialized out of thin air. They are being purchased with existing investment capital that has merely been reallocated away from actively managed mutual funds (Chart 12). Chart 12Mirror Image Mirror Image Mirror Image Bubbles are always the result of speculative, excess-profit-seeking activity. Index-tracking ETFs are vehicles intended to deliver market returns. They are the opposite of a get-rich-quick scheme; they're the instrument investors turn to when they give up on quick riches. We do not worry that ETFs are the object of a bubble, or that they are in any way analogous to portfolio insurance in the fall of 1987. Investment Implications Black Monday was a one-off event that remained contained within the financial markets despite widespread fears that it would spread to constrict the broader financial system and the real economy. A lot has changed in 30 years, but the collision of algorithms, derivatives and global pressures squarely places it in our time. It is entirely possible that its elements could come together to create another massive single-day drop. A key difference between future single- or intra-day swoons, and the ones that have already occurred since the crisis, is that they will arrive while the Fed is tightening policy at the margin. The future swoons, then, may not be as likely to disappear quickly without leaving much of a mark. It may go too far to say that market infrastructure is vulnerable, but it would be too optimistic to assume that it has kept pace with the advances in rapid-fire trading and the increasing prevalence of algorithms. It may make sense for investors with less tolerance for risk to maintain an extra cash buffer to protect against swoons and to ensure that they have dry powder to exploit them when they materialize. We remain constructive on the global economy, however, and our house view recommends overweighting risk assets while maintaining below-benchmark duration within bond portfolios. We sympathize with investors who lament that nothing in the public markets is cheap, but synchronized global acceleration remains intact. None of our models are warning of imminent danger. We therefore remain fully invested but vigilant, seeking out signs that the long bull market may be running out of steam. After reviewing our shortcomings in the aftermath of Black Monday, however, we will seek with an open mind and will not attenuate our efforts by awaiting the rapture of a final reckoning, when the sheep and the goats will be separated according to their virtue. The whole point of policy makers' efforts to engineer a rising tide is to keep the goats, and the broader economy, from harm. Doug Peta, Senior Vice President Global ETF Strategy dougp@bcaresearch.com 1 Except in New Zealand, where Black Tuesday popped a bubble of such notable excess that the MSCI New Zealand Index today trades at less than two-thirds of its September 1987 high, and Japan, where the mania lasted until December 1989 and the MSCI Japan Index is still nearly 40% below its all-time high. 2 Index arbitrageurs would have followed the same pattern, but they were sidelined by delayed price quotes and the failure of the NYSE's automated order execution system, which kept them from accurately identifying and exploiting true arbitrage opportunities. 3 Portfolio insurance was no secret - it was estimated that $90 billion of assets were following the strategy - and its potential to amplify selling pressures in a vicious circle had been the subject of a widely followed Wall Street Journal column published a week before the crash. 4 Lefevre, Edwin. Reminiscences of a Stock Operator, John Wiley & Sons, Inc.: Hoboken (NJ), pp. 57-8. Until 1997, the prices of NYSE-listed stocks were quoted in eighth-of-a-dollar increments. 5 For details on the interaction between recessions and equity bear markets, please see the August 16, 2017 Global ETF Strategy Special Report, "A Guide to Spotting and Weathering Bear Markets," available at etf.bcaresearch.com. 6 Hysteresis is the process by which a negative cyclical phenomenon, if left unchecked, can evolve into a secular phenomenon. 7 Greenspan, Alan. The Age of Turbulence: Adventures in a New World, Penguin (New York): 2007, p.108. Greenspan disavowed knowledge of the details, but suggested that Corrigan, "the Fed's chief enforcer," "bit off a few earlobes" while encouraging bankers to keep in mind that, "'if you shut off credit to a customer just because you're a little nervous about him, but with no concrete reason, he's going to remember that'." 8 Greenspan, p. 110.

Highlights Since the release of our currency hedging report on September 29, 2017,1 we have received an overwhelming positive response from clients around the globe. We thank our clients for their appreciation of our research. Instead of answering client requests individually, we have decided to publish this follow-up report, in which we apply the same methodology to analyze both static and dynamic hedging strategies to hedge a global equity portfolio for the remaining three home currencies (Swiss franc, Swedish krona and Norwegian krone) in our nine-currency global equity universe. For investors based in Switzerland and Sweden, BCA's dynamic hedging framework, based on the proprietary currency indicators from BCA's Foreign Exchange Strategy (FES) service,2 has also outperformed all the static hedging strategies on a risk-adjusted basis since 2001. For Norway-based investors, however, BCA's dynamic hedging strategy does not generate consistently superior performance. Using static hedging, we find that the Swiss franc, together with U.S. dollar and Japanese yen, maintain their "safe-heaven currency" status, in the sense that CHF-, JPY- and USD-based investors should fully hedge foreign-currency exposure to minimize risk. However, our proposed dynamic hedging can achieve a better return/risk profile with less than 100% hedging. Over a four-year moving performance cycle (in line with how most portfolio managers are evaluated), BCA's dynamic hedging adds little career risk to portfolio managers in Switzerland and Sweden, compared to the "least regret" 50% static hedging, but the same cannot be said for Norwegian PMs. We recommend global equity investors based in the U.S., U.K., euro area, Japan, Canada, Australia, Switzerland and Sweden to use the BCA dynamic hedging framework to manage their foreign currency exposure. For Norwegian investors, we suggest "the least regret" 50% static hedging. Feature Dynamic Hedging Vs. Static Hedging We apply the same methodology as described in the previously published Special Report 3 to hedge an identical global equity portfolio into CHF, SEK and NOK using static and dynamic hedging strategies. As shown in Chart I-1, BCA's dynamic hedging strategy, based on the proprietary Intermediate-Term Timing Model (ITTM)4 indicators from the Foreign Exchange Strategy service, outperforms all static hedging strategies on a risk-adjusted basis for the CHF and SEK portfolios, in line with our findings for the other six home currencies. However, the same is not true for the NOK portfolio. Chart I-1Identical Investment, But Different Risk/Return Profiles Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors (Part II) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors (Part II) The Swiss Perspective: On a static-hedging basis, the Swiss franc holds its "reserve currency" status as classified by Campbell et al,5 in the sense that risk-minimizing Swiss-based investors should fully hedge foreign currency exposure. Unlike the other two "safe-haven" home currencies, the USD and JPY, for which a higher hedge ratio results in lower risk and lower return in both the 16-year period from 2001 and the 41-year period form 1976, the CHF-based portfolio has achieved higher return/lower risk in the 16-year period from 2001 as the hedge ratio increases. The ITTM-based dynamic hedging outperforms the best static hedging (100%) in the shorter period, but the simple momentum-based dynamic hedging is inferior to the best static hedging (90%) in the longer period (Chart I-1, top two graphs and Tables II-1 and II-2). Chart I-2Little Career Risk For Swiss ##br##And Swedish Portfolio Managers Little Career Risk For Swiss And Swedish Portfolio Managers Little Career Risk For Swiss And Swedish Portfolio Managers The Swedish Perspective: On a static-hedging basis, the SEK-based portfolio behaves in a similar way to the euro-based portfolio in both the shorter and longer periods. In the shorter period from 2001, a higher hedge ratio results in higher returns, albeit gradually, but risk decreases until the hedge ratio hits 30% and then starts to increase such that the full hedge has the highest risk. In the longer period from 1976, a higher hedge ratio results in a lower return, while risk decreases until the hedge ratio hits 70% and then starts to rise, such that the unhedged portfolio has the highest risk and the fully hedged portfolio has the lowest return. On a risk-adjusted basis, the best static hedge ratio is 50% for both the shorter and longer periods. Both the ITTM-based dynamic hedging and the momentum-based dynamic hedging are superior to the best static hedge ratio of 50% (Chart I-1, middle 2 graphs and Table II-3 and II-4). The Norwegian Perspective: On a static-hedging basis, the NOK-based portfolio behaves like the GBP-based portfolio in the longer period from 1976, with return increasing and risk decreasing as hedge ratio increases, but it behaves like the euro- and SEK-based portfolios in the shorter period from 2001. On a risk-adjusted return basis, both the ITTM-based and momentum-based dynamic hedging strategies underperformed the best static hedge which is about 80% hedged (Chart I-1, bottom 2 graphs and Tables II-5 and II-6). Little Career Risk for Swiss and Swedish Portfolio Managers: As shown in Chart I-2, on a rolling four-year basis, the ITTM-based dynamic hedging strategy has outperformed the best static hedging strategy for CHF portfolio (which is 100%) and the best static hedging strategy for SEK portfolio (which is 50%). For the NOK portfolio, however, neither the ITTM-based dynamic strategy, nor the "best static hedging" strategy (which is 80%) can consistently outperform the "least regret" 50% hedging strategy. Equal Playing Field: In theory, if hedges were effective, then an identical global investment should have similar returns for all investors, no matter which home currency they hold. While neither the static hedging strategies nor the momentum-based dynamic hedging approach pass this criteria, BCA's ITTM-based dynamic hedging approach has indeed achieved this: it levels out the playing-field for all investors globally. As shown in Chart I-3, in the period from March 2001 to August 2017, if left unhedged, the same global investment exhibits very different annualized returns for investors in different home currencies, with CHF investors at the low end at around 2.8%, and GBP investors at the high end at around 7%. With BCA's ITTM-based dynamic hedge, however, returns for all investors are similar, no matter which currency is their home currency. Chart I-3BCA Dynamic Hedging Strategy Levels Out The Playing Field Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors (Part II) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors (Part II) Bottom Line: We have back-tested the efficacy of BCA's proprietary currency indicators from the Foreign Exchange Strategy team's Intermediate-Term Timing Models to dynamically hedge a global investment portfolio into nine different home currencies. These indicators have proven to add significant value to eight out of the nine home currencies. Granted, back-tests show good results by default. But our FES team will strive to ensure that these indicators continue to work well going forward. We recommend global equity investors based in the U.S., U.K., euro area, Japan, Canada, Australia, Switzerland and Sweden to use BCA's ITTM currency indicator-based dynamic hedging framework to manage their foreign currency exposure. For Norway-based global equity investors, we suggest the "least regret" 50% static hedging. Xiaoli Tang, Associate Vice President xiaolit@bcaresearch.com Appendix 1: Dynamic Hedging For Three Home Currencies 1.1 The Swiss Perspective Correlations: For Swiss investors, foreign currencies in aggregate have generally been positively correlated with foreign equities and domestic equities (Chart II-1). In addition, the Swiss franc has strengthened over time, especially after 1999. This explains why, on a static basis, the fully hedged portfolio generates the best risk/return profile. (Table II-1 and Table II-2). Chart II-1Swiss Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Swiss Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Swiss Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Table II-1Risk/Return Profile For Global Equities In CHF (2001-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors (Part II) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors (Part II) Table II-2Risk/Return Profile For Global Equities In CHF (1976-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors (Part II) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors (Part II) Historical Performance: Since 2001, ITTM-based dynamic hedging has produced the highest risk-adjusted return for the global portfolio in CHF. The risk is slightly higher than the best static hedging (which is 100%), but the return is over 200 bps higher, resulting in a 40% increase in the risk-adjusted return (Table II-1). In addition, this is achieved with far fewer hedging transactions than the fully hedged strategy as shown in Chart II-2 panel 2. Over the longer period from 1976, the optimal static hedge ratio is about 90%, almost fully hedged as well, as shown in Table II-2. Chart II-2Swiss Perspective: Dynamic Vs. Static Hedging Swiss Perspective: Dynamic Vs. Static Hedging Swiss Perspective: Dynamic Vs. Static Hedging On a 60-month rolling basis, as shown in Chart II-2, the ITTM-based dynamic risk/return profile also prevails. Current State: Currently our indicators show that Swiss investors should not hedge any foreign currency. Chart II-3 shows how the Swiss investors should have hedged their exposure in U.S. dollar. Chart II-3Swiss Perspective: MSCI U.S. Index Dynamically Hedged Swiss Perspective: MSCI U.S. Index Dynamically Hedged Swiss Perspective: MSCI U.S. Index Dynamically Hedged 1.2 The Swedish Perspective Correlations: For Swedish investors, foreign currencies in aggregate have little correlation with domestic equities as the average correlation from 1980 is almost 0. This overall average can be misleading, however, as evidenced by the rolling 60-month correlation, which was positive before 1998 and then was negative until recently, and is now in the positive territory again (Chart II-4). This is a typical case where dynamic hedging would outperform static hedging, because the latter assumes constant mean and covariance for the chosen time period (Tables II-3 and II-4) Chart II-4Swedish Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Swedish Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Swedish Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Table II-3Risk/Return Profile For Global Equities In SEK (2001-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors (Part II) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors (Part II) Table II-4Risk/Return Profile For Global Equities In SEK (1976-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors (Part II) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors (Part II) Historical Performance: Since 2001, ITTM-based dynamic hedging has produced the highest risk-adjusted return in SEK for a global portfolio. The risk profile looks similar to that of the 50% hedged portfolio, but return is much higher, resulting in a 35% increase in the risk-adjusted return (Table II-3). Over the longer period, the optimal static hedge ratio is also 50%, as shown in Table II-4. On a five-year rolling basis, as shown in Chart II-5, the ITTM-based dynamic risk/return profile also prevails. Chart II-5Swedish Perspective: Dynamics Vs. Static Hedging Swedish Perspective: Dynamics Vs. Static Hedging Swedish Perspective: Dynamics Vs. Static Hedging Current State: Currently Sweden-based investors should be hedging only their exposure in Norwegian krona. Chart II-6 shows how the Swedish investors should have hedged their exposure in Canadian dollar. Chart II-6Swedish Perspective: MSCI Canadian Index Dynamically Hedged Swedish Perspective: MSCI Canadian Index Dynamically Hedged Swedish Perspective: MSCI Canadian Index Dynamically Hedged 1.3 The Norwegian Perspective Correlations: For Norway-based investors, foreign currencies in aggregate have a slightly negative correlation with domestic equities as the average correlation from 1980 is -0.12. This overall average can be misleading, however, as evidenced by the rolling 60-month correlation, which was above this long-run average before the Great Financial Crisis (GFC), but has been in negative territory ever since. On the other hand, the correlations between foreign currencies and foreign equities, and between foreign equities and domestic equities, have also gone though some regime changes (Chart II-7). Chart II-7Norwegian Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Norwegian Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Norwegian Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Historical Performance: Since 2001, ITTM-based dynamic hedging has produced 7% lower risk-adjusted return for the global portfolio in NOK compared to the best static hedging strategy of 80% (Tables II-5). In the longer period from 1976, the momentum-based dynamic also underperformed the 80% static hedging strategy by 3% on a risk-adjusted return basis (Tables II-6). Table II-5Risk/Return Profile For Global Equities In NOK (2001-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors (Part II) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors (Part II) Table II-6Risk/Return Profile For Global Equities In NOK (1976-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors (Part II) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors (Part II) On a five-year rolling basis, as shown in Chart II-8, the ITTM-based dynamic risk/return profile also looks less attractive. Chart II-8Norwegian Perspective: Dynamic Vs. Static Hedging Norwegian Perspective: Dynamic Vs. Static Hedging Norwegian Perspective: Dynamic Vs. Static Hedging Why does dynamic hedging not work? We do not have a good understanding on this yet. Looking at the individual currency pairs, we notice that our indicators work very well for CAD/NOK, SEK/NOK and JPY/NOK, but not for other pairs, especially during the period between 2011 and 2016 when NOK was strong against most of these currencies. Chart II-9 and Chart II-10 show how JPY/NOK and USD/NOK should have been hedged based on our indicators. The former worked very well, while the latter failed terribly in the period between 2013 and 2016. Chart II-9Norwegian Perspective: MSCI Japanese Index Dynamically Hedged Norwegian Perspective: MSCI Japanese Index Dynamically Hedged Norwegian Perspective: MSCI Japanese Index Dynamically Hedged Chart II-10Norwegian Perspective: MSCI U.S. Index Dynamically Hedged Norwegian Perspective: MSCI U.S. Index Dynamically Hedged Norwegian Perspective: MSCI U.S. Index Dynamically Hedged 1 Please see Global Asset Allocation and Foreign Exchange Strategy joint Special Report "Currency Hedging: Dynamic Or Static? - A Practical Gide For Global Equity Investors," dated September 29, 2017. 2 Please see Foreign Exchange Strategy Special Report, "In Search Of A Timing Model", dated June 22, 2016 3 Please see Global Asset Allocation and Foreign Exchange Strategy joint Special Report "Currency Hedging: Dynamic Or Static? - A Practical Gide For Global Equity Investors," dated September 29, 2017. 4 Please see Foreign Exchange Strategy Special Report, "In Search of A Timing Model", dated June 22, 2016 5 Campbell, J., K. de Medeiros and L. Viceira, 2010, "Global Currency Hedging," Journal of Finance LXV, 87-122

Dear Client, There is no regular report this week. Instead, I am sending you a Special Report written by colleague Mark McClellan, who examines global equity valuations from a bottom-up perspective using our Equity Trading Strategy (ETS) platform. I discussed the intellectual underpinnings for the ETS model in 2015. In addition, if you haven't done so already, please take a moment to listen to our latest webcast, where I survey the global macro landscape, drawing on the material published in our Quarterly Strategy Outlook. Best regards, Peter Berezin, Chief Global Strategist Highlights The performance of Japanese stocks relative to the U.S. has been dismal over the past couple of decades, and the same is true for Europe in the post-Lehman period. However, both the Japanese and European economies are performing impressively this year, profit growth is accelerating and margins are rising. This suggests that there could be some "catch up" for both markets, at least in local-currency terms. Standard valuation measures based on index data also suggest that Eurozone and Japanese stocks are cheap compared to the U.S. Nonetheless, these markets almost always trade at a discount, due to a persistent lackluster profit performance. In this Special Report, we approach the issue from a bottom-up perspective, utilizing the powerful analytics provided by BCA's exciting new Equity Trading Strategy (ETS) platform. The ETS software allows us to compare companies across markets on a head-to-head basis and rank them based on a wide range of characteristics. The bottom-up approach adjusts for structural valuation gaps between these markets and avoids the problems of index construction. Investors can have greater confidence that they will make money on a 12-month horizon by taking a position when the new bottom-up indicators reach +/-1 standard deviations over- or under-valued, although technical information should be taken on board to sharpen the timing. The +/-2 sigma level gives clear buy/sell signals irrespective of fundamental or technical factors. The bottom-up valuation indicators will not replace our top-down versions that are based on index data, but rather will be considered together when evaluating relative value. European stocks are near fair value relative to the U.S. at the moment, while Japan is modestly cheap. We favor the European and, especially, Japanese markets over the U.S., due to policy divergence and the view that EPS has more room to expand in the former two economies. Feature Chart 1European And Japanese Stocks Have Lagged... European And Japanese Stocks Have Lagged... European And Japanese Stocks Have Lagged... Japanese equities have been perennial underperformers versus the U.S. for most of the past 2-3 decades in both local- and common-currency terms (Chart 1). The simultaneous bursting of the equity and land bubbles in the 1990s ushered in a prolonged period of deflation in wages and consumer prices. There was a ray of light in the early years of Abenomics, when the aggressive three-arrow approach appeared to be finally lifting the Japanese economy out of a Secular Stagnation. Yen weakness contributed to a surge in earnings-per-share (EPS) in absolute terms and relative to the U.S. Equity multiples rose between 2012 and 2015. Unfortunately, Abe's honeymoon with equity markets faded in 2016 (Chart 2). A bout of yen strength, collapsing inflation expectations, weakening business confidence and a lack of progress on structural reforms caused investors to question the upside potential for Japanese corporate top-line growth. While European indexes have fared better than Japanese stocks relative to the U.S. over the past 25 years as a whole, the post-Lehman period has been particularly tough for European corporate profitability and relative equity market performance. The U.S. total return index has more than doubled its pre-recession peak according to Thomson Reuters/Datastream data, while the Eurozone total return index is only 10% above the previous high-water mark when expressed in U.S. dollars (Chart 2). The yawning return gap between the two equity markets was almost entirely due to earnings as market multiples have moved largely in sync. Earnings-per-share generated by U.S. companies now exceed the pre-recession peak by about 23%. In contrast, earnings produced by their Eurozone peers are a whopping 42% below their peak (common-currency). That said, the earnings backdrop now appears to be shifting. The strengthening global recovery is turbocharging EPS growth in Europe and Japan, where the corporate sector is more leveraged to global growth than is the case in the U.S. Eurozone domestic demand is also hot. Japan is still struggling with deflation, but the economy is performing well and the corporate sector is benefiting from this year's yen pullback. Japanese EPS is surging in both yen and dollar terms. Finally, both Europe and Japan appear cheap versus the U.S. by traditional valuation metrics. Based on index data, these two markets trade at a hefty discount across most of the main valuation measures (Chart 3). This is the case even for normalized measures such as price-to-book. However, these two markets have almost always traded at a discount to the U.S. Chart 2...Due To Depressed Fundamentals ...Due To Depressed Fundamentals ...Due To Depressed Fundamentals Chart 3Europe And Japan Trade At A Discount Europe And Japan Trade At A Discount Europe And Japan Trade At A Discount There are many possible explanations for the persistent valuation gap, including differences in accounting standards, discount rates and sector weights. The wider use of stock buybacks in the U.S. also favors American equity valuations. But most important are historical differences in underlying corporate fundamentals. U.S. companies on the whole have been significantly more profitable over the years based on return on equity and operating margins (Charts 4 and 5). Until recently, U.S. companies have also tended to have lower leverage relative to Europe and Japan, and a higher interest coverage ratio than Europe. Better profitability metrics in the U.S. are not solely an artifact of sector weighting either. Operating margins are lower in Europe and Japan even after applying U.S. sector weights to the other two markets (Chart 6). Chart 4RoE Is Consistently Lower In Japan And Europe RoE Is Consistently Lower In Japan And Europe RoE Is Consistently Lower In Japan And Europe Chart 5U.S./Europe/Japan Comparison U.S./Europe/Japan Comparison U.S./Europe/Japan Comparison Chart 6U.S./Europe/Japan Comparison (U.S. Sector Weights) U.S./Europe/Japan Comparison (U.S. Sector Weights) U.S./Europe/Japan Comparison (U.S. Sector Weights) Why the European and Japanese corporate sectors have been profit underachievers is beyond the scope of this paper. U.S. companies reaped most of the benefit from productivity gains over the past 25 years, with the result that the capital share of income soared while the labor share collapsed. European and Japanese companies were less successful in squeezing down labor costs. This raises the question of whether European and Japanese stocks are, in fact, cheap relative to the U.S. Measuring Value Our monthly Bank Credit Analyst publication developed top-down valuation indicators that adjust for different sector weights and persistent differences in the underlying profit fundamentals. These indicators are based on index data, and have a good track record for providing profitable buy/sell signals.1 In this Special Report, we take a bottom-up approach that utilizes the powerful analytics provided by BCA's Equity Trading Strategy (ETS) platform.2 The software allows us to compare companies on a head-to-head basis and rank them based on a wide range of characteristics. The bottom-up approach avoids the problems of index construction when trying to gauge valuation across countries. The web-based platform uses over 27 quantitative factors to rank approximately 10,000 individual stocks in 23 countries, allowing clients to find stocks with winning characteristics at the global level. Users can rank and score individual equities to support a broad set of investment strategies and apply macro and sector views to single-name investments. The ETS approach has an impressive track record.3 Historically, the top-decile of stocks ranked using the "BCA Score" methodology has outperformed stocks in the bottom decile by over 25% a year. The BCA Score includes 27 factors when ranking stocks, including sentiment and momentum. However, since we are interested in developing a valuation metric in this paper, we focus on five valuation measures in the ETS database: trailing P/E, forward P/E, price-to-book, price-to-sales and price-to-cash flow. We combined all of the Eurozone and U.S. companies that have total assets of greater than $1 billion into one dataset. The ETS platform then ranked the stocks from best to worst on a daily basis (i.e., cheapest to most expensive), using an equally-weighted average of the five valuation measures. The average score for U.S. stocks is subtracted from the average score for European stocks, and then divided by the standard deviation of the series. This provides a valuation metric that fluctuates roughly between +/- 2 standard deviations. This approach inherently adjusts for structural valuation gaps. We then used the same methodology to construct bottom-up valuation indicators for Japan relative to the U.S. Chart 7 presents the resulting bottom-up indicators for Europe and Japan, along with our top-down valuation measure. A high reading indicates that European or Japanese stocks are cheap relative to the U.S., while the opposite is true for low readings. Chart 7Top-Down And Bottom-Up Valuation Indicators Top-Down And Bottom-Up Valuation Indicators Top-Down And Bottom-Up Valuation Indicators The underlying bottom-up data extend back to 2000. However, the bursting of the tech bubble in the early 2000's caused major shifts in relative valuation among sectors that skew the indicator when constructed using the entire data set. A cleaner indicator emerges when using only the data from 2005. As with any valuation indicator, it is only useful when it reaches extremes. We calculated the historical track record for a trading rule that is based on critical levels of over- and under-valuation. For example, we calculated the (local-currency basis) excess returns over 3-, 6-, 12- and 24-month horizons generated by (1) overweighting European or Japanese stocks when that market was one and two standard deviations cheap versus the U.S. market, and (2) overweighting the U.S. when the European or Japanese market was one and two standard deviations expensive (Tables 1 and 2). Table 1Eurozone Vs. U.S. Value Indicator: Trading Rule Returns And Batting Average Valuing Stocks Using The BCA Equity Trading Strategy Platform Valuing Stocks Using The BCA Equity Trading Strategy Platform Table 2Japan Vs. U.S. Value Indicator: Trading Rule Returns And Batting Average Valuing Stocks Using The BCA Equity Trading Strategy Platform Valuing Stocks Using The BCA Equity Trading Strategy Platform The trading rule returns are best in the case of Europe when the indicator reached two standard deviations cheap or expensive, providing average returns of almost 11 percent over 12 months. The trading rule returns when the indicator reached +/-1 standard deviation are lower, but still respectable at roughly 3% on 12- and 24-month horizons. The results are even better for the Japan trading rule (Table 2). Excess returns are 14% and 35%, respectively, over 12 and 24-month horizons after the indicator reaches +/-2 standard deviations. The results are very impressive even when using +/-1 standard deviation as the trigger point. Tables 1 and 2 also present the trading rules' batting average. That is, the number of positive excess returns generated by the trading rule as a percent of the total number of signals. For the European indicator, the batting average ranged from 50% on a 3-month horizon to 68% over 12 months when buy/sell signals are triggered at +/- 1 standard deviation. The batting average is much higher (80-100%) using +/- 2 standard deviations as a trigger point, although there were only five months over the entire sample when the indicator reached this level. The batting average is even better for the Japanese indicator. Sharpening The Buy/Sell Signals We then augmented the valuation analysis by adding information on company fundamentals, such as EPS growth and profit margins, among others. The ETS software ranked the companies after equally-weighting the valuation and fundamental factors. However, this approach yielded poor results in terms of the trading rule. This is because, for example, when European stocks reached undervalued levels relative to the U.S., it is usually because the European earnings fundamentals have underperformed those of the U.S. companies. Thus, favorable value is offset by poor fundamentals when scored by the ETS model, muddying the message provided by valuation alone. We also tried including some technical indicators to see if they could add information on timing. Chart 8 compares the valuation indicator discussed above to an enhanced indicator that includes both value and technical factors. Tables 3 and 4 provide the excess returns and batting averages for a trading rule based on the enhanced indicator. Chart 8Bottom-Up Indicators: Value, And Value Plus Technical Bottom-Up Indicators: Value, And Value Plus Technical Bottom-Up Indicators: Value, And Value Plus Technical Table 3Eurozone Vs. U.S. Value And Technical Indicator: Trading Rule Returns And Batting Average Valuing Stocks Using The BCA Equity Trading Strategy Platform Valuing Stocks Using The BCA Equity Trading Strategy Platform Table 4Japan Vs. U.S. Value And Technical Indicator: Trading Rule Returns And Batting Average Valuing Stocks Using The BCA Equity Trading Strategy Platform Valuing Stocks Using The BCA Equity Trading Strategy Platform It turns out that including some technical information does add value, but only in the case of Europe when using +/-1 standard deviation as the trigger point for trades. Both the excess returns and batting average to the trading rule improve. However, this is not the case when using +/-2 sigma. In the case of Japan, including technical information detracts from excess returns for both trigger points. Investment Conclusions Our new ETS platform provides investors with a unique way of picking stocks by combining top-down macro themes with company-specific information. It also allows us to develop valuation tools that avoid some of the pitfalls of index data by comparing stocks on a head-to-head basis. Investors can be fairly confident that they will make money on a 12-month horizon by taking a position when the bottom-up valuation indicators reach +/-1 sigma over- or under-valued. The +/-2 sigma valuation level gives clear buy/sell signals irrespective of fundamental or technical factors for both Europe and Japan. The bottom-up valuation indicators will not replace our top-down versions, but rather will be considered together when evaluating relative value. At the moment, both the top-down and bottom-up versions suggest that European stocks are roughly fairly valued relative to the U.S. market. Japanese stocks are on the cheap side based on both indicators, but neither one exceeds +1 sigma. This means that investors cannot make the allocation decision based on value alone. Valuation indicators need to be at extremes to have any predictive power. Our global equity strategists recommend overweighting Eurozone stocks versus the U.S. on a currency-hedged basis, although not because of valuation. On the plus side, the economy is flying high and there are no warning signs that this is about to end. There is hope for structural reform in France after Macron's election win this year. We give Macron's proposed labor market reforms high marks. Many doubt that these reforms will see the light of day, but our geopolitical team believes that investors are underestimating the chances. The German election in September poured cold water on recent enthusiasm regarding accelerated European integration. This is because Merkel will likely have to deal with a larger contingent of Euroskeptics in the grand coalition that emerges in the coming months. However, we do not expect political developments in Germany to be a headwind for the Eurozone stock market. On the negative side, this year's euro bull phase will take a bite out of earnings. Euro strength so far this year will lop three to four percentage points off of EPS growth by the middle of next year. Our model suggests that this will be overwhelmed by the robust economic expansion at home and abroad, but profit growth will diminish heading into year-end and will likely trail that in the U.S. and Japan over the next six months (local-currency basis). Still, a lot of the negative impact of the currency on profits may already be discounted. The bullish case versus the U.S. is more compelling for the Nikkei, at least in local-currency terms. Valuation is modestly attractive and Japanese earnings are highly geared to economic growth at home and abroad. Japanese EPS is in an uptrend versus the U.S. in both local and common currencies. We do not expect to see a peak in EPS growth until mid-2018, a good six months after the expected top in the U.S. Moreover, an Abe win in the October 22 election would mean that policy will remain highly reflationary in absolute terms and relative to the U.S. However, overweight positions in both the European and Japanese bourses should be currency hedged because the dollar is likely to appreciate over the next 6-12 months due to monetary policy divergences. Mark McClellan, Senior Vice President The Bank Credit Analyst markm@bcaresearch.com 1 Please see The Bank Credit Analyst Special Report, "Are Eurozone Stocks Really That Cheap?" dated July 2016. 2 Please see Equity Trading Strategy Special Report, "Introducing ETS: A Top Down Approach To Bottom-Up Stock Picking," dated December 2, 2015. 3 For more information, please see Equity Trading Strategy Special Report, "Making Money with ETS," dated January 20, 2016 Strategy & Market Trends Tactical Trades Strategic Recommendations Closed Trades

Highlights It is often argued that the U.S. dollar is expensive, but models do not offer a unanimous picture. The U.S. current account, exports share, and cyclical inflation do not point to an obvious dollar overvaluation either. Without a clear valuation signal, the dollar will continue to trade off rate differentials. An increasing body of evidence points toward a rebound in U.S. inflation. As such, U.S. rates are likely to move up relative to the rest of the world, lifting the USD over the next 12 months. Feature We are sending you a shorter regular bulletin this week as we are also publishing a follow up to our joint Special Report titled, "Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors," released with the Global Asset Allocation team two weeks ago. In this follow-up, my colleague Xiaoli Tang expands on the same methodology, testing various FX-hedging strategies for international investors - but this time looking at portfolios based in the CHF, the SEK, and the NOK. In this week's regular bulletin, we take a closer look at the U.S. dollar's valuations. The consensus view is that the dollar is expensive. We explore how this claim stacks up against the facts. At this juncture, the U.S. economy is not exhibiting some of the key consequences typical of an economy burdened by an expensive currency. Valuation Models The main argument used by some investors to show that the U.S. dollar is expensive is the traditional purchasing power parity model. This indicator does indeed flag a large 17% overvaluation for the greenback (Chart I-1). However, this is only one metric based on producer price indices. We also like to look at measures that focus on the true determinant of competitiveness: the cost of labor. When we deflate the U.S. dollar's exchange rate using unit labor costs, the dollar is neither a screaming sell nor a screaming buy. It is in line with its long-term average (Chart I-2). The same IMF real effective exchange rate model based on unit labor costs also shows the euro as fairly valued. Thus, on this metric, valuations do not seem to provide a compelling argument to go long or short the dollar, which challenges the universally bearish take on the dollar's perceived overvaluation. Chart I-1An Argument For An###br## Expensive USD An Argument For An Expensive USD An Argument For An Expensive USD Chart I-2But Not All Valuation Approaches ##br##Are That Clearcut But Not All Valuation Approaches Are That Clearcut But Not All Valuation Approaches Are That Clearcut We can also double-check the result of this metric using our own long-term fair value model, which incorporates long-term relative productivity trends. This model tries to capture the so-called Balassa-Samuelson effect. This effect is an empirical observation that countries with superior long-term labor productivity trends tend to experience a secular upward bias on their real exchange rates. The perceived overvaluation of the U.S. dollar may in fact be an illusion, because when the Balassa-Samuelson effect is taken into account, the dollar currently trades in line with its fair value (Chart I-3). Chart I-3Another Global Approach With USD At Fair Value Another Global Approach With USD At Fair Value Another Global Approach With USD At Fair Value Bottom Line: Valuing currencies is always an exercise to be approached with plenty of circumspection. It is easy to look at simple PPP models and argue that the dollar looks very expensive. However, when one takes into account labor market costs and productivity trends, the dollar seems fairly valued. A Look At The Symptoms Chart I-4The U.S. Current Account##br## Shows Little Dollar Strain The U.S. Current Account Shows Little Dollar Strain The U.S. Current Account Shows Little Dollar Strain Models are only as good as their inputs. It is important to try to corroborate their insights with economic reality. An expensive currency should produce three major outcomes: the country's current account position should be deteriorating, its market share of global exports should be falling, and it should be experiencing deep deflationary pressures relative to the rest of the world. Let's begin with the current account. Despite a 17% increase in the U.S. dollar since 2014, the U.S. current account has remained stable (Chart I-4). It is undeniable that this reflects an improvement in the energy trade balance of the U.S., itself a byproduct of the shale revolution. Nonetheless, it also highlights that there is little balance-of-payments strains in the U.S. In fact, the move away from energy imports in itself should point to a higher level of equilibrium for the dollar. The export share of the U.S. also does not point to too much stress created by the dollar bull market. As Chart I-5 illustrates, in contrast to the early 1980s or late 1990s-early 2000s, U.S. exports has been faring well when compared to the rest of the world. This exercise needs to be conducted by comparing U.S. exports to the rest of the world excluding China. China has been grabbing global market share from everyone for 30 years. As an aside, the continued rise of China, as well as its still-large current account surplus of more than US$155 billion, supports the idea that the RMB is indeed cheap and remains attractive on a long-term basis - a message also flagged by our long-term fair value model for the CNY (Chart I-6). Chart I-5Growing U.S. Market Share Growing U.S. Market Share Growing U.S. Market Share Chart I-6The Yuan Is Clearly Cheap The Yuan Is Clearly Cheap The Yuan Is Clearly Cheap Finally, there is little evidence that the U.S. dollar is depressing U.S. inflation on a cyclical basis. Changes in financial conditions can temporarily redistribute inflationary pressures between the U.S. and the rest of the world, but an expensive dollar should depress U.S. inflation for an extended period of time on a global relative basis. An expensive U.S. dollar makes the U.S. uncompetitive, and should force some degree of internal adjustment on the U.S. economy. So far, the two-year moving average of U.S. core inflation relative to the OECD does not show the same kind of swoon as in the 1980s or late 1990s. In fact, even after this year's inflation slowdown in the U.S., American inflation remains in an uptrend relative to the rest of the OECD (Chart I-7). One source of worry remains the U.S. net international investment position (NIIP). The U.S.'s NIIP currently stands at -41% of GDP, and despite stabilizing for the past two years, has been in a pronounced downtrend over the past 35 years. Historically, countries like Switzerland or Japan with strong NIIPs have tended to experience long-term upward pressure on their exchange rates, while those with poor NIIPs such as South Africa tend to experience negative secular trends, even in real terms. For the time being, what keeps the negative impact of the NIIP on the USD at bay is that the U.S. continues to earn a positive net income - despite negative net assets abroad (Chart I-8). This reflects the willingness of investors to hold the U.S. dollar for its reserve currency status. For the time being, with a lack of alternative to challenge the U.S. dollar's reserve status, the NIIP should not represent a key hurdle for a few more years. Chart I-7The U.S. is Not Experiencing##br## An Internal Devaluation The U.S. is Not Experiencing An Internal Devaluation The U.S. is Not Experiencing An Internal Devaluation Chart I-8The Exorbitant ##br##Privilege The Exorbitant Privilege The Exorbitant Privilege Bottom Line: The U.S. economy is currently exhibiting few of the signals that would be associated with an expensive dollar: the current account remains well behaved, the country is not losing export market shares to its main competitors, and U.S. inflation remains well behaved relative to the rest of the OECD on a cyclical basis. A key risk remains the U.S.'s net international investment position, but so long as the USD can maintain its unchallenged role as the key reserve in the global financial system, the U.S. is likely to continue to run an income surplus vis-à-vis the rest of the world. So What? When it comes to the FX space, long-term valuations only become binding constraints when they are in the extreme. Right now, there is enough conflicting evidence to suggest that if the dollar is indeed expensive, it is not expensive enough to flash a bright sell signal. In this case, the U.S. dollar's dynamics are likely to be dominated by interest rate differentials. Interest rate curves outside of the U.S. seem currently fairly priced, but this is not the case in the U.S. Thus, with only two full hikes priced in over the next 24 months, one needs to see upside for U.S. interest rates if one is to be bullish on the greenback. Despite last month's very poor employment numbers, a consequence of hurricanes Harvey and Irma, the labor market remains strong enough to justify the Federal Reserve's desire to hike rates. The ISM surveys also remains very strong, with the headline numbers and new order components pointing toward robust growth. The only factor that could impede the Fed is inflation. On this front, we remain optimistic that inflation will not deteriorate much further and that, in fact, it is likely to pick up over the next six months, giving the Fed a green light to increase rates in line with its own forecast: First, in the past, we have highlighted that velocity of money - based on the money of zero maturity and nominal GDP - has been a very reliable leading indicator of inflation over the past 20 years, and is pointing toward a rebound in core inflation measures toward year-end.1 Moreover, the easing in U.S. financial conditions over the past 18 months also points toward upside risks to both U.S. growth and inflation. Second, the strength in the Prices-Paid component of both ISM surveys further increases our optimism. Moreover, the recent vigor of the Supplier Delivery subcomponent - a measure of bottlenecks in the system - also points to pipeline inflationary pressures. It is true that some of the recent spike is most likely skewed by the devastating impact of the hurricanes, but this improving trend began much earlier this year. Historically, a combined improvement in both the Prices-Paid and the Supplier Delivery components of the ISM survey tends to provide long leads on core inflation (Chart I-9). Third, the New York Fed has recently started publishing an underlying inflation trend estimate. This measure has also been rebounding sharply, hitting its highest level in 10 years, also pointing toward higher core inflation (Chart I-10). Chart I-9Pipeline Inflationary Pressures##br## Are Growing In The U.S. Pipeline Inflationary Pressures Are Growing In The U.S. Pipeline Inflationary Pressures Are Growing In The U.S. Chart I-10Underlying Inflationary ##br##Pressures Are Growing Underlying Inflationary Pressures Are Growing Underlying Inflationary Pressures Are Growing Fourth, the behavior of inflation itself is somewhat encouraging. While the recent core PCE year-over-year numbers have been disheartening, the three-month annualized rate of change has picked up robustly. Historically, this has also led to turning points in the year-on-year number (Chart I-11). Finally, there are signs of underlying vigor in wages. Last week's U.S. average hourly earnings number clicked in at 2.9%.It was likely overinflated by the effect of the hurricanes, which have temporarily dropped workers in low-paid industries out of the sample used by the U.S. Bureau of Labor Statistics to compute this data. However, the median average hourly earnings across the key sectors covered by the BLS has been in an uptrend since the beginning of the year (Chart I-12), pointing to some faint but real early signs of rising underlying wage growth. Moreover, while much ink has been spilled regarding whether or not the Philips curve is flat, there remain a well-defined tight relationship between the U.S. employment cost index (ECI) and the level of employment-to-population ratio in the U.S. (Chart I-13). Our view that employment growth will likely continue to tick in north of 120,000 jobs for the next 12 months, implies further improvement in the employment-to-population ratio, and thus a growing ECI. This will both support household income and consumption as well as our inflation view. Chart I-11Sequential Inflation Pointing ##br##To A Turning Point Sequential Inflation Pointing To A Turning Point Sequential Inflation Pointing To A Turning Point Chart I-12Cross-Sectional Median ##br##Of Wages Improving The Cross-Sectional Median Of Wages Improving The Cross-Sectional Median Of Wages Improving Chart I-13The Cross-Sectional Median##br## Of Wages Improving Is The Dollar Expensive? Is The Dollar Expensive? Bottom Line: With no clear message from long-term valuation, the key driver of the dollar is likely to remain interest rate differentials. At this point, U.S. interest rates need U.S. inflation to be able to rise by more than what is implied in the OIS curve and lift the dollar. Signs continue to accumulate that U.S. inflation is likely to turn the corner over the next six months, thanks to an easing in U.S. financial conditions and the pick-up in the velocity of money: the Prices-Paid and Supplier Deliveries components of the ISM have hooked up significantly, the NY Fed's underlying inflation measure is strong, the sequential growth rate in core inflation is improving, and there are growing signs that wage growth in the U.S. is picking up. Mathieu Savary, Vice President Foreign Exchange Strategy mathieu@bcaresearch.com 1 Please see Foreign Exchange Strategy Weekly Report titled "Fade North Korea, And Sell The Yen", dated August 11, 2017, or Foreign Exchange Strategy Weekly Report, titled "Conflicting Forces For The Dollar", dated September 8, 2017, available at fes.bcaresearch.com Trades & Forecasts Forecast Summary Core Portfolio Closed Trades

Highlights Year One Performance: The GFIS recommended model bond portfolio returned 1.1% (hedged into USD) in its first year of existence, slightly underperforming the custom benchmark index by -2bps. Our bearish duration tilts were a drag on performance, while our overweights to U.S. corporate debt were a major contributor. Risk Management Lessons: The maximum overweight to low-beta, but low-yielding, Japanese Government Bonds was a drag on performance by reducing the portfolio yield. This highlights the classic bond management trade-off between controlling portfolio risks, like duration or tracking error, and maximizing sources of return, like interest income. Future Drivers Of Returns: Over the next 6-12 months, we expect the model portfolio returns to again benefit mostly from our below-benchmark duration stance (as global bond yields grind higher) and from our overweight stance on U.S. corporates (as the U.S. economy maintains a solid pace of growth). Feature In September of 2016, we introduced a new element to the BCA Global Fixed Income Strategy (GFIS) service - our recommended model bond portfolio.1 This represented a bit of a departure from the usual macroeconomic analysis and forecasting of financial markets that has been the hallmark of BCA. Yet we felt that it was important to add an actual portfolio, with specific allocations and weightings, given the needs and constraints faced by our readers. With so many of our clients being traditional fixed income managers (or multi-asset managers) who measure investment performance versus benchmark indices, we felt that it was important to have a way to communicate our views within a framework akin to what they deal with each day. Even for clients who are not professional bond managers, the model portfolio can be useful as a way to express how much we prefer one bond market (or sector) versus others. It also gives us a forum to discuss portfolio management issues as an addition to the macro analysis. So far, the reception from clients to this new addition to the GFIS service has been a warm one, and we look forward to additional feedback in the months and years ahead. With the model portfolio just passing its first birthday, we are dedicating this Weekly Report to an overview of the final Year One performance numbers. We will evaluate our winning and losing recommendations, look back at the lessons learned as the model portfolio framework has evolved, and identify what we expect will be the biggest drivers of performance in Year Two based on our current views. Year One Model Portfolio Performance: Winners & Losers Chart 1GFIS Model Portfolio Performance GFIS Model Portfolio Performance GFIS Model Portfolio Performance The GFIS model portfolio produced a total return of 1.09% (hedged into U.S. dollars) over first full year since inception on September 20, 2016 (Chart 1). This essentially matched the performance of our custom benchmark index, with the model portfolio lagging by a mere -2bps.2 In terms of the breakdown between government bonds and credit (spread product), the former underperformed the benchmark by -18bps while the latter outperformed by +16bps. A more traditional period to evaluate investment performance is on a calendar year-to-date basis. We also show the 2017 year-to-date (YTD) numbers in Chart 1, measured from January 1st to October 3rd. Over that time period, the total returns are much higher - the model portfolio has returned 2.78%, lagging the index by -6bps. This higher absolute return is mostly due to the strong outperformance of corporate bond markets and the decline in government bond yields seen since March. Broadly speaking, that breakdown of returns lines up with what were our largest strategic market calls: to be underweight overall portfolio duration and overweight U.S. corporate bond exposure (bottom panel). This is obviously a welcome property to see in our returns, which we hope will always line up with our desired tilts! When looking at the detailed decomposition of the returns on the government bond side of the portfolio (Table 1), however, a few points stand out: Table 1A Detailed Breakdown Of The GFIS Model Portfolio Year One Of The GFIS Model Bond Portfolio: Winners, Losers & Lessons Learned Year One Of The GFIS Model Bond Portfolio: Winners, Losers & Lessons Learned The underperformance on the government bond side of the portfolio (Chart 2) came from underweight positions at the long-end (maturities beyond seven years) of yield curves in the U.S. (-4bps), U.K. (-5bps), Germany (-5bps) and, most notably, France (-18bps). Chart 2GFIS Model Portfolio Government Bond Performance Attribution By Country Year One Of The GFIS Model Bond Portfolio: Winners, Losers & Lessons Learned Year One Of The GFIS Model Bond Portfolio: Winners, Losers & Lessons Learned The underweight position in Italy, across the curve, generated another -7bps of underperformance, although this was paired against an overweight to Spanish government bonds that positively contributed to returns (+3bps). Overweights to bonds in the middle and shorter ends of yields curves (maturities less than seven years) positively contributed to returns in the U.S. (+6bps), Germany (+2bps) and France (+2bps). Our significant overweight to Japanese government bonds, intended as a way to reduce portfolio duration by increasing exposure to a market with a low beta to global bond yields, also helped boost performance (+8bps). The conclusion? By concentrating our recommended duration underweights on longer-maturity bonds, and raising the weightings on shorter-maturity government debt, we imparted a bearish curve steepening bias on top of the reduced duration exposure. It is no surprise that our recommended government bond allocations underperformed during the bull-flattening move in global yield curves seen earlier this year. By contrast, the returns on the credit (spread) product allocations within the GFIS model portfolio tell a more positive story (Chart 3): Chart 3GFIS Model Portfolio Spread Product Performance Attribution Year One Of The GFIS Model Bond Portfolio: Winners, Losers & Lessons Learned Year One Of The GFIS Model Bond Portfolio: Winners, Losers & Lessons Learned The outperformance came from our overweight allocations to U.S. Investment Grade (IG) corporate debt, focused on Financials (+14bps) and Industrials (+4bps), and U.S. High-Yield (HY), concentrated on Ba-rated (+13bps) and B-rated (+8bps) bonds. U.S. Mortgage-Backed Securities (MBS) were a laggard during the first year of the model bond portfolio (-12bps), which largely came from an ill-timed tactical move to overweight in the 4th quarter of 2016. More recently, our underweight stance on MBS has been only a modest drag on the total return of the portfolio since the peak in U.S. bond yields back in March. Our decisions to reduce exposure to Euro Area IG (-5bps) and HY (-2bps) corporate debt earlier in the year, and our more recent decision to downgrade Emerging Market (EM) sovereign (-1bp) and corporate debt (-4bps), were both small negative contributors to performance. Summing it all up, our spread product allocations performed well because of the overweight to U.S. IG and HY corporates. The underweights in Euro Area and EM credit were set up as relative value allocations versus U.S. equivalents, so the underperformance versus the benchmark should be viewed against the substantial outperformance from U.S. corporates. The MBS underperformance was small on a YTD basis, but we see an opportunity for that to soon turn around, as we discuss later. Bottom Line: The GFIS recommended model bond portfolio returned 1.1% (hedged into USD) in its first year of existence, slightly underperforming the custom benchmark index by -2bps. Our bearish duration tilts were a drag on performance, while our overweights to U.S. corporate debt were a major contributor. Lessons Learned On Risk Management As the first year of the GFIS model portfolio progressed, we added elements to the framework to help us manage the overall risk of the portfolio. Specifically, we began to include a tracking error calculation to show the relative volatility of the portfolio to its benchmark.3 When we first introduced that tracking error back in April, we were running far too little risk in the portfolio given the relatively modest position sizes (Chart 4). Rather than be an "index hugger", we decided to increase the sizes of all our relative tilts (Chart 5), and the tracking error rose accordingly from a mere 25bps to over 60bps. This is still below the 100bps limit that we decided to impose on the relative volatility of the model portfolio, but we were comfortable not running less-than-maximum risk given that valuations on many spread products were not extraordinarily cheap. The time to max out a risk budget is early in the credit cycle when spreads are wide, not when the cycle is far advanced and spreads are relatively tight. Yet one lesson that was learned in Year One was that too much focus on tracking error can result in lost opportunities to boost the performance of the portfolio. As part of our strategic call to maintain a below-benchmark overall duration stance, we upgraded Japan to maximum overweight in the model portfolio back on July 4th.4 With Japanese Government Bonds (JGBs) having such a low beta to yield changes in the overall Developed Markets (Chart 6), adding more Japan exposure was a way to get more defensive on duration in a way that would also boost our desired tracking error (since we were adding more of an asset less correlated to the other government bonds in the portfolio). Chart 4Tracking Error Of##BR##The Model Portfolio Tracking Error Of The Model Portfolio Tracking Error Of The Model Portfolio Chart 5Allocations Between##BR##Government Bonds & Spread Product Year One Of The GFIS Model Bond Portfolio: Winners, Losers & Lessons Learned Year One Of The GFIS Model Bond Portfolio: Winners, Losers & Lessons Learned Chart 6Are JGBs The##BR##Optimal Duration Hedge? Are JGBs The Optimal Duration Hedge? Are JGBs The Optimal Duration Hedge? Yet by increasing the allocation to low-beta JGBs, we were also adding exposure to "no-yield" JGBs. The overall yield of the model portfolio suffered as a result, fully offsetting the bump to the portfolio yield from the increase in allocations to spread product in April (Charts 7 & 8). With the benefit of hindsight, increasing the allocation even more to something like U.S. HY corporate bonds would have a been a more prudent way to redirect government bond exposure to a low-beta market that would have boosted the overall portfolio yield (Chart 9). Chart 7Too Much Japan##BR##In The Portfolio ... Too Much Japan In The Portfolio... Too Much Japan In The Portfolio... Chart 8... Offsetting The Yield Pick-Up##BR##From Spread Product ...Offsetting The Yield Pick-Up From Spread Product ...Offsetting The Yield Pick-Up From Spread Product Chart 9There Is Not Enough Yield##BR##In The Model Portfolio There Is Not Enough Yield In The Model Portfolio There Is Not Enough Yield In The Model Portfolio Going forward, we will pay more attention to managing the portfolio yield more actively as another piece of our model bond portfolio framework that can help boost expected returns. Bottom Line: The maximum overweight to low-beta, but low-yielding, Japanese Government Bonds was a drag on performance by reducing the portfolio yield. This highlights the classic bond management trade-off between controlling portfolio risks, like duration or tracking error, and maximizing sources of return, like interest income. The Outlook For The Next Year Looking towards the next twelve months, the biggest expected drivers of returns in our model bond portfolio are expected to come from the following allocations: Below-benchmark overall duration exposure: We are sticking to our guns on the future direction of global bond yields, which have more room to rise over the next 6-12 months. The coordinated global economic upturn is showing little sign of slowing, with leading indicators still rising and pointing to upward pressure on real bond yields (Chart 10). At the same time, inflation expectations in the developed economies remain too low relative to current levels of inflation (bottom panel). Thus, we expect government bond yield curves to bear-steepen as central banks will respond slowly to the rise in inflation. This will benefit the steepening bias we have in the model portfolio from the underweights in longer maturity buckets in the U.S., Europe and the U.K. (Chart 11). Chart 10Future Drivers Of Performance:##BR##Below-Benchmark Duration Future Drivers Of Performance: u/w Duration Future Drivers Of Performance: u/w Duration Chart 11An Unexpected##BR##Bull Flattening This Year An Unexpected Bull Flattening This Year An Unexpected Bull Flattening This Year Overweight U.S. corporate bonds (both IG and HY): Looking over the indicators from our U.S. Corporate Bond Checklist, the backdrop is not yet pointing to a period of expected underperformance for U.S. corporates (Chart 12). While balance sheet fundamentals do appear stretched, as indicated by our Corporate Health Monitor (2nd panel), the overall stance of U.S. monetary conditions is neutral (3rd panel), while bank lending standards are not yet restrictive (4th panel). We expect the Fed to deliver another 25bp rate hike in December, and at least another 2-3 hikes in 2018, which will shift monetary conditions into more restrictive territory. A very rapid rise in the U.S. dollar would worsen this trend, but we expect only a moderate grind higher in the greenback as the Fed slowly delivers additional rate hikes and non-U.S. growth remains robust. While the solid global economic backdrop should benefit all growth-sensitive assets like corporate debt, we see more attractive relative valuations on U.S. corporates versus Euro Area or EM equivalents. The upcoming tapering of asset purchases by the European Central Bank (ECB) also represents a major risk to Euro Area corporate debt, as the ECB will be slowing the pace of its corporate bond buying. One other sector that can potentially boost the portfolio performance in Year Two versus Year One is U.S. MBS. Our colleagues at our sister service, U.S. Bond Strategy, now see MBS valuations as looking attractive to other U.S. spread product like IG corporates (Chart 13).5 The relative option-adjusted spreads (OAS) on MBS and U.S. IG are a good leading indicator of the relative performance of the two asset classes and current spread levels should lead to a better return profile for MBS over IG. Another factor benefitting MBS is the continued rising trend in U.S. bond yields (and mortgage rates) that we expect over the next 6-12 months, which will reduce mortgage prepayments that would weigh on MBS returns (bottom panel). Chart 12Future Drivers Of Performance:##BR##Overweight U.S. Corporates Future Drivers Of Performance: o/w U.S. Corporates Future Drivers Of Performance: o/w U.S. Corporates Chart 13Upgrade U.S. MBS##BR##To Neutral Upgrade U.S. MBS To Neutral Upgrade U.S. MBS To Neutral This week, we are upgrading our MBS allocation to neutral from underweight in our model portfolio. However, given that our allocations to U.S. corporates are already fairly significant, we are choosing to "fund" the MBS upgrade by lowering our weighting on U.S. Treasuries (see the model portfolio allocations on Page 14). Bottom Line: Over the next 6-12 months, we expect the model portfolio returns to again benefit mostly from our below-benchmark duration stance (as global bond yields grind higher) and from our overweight stance on U.S. corporates (as the U.S. economy maintains a solid pace of growth). We are also now more constructive on valuations on U.S. MBS, thus we are upgrading our allocation to neutral at the expense of U.S. Treasuries. Robert Robis, Senior Vice President Global Fixed Income Strategy rrobis@bcaresearch.com 1 Please see BCA Global Fixed Income Model Special Report, "Introducing Our Recommended Global Fixed Income Portfolio", dated September 20th, 2016, available at gfis.bcaresearch.com. 2 The GFIS model portfolio custom benchmark index can most simply be described as the Barclays Global Aggregate Index, but with allocations to global high-yield corporate debt replacing very highly-rated spread product. We believe this to be more indicative of the typical internal benchmark used by global multi-sector fixed income managers. 3 Please see BCA Global Fixed Income Strategy Special Report, "Adding A Risk Management Framework To Our Model Bond Portfolio", dated June 20th 2017, available at gfis.bcareseach.com. 4 Please see BCA Global Fixed Income Strategy Weekly Report, "Central Banks Are Now Playing Catch-Up", dated July 4th 2017, available at gfis.bcaresearch.com. 5 Please see BCA U.S. Bond Strategy Weekly Report, "Dollar Watching: Yet Another Debate", dated October 10th 2017, available at usbs.bcaresearch.com. The GFIS Recommended Portfolio Vs. The Custom Benchmark Index Year One Of The GFIS Model Bond Portfolio: Winners, Losers & Lessons Learned Year One Of The GFIS Model Bond Portfolio: Winners, Losers & Lessons Learned Appendix - Selected Sectors From The GFIS Model Portfolio Appendix 1 Appendix 1 Appendix 2 Appendix 2 Appendix 3 Appendix 3 Appendix 4 Appendix 4 Appendix 5 Appendix 5 Appendix 6 Appendix 6 Appendix 7 Appendix 7 Appendix 8 Appendix 8 Recommendations Duration Regional Allocation Spread Product Tactical Trades Yields & Returns Global Bond Yields Historical Returns

GAA DM Equity Country Allocation Model Update The GAA DM Equity Country Allocation model is updated as of September 29th, 2017. The model sharply reduced its allocation to the U.K. to a bare minimum in response to the tightening in liquidity condition as the Bank of England warned of a rate hike in "coming months." The funds are reallocated to the Spain and Germany. Other smaller changes are the reductions in Italy and Australia in favor of Sweden and Switzerland, as shown in Table 1. As shown in Table 2 and Charts 1, 2 and 3, the overall model outperformed its benchmark by 44 bps in September. Both level 1 and level 2 models performed well, with level 2 outperforming its benchmark by 63 bps and level 1 outperforming its benchmark by 9 bps, as the underweight in Australia, U.S. and Japan versus the overweight in Italy, Germany and Netherland worked very well. Since going live in January 2016, the overall model has outperformed the benchmark by 341 bps, largely from the allocation among the 11 non-U.S. countries, which has outperformed its benchmark by 743 bps. Chart 1GAA DM Model Vs. MSCI World GAA DM Model Vs. MSCI World GAA DM Model Vs. MSCI World Chart 2GAA U.S. Vs. Non U.S. Model (Level1) GAA U.S. Vs. Non U.S. Model (Level1) GAA U.S. Vs. Non U.S. Model (Level1) Chart 3GAA Non U.S. Model (Level 2) GAA Non U.S. Model (Level 2) GAA Non U.S. Model (Level 2) Table 1Model Allocation Vs. Benchmark Weights GAA Quant Model Updates GAA Quant Model Updates Table 2Performance (Total Returns In USD) GAA Quant Model Updates GAA Quant Model Updates Please see also on the website http://gaa.bcaresearch.com/trades/allocation_performance. For more details on the models, please see the January 29th, 2016 Special Report, "Global Equity Allocation: Introducing the Developed Markets Country Allocation Model." http://gaa.bcaresearch.com/articles/view_report/18850. Please note that the overall country and sector recommendations published in our Monthly Portfolio Update and Quarterly Portfolio Outlook use the results of these quantitative models as one input, but do not stick slavishly to them. We believe that models are a useful check, but structural changes and unquantifiable factors need to be considered too in making overall recommendations. GAA Equity Sector Selection Model The GAA Equity Sector Selection Model (Chart 4) is updated as of September 30, 2017. Chart 4Overall Model Performance Overall Model Performance Overall Model Performance Table 3Allocations GAA Quant Model Updates GAA Quant Model Updates Table 4Performance Since Going Live GAA Quant Model Updates GAA Quant Model Updates The model continues to be optimistic on global growth as seen by an increasing allocation to cyclical sectors. Additionally, the model has also reduced its underweight on consumer discretionary stocks, which is currently the only cyclical sector to have a below-benchmark allocation. Finally, the biggest shift was a downgrade in utilities from overweight to underweight. This was primarily driven by momentum. For more details on the model, please see the Special Report "Introducing The GAA Equity Sector Selection Model," July 27, 2016 available at https://gaa.bcaresearch.com. Xiaoli Tang, Associate Vice President xiaoli@bcaresearch.com Aditya Kurian, Research Analyst adityak@bcaresearch.com

Highlights In this report, we analyze both static and dynamic hedging strategies to hedge an identical global equity portfolio to six home currencies: the U.S. dollar, the British pound, the euro, the Japanese yen, the Canadian dollar and the Australian dollar. We propose an easy to implement dynamic hedging framework based on the proprietary currency indicators from BCA's Foreign Exchange Strategy (FES) service. It has outperformed all the static hedging strategies since 2001 on a risk-adjusted return basis. In addition, it levels out the playing field for all investors as the hedged returns are quite similar, no matter what their home currencies are. Among the static hedging strategies, the "least-regret" hedge ratio of 50% has lived up to its reputation, as it has reduced risk by more than 50% without severely jeopardizing returns. Over a four-year moving performance cycle (in line with how most portfolio managers are evaluated), the proposed dynamic hedging adds little career risk to portfolio managers compared to the "least regret" 50% static hedging, while provides superior returns most of the time. A global equity portfolio's currency exposure should be managed in a centralized currency overlay under the supervision of the Chief Investment Officer, so that equity and currency managers can both fully utilize their expertise in their respective field, and the organization can manage currency risk more efficiently at the total portfolio level. Feature Dynamic Hedging Outperforms Static Hedging We have received many client requests asking about currency hedging in global equity portfolios with different home currencies. This is not surprising given how currency movements have overwhelmed global equity portfolio returns of late. For example, this year the U.S. dollar's weakness against the major currencies has beefed up returns for U.S. investors who did not hedge their foreign exposure (Table I-1). Table I-1Year-To-Date Currency Movements Have Overwhelmed Equity Returns Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors GAA's equity country allocation recommendations are by default unhedged on USD basis. When a hedge is required we make the recommendation explicit. There have been many conflicting views on whether global equity investors should hedge foreign currency exposure, and if so, what proportion of the exposure should be hedged. Perold and Schulman (1988) suggest fully hedging foreign currency exposure, because significant risk reduction can be achieved without a significant loss of return.1 This is based on their famous "free lunch" claim that average currency returns are zero over the long-term. At the other extreme, Froot (1993) suggests that foreign currencies should not be hedged at all for long-term investors, because purchasing power parity holds in the long term and exchange rates are mean reverting.2 There are many other views in between, including the universal hedge ratio proposed by Black (1989), which is estimated to be 77%.3 Campbell et al (2010) classify currencies into reserve currencies (USD, EUR and CHF), commodity currencies (AUD and CAD) and neutral currencies (JPY and GBP), and suggest that risk-minimizing investors should hold reserve currencies while hedging out commodity currencies, based on the correlations between the currencies and equity markets.4 Realizing the limitations of "static hedging," which assumes constant correlation, mean and variance, many academic researchers have explored "dynamic hedging models" that allow the mean and covariance to be time-varying by using complex econometric modelling techniques.5,6,7 These academic dynamic hedging strategies have shown improvement over the 50% static hedge, but it's very difficult for investors without a strong quantitative background to understand these very complex approaches. In fact, with all these confusing academic recommendations floating around, the "least regret" hedge ratio of 50% has been quite popular among practitioners.8 To help our clients better understand the role of currency management in global equity portfolios, we have joined forces with BCA's Foreign Exchange Strategy (FES) service to de-mystify the currency hedging process, and to propose a simple framework for clients with six different home currencies to dynamically hedge their foreign currency exposure based on the FES team's proprietary Intermediate-Term Timing Model (ITTM) indicators.9 These indicators have been used in their regular weekly publications. The ITTM-based dynamic hedging strategy is back-tested from 2001 because the ITTM indicators only date back to 2001 (See methodology). We have also back-tested a simple trend-following momentum-based dynamic strategy to see how a dynamic hedging methodology works in a longer period from 1976. For comparison we have back-tested ten different static hedging strategies that employ fixed hedge ratios across currencies and time. The test results not only clarify much of the confusion about static hedging, they also demonstrate that on a risk-adjusted return basis, BCA's ITTM-based dynamic hedging strategy has outperformed all static hedging strategies for all investors with six different home currencies since 2001 (Chart I-1). Even in the very long run of 41 years from August 1976, the simple momentum-based dynamic hedging outperforms the static strategies for investors with five home currencies, with only the AUD portfolio being worse off (Chart I-2). Chart I-1Identical Investment, But Different Risk/Return Profiles (3/2001-8/2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Chart I-2Identical Investment, But Different Risk/Return Profiles (8/1976-8/2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Now let's clarify some of the confusion: Does static hedging reduce portfolio risk at little expense of lowering returns? The answer is yes only for USD and JPY portfolios. For both the 41-year period from 1976 and the shorter 16-year period from 2001, a higher hedge ratio results in lower risk with slightly lower return. So fully hedged would be the "optimal" strategy for risk-minimizing investors with USD and JPY as home currencies (Panel 1 and 2 on left side in both Chart I-1 and Chart I-2). For the U.K. portfolio, the answer is a partial yes, because the "optimal hedge ratio" for risk-minizing investors, around 60%-80%, does produce the lowest risk, but the paths to that "optimal" point are totally opposite when different time periods are chosen. In the short period (Chart I-1, bottom left panel), it follows the same pattern as that for U.S. and Japanese investors up to the optimal point. As the hedge ratio increases, however, return drops and risk increases! In the longer period from 1976, as the hedge ratio increases, return increases and risk decreases until the "optimal point," after which risk and returns both increase (Chart I-2, bottom left panel). In the period from 2001, the AUD, CAD and EUR portfolios share a similar pattern to that of the GBP portfolio in the period from 1976. The AUD portfolio behaved the same in both the shorter period (Chart I-1, top right) and the longer period (Chart 2, top right), while the EUR and CAD portfolios behaved differently in the longer-term period from the shorter period. Overall, the CAD portfolio's "optimal" hedge ratio is around 0-30%, the AUD portfolio around 30-60% while the EUR portfolio is around 40% in the shorter period but around 90% in the longer period (Chart I-1 and Chart I-2). It is also worth noting that even though both the CAD and AUD are commodity currencies, AUD investors benefit significantly from hedging, while CAD investors' risk/return profile does not change much. This is because 1) currency returns for AUD investors do not average to zero in the long term due to positive carry, and 2) correlations between foreign currencies, foreign equities and domestic equities are not constant over time or across currencies (Appendix 2, Chart II-1 and Chart II-4) How does the "least regret" 50% static hedge do? The 50% hedge ratio fares quite well compared to the "optimal" static hedge ratio in terms of risk reduction for all portfolios in both periods, because more than half of the total risk reduction (the highest minus the lowest) occurs around the 50% hedge (Chart I-1 and Chart I-2). How does BCA's ITTM-based dynamic hedge do in terms of risk reduction? The ITTM produces better risk-adjusted returns for each portfolio than all the static hedges. In terms of risk, it generates the lowest risk for the EUR and GBP portfolios and is comparable to the 50% static hedge for other portfolios, while it generates a much higher return than all static hedges (Chart I-1 and Chart I-2). How does the BCA Dynamic Hedge (ITTM) compare to the 50% static hedge over time? Chart I-3 shows that the dynamic hedge consistently outperformed the 50% static hedge for all six home currencies since 2001 without significantly increasing hedging transactions, compared to the fixed 50% hedge ratio for all currency pairs. The dash line in each panel of Chart I-3 corresponds to the market cap-weighted aggregate of hedge ratios of foreign currencies for each home currency. On average, they are comparable to 50%. Most portfolio managers are measured on a moving four-year performance cycle. Chart I-4 shows that the ITTM-based dynamic hedging strategy has outperformed the 50% static hedging most of the time on a moving four-year basis, with only CAD, USD and JPY managers suffering brief drawdowns. Chart I-3BCA Dynamic Hedging Adds ##br##Value For All Investors BCA Dynamic Hedging Adds Value For All Investors BCA Dynamic Hedging Adds Value For All Investors Chart I-4Little Career Risk For ##br##Portfolio Managers Little Career Risk For Portfolio Managers Little Career Risk For Portfolio Managers In theory, if hedges were effective, then an identical global equity portfolio should have similar returns for all investors, no matter what home currency they hold. While neither the static hedging strategies nor the momentum-based dynamic hedging approach could pass this criteria, BCA's ITTM-based dynamic hedging approach does. It levels out the playing field for all investors globally. As shown in Chart I-5, in the period from March 2001 to August 2017, if left unhedged, the same global investment exhibits very different annualized returns for investors in different home currencies, with AUD investors at the low end at around 3.2%, and GBP investors at the high end at around 7%. With BCA's ITTM-based dynamic hedge, however, returns for all investors are very similar, no matter which currency is their home currency. Chart I-5BCA Dynamic Hedging Strategy Levels Out The Playing Field Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors The BCA Dynamic Hedging Methodology To back-test all the hedging strategies, we use an identical global equity portfolio that is a market cap-weighted aggregate of nine countries/regions based on MSCI U.S., Japan, the euro area, U.K., Canada, Australia, Switzerland, Sweden and Norway. This universe accounts for about 97% of the current MSCI World index (Chart I-6). The history of the euro area before 1987 (when MSCI data were available) is calculated as a market cap-weighted aggregate of MSCI Germany, France, Spain, Italy, Austria, Belgium and the Netherlands. Chart I-6GAA Global Equity Universe GAA Global Equity Universe GAA Global Equity Universe We evaluate the same global portfolio for investors with six different home currencies: USD, JPY, GBP, EUR, CAD and AUD. The Measurement for Hedging Efficacy: All the academically claimed "optimal" hedge ratios, static or dynamic, are based on risk-minimizing in a mean-variance optimization framework. For practitioners, however, "not meeting return objectives" is a much higher risk priority than minimizing portfolio risk. This is why we advocate risk-adjusted return as our measurement for hedge efficacy. The Objective: We aim to find the hedging strategies that outperform the widely used 50% static hedging strategy on a risk-adjusted return basis. At BCA, our philosophy has always been not to strive to find the optimal solution, but to try our best to find a feasible solution that best meets the stated objective. Interestingly, this approach has produced superior results for the GBP and EUR portfolios, achieving the combination of "highest return - lowest risk." It also levels out the playing field for all investors by generating similar hedged returns for all investors, no matter what home currency they hold (Chart I-1 and Chart I-5). The Proprietary Currency Indicators: The indicators from Foreign Exchange Strategy service's Intermediate Term Timing Model (ITTM) are built under the assumptions that the uncovered interest rate parity (UIP) holds, and the fair value of a currency pair is a function of the real rate differential (using an average of two-year and 10-year real rates), Junk OAS (a proxy for global risk appetite), commodity prices and past-year trends (52-week moving average). When a currency pair deviates from its fair value to an extreme, then the likelihood for a trend reversal is high.9 The Simple Rule-Based Dynamic Hedging: For each home currency, we evaluate the other eight foreign currencies individually based on each pair's ITTM indicator. When a foreign currency overshoots fair value above the upper band of its historical range, then the currency is a short, and the short position is kept until the foreign currency value touches the lower band of its historical range that's below the fair value. The Implementation: We use one-month forward contracts and re-balance on a monthly basis. The gain or loss of the underlying equity index during the month is not hedged, but converted back to the home currency at the month-end spot rate. For history before 2001, we use one-month interest rates to calculate hedged returns (Please see Appendix 1 hedged return calculations using forwards and also interest rates). Example: Chart I-7 illustrates how a Canadian investor uses the ITTM indicator to decide when to hedge JPY exposure when they invest in the MSCI Japan equity index. Chart I-7Canadian Investor: Japanese Index Dynamically Hedged Canadian Investor: Japanese Index Dynamically Hedged Canadian Investor: Japanese Index Dynamically Hedged The top panel shows the hedging signal for JPY (solid line) versus our proprietary ITTM indicator for JPY/CAD exchange rate (dash line). The upper and lower band are set as 7% above fair value and 9% below fair value; the bottom panel shows the relative performance of the MSCI Japan hedged in CAD versus the MSCI Japan unhedged in CAD. Currently CAD investors should hedge their JPY exposure based on the ITTM indicator. Some Suggestions For Asset Allocators Use a centralized currency overlay portfolio to manage foreign currency exposure. The overlay portfolio should be managed by currency specialists (either in-house or using external managers) under the supervision of the CIO. The objective of the overlay portfolio is to manage currency exposure based on the underlying assets of the organization's Total Portfolio, such that the risk/return profile of the total portfolio is improved against its benchmark. Global equity portfolio manager performance should be measured on an unhedged basis in their respective home currency. Some have argued that a fully hedged benchmark such as the MSCI All Country Total Return Index in local currencies should be used to measure the performance of a global equity portfolio manager. We strongly disagree, even though in theory it does not really matter what benchmark is used. MSCI's "total return indexes in local currencies" for global equity aggregates are theoretical in nature. They cannot be replicated in the real world because they are calculated on a daily basis using the previous closing day's exchange rate to calculate foreign equity return10 - such that the "local return" for each foreign equity index is perfectly hedged. Unfortunately this "perfect hedge" is humanly impossible, because as shown in Formula (1) in Appendix 1, only when both the spot rate and forward rate at the time t are equal to the spot rate at time t+1, can the local returns be fully captured! Xiaoli Tang, Associate Vice President xiaolit@bcaresearch.com 1 Perold, A and E. Schulman, 1988, "The free lunch in currency hedging: Implications for investment policy and performance standards", Financial Analyst Journal 44, 45-50. 2 Froot K., 1993, "Currency hedging over long horizons", NBER working paper 4355 3 Black, F., 1989, "Universal hedging: optimizing currency risk and reward in international equity portfolios", Financial Analyst Journal 45, 16-22 4 Campbell, J., K. de Medeiros and L. Viceira, 2010, "Global currency hedging", Journal of Finance LXV, 87-122 5 Gagnon, L., T., McCurdy, and G., Lypny, 1998, " Hedging foreign currency portfolios", Journal of Empirical Finance 5, 197-220 6 Hautsch, N., and J. Inkmann, 2003, "Optimal hedging of the currency exchange risk exposure of dynamically balanced strategic asset allocations", Journal of Asset Management 4, 173-189 7 Brown, C., J., Dark, and W., Zhang, "Dynamic currency hedging for international stock portfolios", 2012, Ph.D. dissertation, University of Melbourn 8 Michenaud, S., and B., Solnik, 2008, "Applying regret theory to investment choices: Currency hedging decisions", Journal of International Money and Finance 27, 677-694 9 Please see BCA Foreign Exchange Strategy Special Report titled "In Search Of A Timing Model", June 22, 2016 available at fes.bcaresearch.com 10 "Note on index calculation in local currency", MSCI Bara Index Calculation Methodologies, p19, May 2010 11 MSCI uses 2 business days as described in "MSCI Index Methodology: MSCI Hedged Indexes", July 2013 Appendix 1 We use one-month forward contracts and re-balance on a monthly basis. The gain or loss of the underlying equity index during the month is not hedged, but converted back to the home currency at the month-end spot rate. Before reliable forward contract rates were available (Jan 2001), we use one-month interest rates instead to calculate hedged returns. Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Please note that for simplification we have ignored the bid-ask spread in all the quotations, and we do not take into account the time lag required to implement a hedge.11 In practice, however, these are valid considerations. Appendix 2: Dynamics Hedging For Six Home Currencies 2.1 The Australian Perspective Correlations: For Aussie investors, foreign currencies in aggregate have a negative correlation with the domestic equity index (especially in the period from 2001), and a mostly positive but low correlation to the unhedged foreign equities. (Chart II-1). So hedging away foreign currency exposure would increase total risk of the global portfolio. This is why a fully hedged portfolio has the highest risk (Chart II-2, Table II-1). Historical Performance: Since 2001, ITTM-based dynamic hedging has produced the highest risk-adjusted return for the global portfolio in AUD. The return profile looks similar to the fully hedged portfolio, but risk is much lower (Table II-1). Over the longer period, the optimal static hedge ratio is about 70%, which is actually quite close to the 50% hedge, as shown in Table II-2. On a five-year rolling basis, as shown in Chart II-2, the ITTM-based dynamic risk/return profile also prevails. Current State: Currently AUD investors should only be hedging their exposure in Swiss francs and U.S. dollars, the two "safe haven" currencies. Actually, our indicators show a close to 100% hedge of the Swiss franc, as shown in Chart II-3, which did hurt the risk/return profile during the GFC period despite an outstanding full-period performance. Table II-1Risk/Return Profile For Global Equity In AUD (2001-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Table II-2Risk/Return Profile For Global Equity In AUD (1976-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Chart II-1Australian Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Australian Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Australian Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Chart II-2Australian Perespective: Dynamic Vs. Static Hedging Australian Perespective: Dynamic Vs. Static Hedging Australian Perespective: Dynamic Vs. Static Hedging Chart II-3Australian Perspective: Swiss Index Dynamically Hedged Australian Perspective: Swiss Index Dynamically Hedged Australian Perspective: Swiss Index Dynamically Hedged 2.2 The Canadian Perspective Correlations: For Canadian investors, foreign currencies on aggregate have a negative correlation with the country's domestic equity index, but the correlation with unhedged foreign equities has oscillated in both positive and negative territory. The correlation between Canadian equities and unhedged foreign equities has been always positive, in the range of 0.4-0.8 (Chart II-4). So hedging away foreign currency exposure will increase total risk within a global portfolio. This is why a fully hedged portfolio has the highest risk (Chart II-5, Table II-3 and Table II-4). Historical Performance: Since 2001, the ITTM-based dynamic hedging has produced the highest annualized return for the global portfolio in CAD without significantly increasing volatility from the unhedged scenario. In terms of risk-adjusted return, dynamic hedging has outperformed the best static hedging scenario (40% hedged) by about 46% (Table II-3). On a five-year rolling basis, as shown in Chart II-5, the dynamic risk/return profile also prevails. Current State: Currently Canadian investors should be hedging all foreign currencies except for the Australian dollar. Chart II-6 shows how CAD investors dynamically hedge their exposure to the Swedish krona. Table II-3Risk/Return Profile For Global Equity In CAD (2001-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Table II-4Risk/Return Profile For Global Equity In CAD (1976-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Chart II-4Canadian Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Canadian Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Canadian Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Chart II-5Canadian Perspective: Dynamic Vs. Static Hedging Canadian Perspective: Dynamic Vs. Static Hedging Canadian Perspective: Dynamic Vs. Static Hedging Chart II-6Canadian Perspective: Swedish Index Dynamically Hedged Canadian Perspective: Swedish Index Dynamically Hedged Canadian Perspective: Swedish Index Dynamically Hedged 2.3 The Japanese Perspective Correlations: For Japanese investors, correlations among foreign currencies, foreign equities and domestic equities seem to have gone through regime changes since the GFC, as shown in Chart II-7. These regime changes in correlations explain the evolving risk/return profile of the static hedges in Chart II-8. Before the GFC, full hedge and 50% hedge had similar risk profiles, but after the GFC full hedge reduced total risk significantly due to the sharp increase in correlations. Historical Performance: Since 2001, the ITTM-based dynamic hedging has produced the highest risk-adjusted return for the global portfolio in JPY, with a much higher return and slightly higher risk (Table II-5). Fully hedged has the lowest risk in both periods, and 50% is close to the "optimal" static hedge in both periods as well (Table II-5 and II-6). On a five-year rolling basis, as shown in Chart II-8, the ITTM-based dynamic risk/return profile. The 50% static hedge has similar risk profile to the ITTM-based dynamic hedge, but with lower returns. Current State: Currently JPY investors should be only hedging their exposure in Swiss francs and U.S. dollars. Chart II-9 shows how Japanese investors should have hedged CAD exposure. Table II-5Risk/Return Profile For Global Equity In JPY (2001-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Table II-6Risk/Return Profile For Global Equity In JPY (1976-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Chart II-7Japanese Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Japanese Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Japanese Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Chart II-8Japanese Perspective: Dynamic Vs. Static Hedging Japanese Perspective: Dynamic Vs. Static Hedging Japanese Perspective: Dynamic Vs. Static Hedging Chart II-9Japanese Perspective: Canadian Index Dynamically Hedged Japanese Perspective: Canadian Index Dynamically Hedged Japanese Perspective: Canadian Index Dynamically Hedged 2.4 The U.S. Perspective Correlations: For U.S. investors, correlations among foreign currencies, foreign equities and domestic equities seem to have gone through regime changes since the GFC, as shown in Chart II-10. These regime changes in correlation explain the evolving risk/return profile of the static hedges in Chart II-11. Before the GFC, full hedge and 50% hedge had similar risk profiles, but after the GFC full hedge exhibited significantly reduced total risk due to the sharp increase in correlations. Historical Performance: Since 2001, the ITTM-based dynamic hedging has produced the highest risk-adjusted return for the global portfolio in USD, with a much higher return and slightly lower risk compared to the 50%, which is the best static hedge for the period (Table II-7). Fully hedged had the lowest risk in both periods, but the return profiles of the static hedges were very similar, supporting the widely held belief that in the long run currency returns are close to zero (Table II-7 and II-8). On a five-year rolling basis, as shown in Chart II-11, the dynamic risk/return profile is close to that of the 50%. Current State: Currently U.S. investors should only be hedging their exposure in euros (Chart II-12). Table II-7Risk/Return Profile For Global Equity In USD (2001-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Table II-8Risk/Return Profile For Global Equity In JPY (1976-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Chart II-10U.S. Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies U.S. Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies U.S. Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Chart II-11U.S. Perspective: Dynamic Vs. Static Hedging U.S. Perspective: Dynamic Vs. Static Hedging U.S. Perspective: Dynamic Vs. Static Hedging Chart II-12U.S. Perspective: EMU Index Dynamically Hedged U.S. Perspective: EMU Index Dynamically Hedged US INVESTOR: EMU INDEX DYNAMIC HEDGE U.S. Perspective: EMU Index Dynamically Hedged US INVESTOR: EMU INDEX DYNAMIC HEDGE 2.5 The Euro Perspective Correlations: For investors that call the euro home currency, the correlation and foreign equities has been positive. The correlation between foreign currencies and domestic equity index, however, has been changing signs over time, currently sitting at near zero! (Chart II-13). This explains the shape of the risk/return profile in Chart II-14 and Table II-9. Historical Performance: Since 2001, the ITTM-based dynamic hedging has produced the highest risk-adjusted return for the global portfolio in euros, which has a higher return and lower risk than the best static hedge of 80% (Table II-9). Over the longer period, the optimal hedge ratio is about 50% hedge, which is actually quite close to those between 40-70%, as shown in Table II-10. On a five-year rolling basis, as shown in Chart II-14, the dynamic risk/return profile definitely prevails. Current State: Currently euro investors should not be hedging any foreign exposure, based on our indicators. Chart II-15 shows how euro investors should have hedged JPY exposure over time since 2001. Table II-9Risk/Return Profile For Global Equity In Euro (2001-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Table II-10Risk/Return Profile For Global Equity In Euro (1976-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Chart II-13Domestic And Unhedged Foreign Equities Vs. Foreign Currencies CHART EMU2: DOMESTIC AND UNHEDGED FOREIGN EQUITIES VS. FOREIGN CURRENCIES EURO AREA Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies CHART EMU2: DOMESTIC AND UNHEDGED FOREIGN EQUITIES VS. FOREIGN CURRENCIES EURO AREA Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Chart II-14Euro Area Perspective: Dynamic Vs. Static Hedging Euro Area Perspective: Dynamic Vs. Static Hedging Euro Area Perspective: Dynamic Vs. Static Hedging Chart II-15Euro area Perspective: Japanese Index Dynamically Hedged Euro area Perspective: Japanese Index Dynamically Hedged Euro area Perspective: Japanese Index Dynamically Hedged 2.6 The British Perspective Correlations: For British investors, correlations between foreign currencies and domestic equities have gone through several regime changes over time in both positive and negative territory, as shown in Chart II-16. The positive correlation between foreign and domestic equities has also increased over time. This would definitely make static hedging worse off (Table II-11 and II-12). Historical Performance: Not surprisingly, since 2001, dynamic hedging has produced the highest risk-adjusted return for the global portfolio in pounds, which has a higher return and lower risk than the best static hedge of 20% (Table II-11). Over the longer period, the optimal hedge ratio is about 90% hedge, Table II-12. On a five-year rolling basis, as shown in Chart II-17, the dynamic risk/return profile prevails, as it shares similar risk as the 50% hedge but with a higher return. Current State: Currently the British investors should not be hedging CAD and Swedish krona, while all six other currencies should be hedged. Chart II-18 shows how U.K. investors should have hedged their AUD exposure over time since 2001. Table II-11Risk/Return Profile For Global Equity In GBP (2001-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Table II-12Risk/Return Profile For Global Equity In GBP (1976-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Chart II-16Domestic And Unhedged Foreign Equities Vs. Foreign Currencies CHART UK2: DOMESTIC AND UNHEDGED FOREIGN EQUITIES VS. FOREIGN CURRENCIES U.K. Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies CHART UK2: DOMESTIC AND UNHEDGED FOREIGN EQUITIES VS. FOREIGN CURRENCIES U.K. Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Chart II-17Dynamic Vs. Static Hedging CHART UK1: DYNAMIC VS. STATIC HEDGING U.K. Perspective: Dynamic Vs. Static Hedging CHART UK1: DYNAMIC VS. STATIC HEDGING U.K. Perspective: Dynamic Vs. Static Hedging Chart II-18U.K. Perspective: Australian Index Dynamically Hedged U.K. Perspective: Australian Index Dynamically Hedged UK INVESTOR: AU INDEX DYNAMIC HEDGE U.K. Perspective: Australian Index Dynamically Hedged UK INVESTOR: AU INDEX DYNAMIC HEDGE

Dear client, I am on the road this week, attending BCA's New York Conference and teaching the BCA Academy. In lieu of a regular report, we are sending you a Special Report, a cooperation with our Global Asset Allocation service. In this piece, my colleague Xiaoli Tang tests the benefits of various currency hedging strategies for global equity portfolios. In addition to traditional hedging rules, Xiaoli deploys the Intermediate-Term Timing Models developed by the Foreign Exchange Strategy team to build dynamic hedging strategies, which result in superior risk/reward profiles. I trust you will find this report interesting and informative. Best regards, Mathieu Savary Highlights In this report, we analyze both static and dynamic hedging strategies to hedge an identical global equity portfolio to six home currencies: the U.S. dollar, the British pound, the euro, the Japanese yen, the Canadian dollar and the Australian dollar. We propose an easy to implement dynamic hedging framework based on the proprietary currency indicators from BCA's Foreign Exchange Strategy (FES) service. It has outperformed all the static hedging strategies since 2001 on a risk-adjusted return basis. In addition, it levels out the playing field for all investors as the hedged returns are quite similar, no matter what their home currencies are. Among the static hedging strategies, the "least-regret" hedge ratio of 50% has lived up to its reputation, as it has reduced risk by more than 50% without severely jeopardizing returns. Over a four-year moving performance cycle (in line with how most portfolio managers are evaluated), the proposed dynamic hedging adds little career risk to portfolio managers compared to the "least regret" 50% static hedging, while provides superior returns most of the time. A global equity portfolio's currency exposure should be managed in a centralized currency overlay under the supervision of the Chief Investment Officer, so that equity and currency managers can both fully utilize their expertise in their respective field, and the organization can manage currency risk more efficiently at the total portfolio level. Feature Dynamic Hedging Outperforms Static Hedging We have received many client requests asking about currency hedging in global equity portfolios with different home currencies. This is not surprising given how currency movements have overwhelmed global equity portfolio returns of late. For example, this year the U.S. dollar's weakness against the major currencies has beefed up returns for U.S. investors who did not hedge their foreign exposure (Table I-1). Table I-1Year-To-Date Currency Movements Have Overwhelmed Equity Returns Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors GAA's equity country allocation recommendations are by default unhedged on USD basis. When a hedge is required we make the recommendation explicit. There have been many conflicting views on whether global equity investors should hedge foreign currency exposure, and if so, what proportion of the exposure should be hedged. Perold and Schulman (1988) suggest fully hedging foreign currency exposure, because significant risk reduction can be achieved without a significant loss of return.1 This is based on their famous "free lunch" claim that average currency returns are zero over the long-term. At the other extreme, Froot (1993) suggests that foreign currencies should not be hedged at all for long-term investors, because purchasing power parity holds in the long term and exchange rates are mean reverting.2 There are many other views in between, including the universal hedge ratio proposed by Black (1989), which is estimated to be 77%.3 Campbell et al (2010) classify currencies into reserve currencies (USD, EUR and CHF), commodity currencies (AUD and CAD) and neutral currencies (JPY and GBP), and suggest that risk-minimizing investors should hold reserve currencies while hedging out commodity currencies, based on the correlations between the currencies and equity markets.4 Realizing the limitations of "static hedging," which assumes constant correlation, mean and variance, many academic researchers have explored "dynamic hedging models" that allow the mean and covariance to be time-varying by using complex econometric modelling techniques.5,6,7 These academic dynamic hedging strategies have shown improvement over the 50% static hedge, but it's very difficult for investors without a strong quantitative background to understand these very complex approaches. In fact, with all these confusing academic recommendations floating around, the "least regret" hedge ratio of 50% has been quite popular among practitioners.8 To help our clients better understand the role of currency management in global equity portfolios, we have joined forces with BCA's Foreign Exchange Strategy (FES) service to de-mystify the currency hedging process, and to propose a simple framework for clients with six different home currencies to dynamically hedge their foreign currency exposure based on the FES team's proprietary Intermediate-Term Timing Model (ITTM) indicators.9 These indicators have been used in their regular weekly publications. The ITTM-based dynamic hedging strategy is back-tested from 2001 because the ITTM indicators only date back to 2001 (See methodology). We have also back-tested a simple trend-following momentum-based dynamic strategy to see how a dynamic hedging methodology works in a longer period from 1976. For comparison we have back-tested ten different static hedging strategies that employ fixed hedge ratios across currencies and time. The test results not only clarify much of the confusion about static hedging, they also demonstrate that on a risk-adjusted return basis, BCA's ITTM-based dynamic hedging strategy has outperformed all static hedging strategies for all investors with six different home currencies since 2001 (Chart I-1). Even in the very long run of 41 years from August 1976, the simple momentum-based dynamic hedging outperforms the static strategies for investors with five home currencies, with only the AUD portfolio being worse off (Chart I-2). Chart I-1Identical Investment, But Different Risk/Return Profiles (3/2001-8/2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Chart I-2Identical Investment, But Different Risk/Return Profiles (8/1976-8/2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Now let's clarify some of the confusion: Does static hedging reduce portfolio risk at little expense of lowering returns? The answer is yes only for USD and JPY portfolios. For both the 41-year period from 1976 and the shorter 16-year period from 2001, a higher hedge ratio results in lower risk with slightly lower return. So fully hedged would be the "optimal" strategy for risk-minimizing investors with USD and JPY as home currencies (Panel 1 and 2 on left side in both Chart I-1 and Chart I-2). For the U.K. portfolio, the answer is a partial yes, because the "optimal hedge ratio" for risk-minizing investors, around 60%-80%, does produce the lowest risk, but the paths to that "optimal" point are totally opposite when different time periods are chosen. In the short period (Chart I-1, bottom left panel), it follows the same pattern as that for U.S. and Japanese investors up to the optimal point. As the hedge ratio increases, however, return drops and risk increases! In the longer period from 1976, as the hedge ratio increases, return increases and risk decreases until the "optimal point," after which risk and returns both increase (Chart I-2, bottom left panel). In the period from 2001, the AUD, CAD and EUR portfolios share a similar pattern to that of the GBP portfolio in the period from 1976. The AUD portfolio behaved the same in both the shorter period (Chart I-1, top right) and the longer period (Chart 2, top right), while the EUR and CAD portfolios behaved differently in the longer-term period from the shorter period. Overall, the CAD portfolio's "optimal" hedge ratio is around 0-30%, the AUD portfolio around 30-60% while the EUR portfolio is around 40% in the shorter period but around 90% in the longer period (Chart I-1 and Chart I-2). It is also worth noting that even though both the CAD and AUD are commodity currencies, AUD investors benefit significantly from hedging, while CAD investors' risk/return profile does not change much. This is because 1) currency returns for AUD investors do not average to zero in the long term due to positive carry, and 2) correlations between foreign currencies, foreign equities and domestic equities are not constant over time or across currencies (Appendix 2, Chart II-1 and Chart II-4) How does the "least regret" 50% static hedge do? The 50% hedge ratio fares quite well compared to the "optimal" static hedge ratio in terms of risk reduction for all portfolios in both periods, because more than half of the total risk reduction (the highest minus the lowest) occurs around the 50% hedge (Chart I-1 and Chart I-2). How does BCA's ITTM-based dynamic hedge do in terms of risk reduction? The ITTM produces better risk-adjusted returns for each portfolio than all the static hedges. In terms of risk, it generates the lowest risk for the EUR and GBP portfolios and is comparable to the 50% static hedge for other portfolios, while it generates a much higher return than all static hedges (Chart I-1 and Chart I-2). How does the BCA Dynamic Hedge (ITTM) compare to the 50% static hedge over time? Chart I-3 shows that the dynamic hedge consistently outperformed the 50% static hedge for all six home currencies since 2001 without significantly increasing hedging transactions, compared to the fixed 50% hedge ratio for all currency pairs. The dash line in each panel of Chart I-3 corresponds to the market cap-weighted aggregate of hedge ratios of foreign currencies for each home currency. On average, they are comparable to 50%. Most portfolio managers are measured on a moving four-year performance cycle. Chart I-4 shows that the ITTM-based dynamic hedging strategy has outperformed the 50% static hedging most of the time on a moving four-year basis, with only CAD, USD and JPY managers suffering brief drawdowns. Chart I-3BCA Dynamic Hedging Adds ##br##Value For All Investors BCA Dynamic Hedging Adds Value For All Investors BCA Dynamic Hedging Adds Value For All Investors Chart I-4Little Career Risk For ##br##Portfolio Managers Little Career Risk For Portfolio Managers Little Career Risk For Portfolio Managers In theory, if hedges were effective, then an identical global equity portfolio should have similar returns for all investors, no matter what home currency they hold. While neither the static hedging strategies nor the momentum-based dynamic hedging approach could pass this criteria, BCA's ITTM-based dynamic hedging approach does. It levels out the playing field for all investors globally. As shown in Chart I-5, in the period from March 2001 to August 2017, if left unhedged, the same global investment exhibits very different annualized returns for investors in different home currencies, with AUD investors at the low end at around 3.2%, and GBP investors at the high end at around 7%. With BCA's ITTM-based dynamic hedge, however, returns for all investors are very similar, no matter which currency is their home currency. Chart I-5BCA Dynamic Hedging Strategy Levels Out The Playing Field Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors The BCA Dynamic Hedging Methodology To back-test all the hedging strategies, we use an identical global equity portfolio that is a market cap-weighted aggregate of nine countries/regions based on MSCI U.S., Japan, the euro area, U.K., Canada, Australia, Switzerland, Sweden and Norway. This universe accounts for about 97% of the current MSCI World index (Chart I-6). The history of the euro area before 1987 (when MSCI data were available) is calculated as a market cap-weighted aggregate of MSCI Germany, France, Spain, Italy, Austria, Belgium and the Netherlands. Chart I-6GAA Global Equity Universe GAA Global Equity Universe GAA Global Equity Universe We evaluate the same global portfolio for investors with six different home currencies: USD, JPY, GBP, EUR, CAD and AUD. The Measurement for Hedging Efficacy: All the academically claimed "optimal" hedge ratios, static or dynamic, are based on risk-minimizing in a mean-variance optimization framework. For practitioners, however, "not meeting return objectives" is a much higher risk priority than minimizing portfolio risk. This is why we advocate risk-adjusted return as our measurement for hedge efficacy. The Objective: We aim to find the hedging strategies that outperform the widely used 50% static hedging strategy on a risk-adjusted return basis. At BCA, our philosophy has always been not to strive to find the optimal solution, but to try our best to find a feasible solution that best meets the stated objective. Interestingly, this approach has produced superior results for the GBP and EUR portfolios, achieving the combination of "highest return - lowest risk." It also levels out the playing field for all investors by generating similar hedged returns for all investors, no matter what home currency they hold (Chart I-1 and Chart I-5). The Proprietary Currency Indicators: The indicators from Foreign Exchange Strategy service's Intermediate Term Timing Model (ITTM) are built under the assumptions that the uncovered interest rate parity (UIP) holds, and the fair value of a currency pair is a function of the real rate differential (using an average of two-year and 10-year real rates), Junk OAS (a proxy for global risk appetite), commodity prices and past-year trends (52-week moving average). When a currency pair deviates from its fair value to an extreme, then the likelihood for a trend reversal is high.9 The Simple Rule-Based Dynamic Hedging: For each home currency, we evaluate the other eight foreign currencies individually based on each pair's ITTM indicator. When a foreign currency overshoots fair value above the upper band of its historical range, then the currency is a short, and the short position is kept until the foreign currency value touches the lower band of its historical range that's below the fair value. The Implementation: We use one-month forward contracts and re-balance on a monthly basis. The gain or loss of the underlying equity index during the month is not hedged, but converted back to the home currency at the month-end spot rate. For history before 2001, we use one-month interest rates to calculate hedged returns (Please see Appendix 1 hedged return calculations using forwards and also interest rates). Example: Chart I-7 illustrates how a Canadian investor uses the ITTM indicator to decide when to hedge JPY exposure when they invest in the MSCI Japan equity index. Chart I-7Canadian Investor: Japanese Index Dynamically Hedged Canadian Investor: Japanese Index Dynamically Hedged Canadian Investor: Japanese Index Dynamically Hedged The top panel shows the hedging signal for JPY (solid line) versus our proprietary ITTM indicator for JPY/CAD exchange rate (dash line). The upper and lower band are set as 7% above fair value and 9% below fair value; the bottom panel shows the relative performance of the MSCI Japan hedged in CAD versus the MSCI Japan unhedged in CAD. Currently CAD investors should hedge their JPY exposure based on the ITTM indicator. Some Suggestions For Asset Allocators Use a centralized currency overlay portfolio to manage foreign currency exposure. The overlay portfolio should be managed by currency specialists (either in-house or using external managers) under the supervision of the CIO. The objective of the overlay portfolio is to manage currency exposure based on the underlying assets of the organization's Total Portfolio, such that the risk/return profile of the total portfolio is improved against its benchmark. Global equity portfolio manager performance should be measured on an unhedged basis in their respective home currency. Some have argued that a fully hedged benchmark such as the MSCI All Country Total Return Index in local currencies should be used to measure the performance of a global equity portfolio manager. We strongly disagree, even though in theory it does not really matter what benchmark is used. MSCI's "total return indexes in local currencies" for global equity aggregates are theoretical in nature. They cannot be replicated in the real world because they are calculated on a daily basis using the previous closing day's exchange rate to calculate foreign equity return10 - such that the "local return" for each foreign equity index is perfectly hedged. Unfortunately this "perfect hedge" is humanly impossible, because as shown in Formula (1) in Appendix 1, only when both the spot rate and forward rate at the time t are equal to the spot rate at time t+1, can the local returns be fully captured! Xiaoli Tang, Associate Vice President xiaolit@bcaresearch.com 1 Perold, A and E. Schulman, 1988, "The free lunch in currency hedging: Implications for investment policy and performance standards", Financial Analyst Journal 44, 45-50. 2 Froot K., 1993, "Currency hedging over long horizons", NBER working paper 4355 3 Black, F., 1989, "Universal hedging: optimizing currency risk and reward in international equity portfolios", Financial Analyst Journal 45, 16-22 4 Campbell, J., K. de Medeiros and L. Viceira, 2010, "Global currency hedging", Journal of Finance LXV, 87-122 5 Gagnon, L., T., McCurdy, and G., Lypny, 1998, " Hedging foreign currency portfolios", Journal of Empirical Finance 5, 197-220 6 Hautsch, N., and J. Inkmann, 2003, "Optimal hedging of the currency exchange risk exposure of dynamically balanced strategic asset allocations", Journal of Asset Management 4, 173-189 7 Brown, C., J., Dark, and W., Zhang, "Dynamic currency hedging for international stock portfolios", 2012, Ph.D. dissertation, University of Melbourn 8 Michenaud, S., and B., Solnik, 2008, "Applying regret theory to investment choices: Currency hedging decisions", Journal of International Money and Finance 27, 677-694 9 Please see BCA Foreign Exchange Strategy Special Report titled "In Search Of A Timing Model", June 22, 2016 available at fes.bcaresearch.com 10 "Note on index calculation in local currency", MSCI Bara Index Calculation Methodologies, p19, May 2010 11 MSCI uses 2 business days as described in "MSCI Index Methodology: MSCI Hedged Indexes", July 2013 Appendix 1 We use one-month forward contracts and re-balance on a monthly basis. The gain or loss of the underlying equity index during the month is not hedged, but converted back to the home currency at the month-end spot rate. Before reliable forward contract rates were available (Jan 2001), we use one-month interest rates instead to calculate hedged returns. Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Please note that for simplification we have ignored the bid-ask spread in all the quotations, and we do not take into account the time lag required to implement a hedge.11 In practice, however, these are valid considerations. Appendix 2: Dynamics Hedging For Six Home Currencies 2.1 The Australian Perspective Correlations: For Aussie investors, foreign currencies in aggregate have a negative correlation with the domestic equity index (especially in the period from 2001), and a mostly positive but low correlation to the unhedged foreign equities. (Chart II-1). So hedging away foreign currency exposure would increase total risk of the global portfolio. This is why a fully hedged portfolio has the highest risk (Chart II-2, Table II-1). Historical Performance: Since 2001, ITTM-based dynamic hedging has produced the highest risk-adjusted return for the global portfolio in AUD. The return profile looks similar to the fully hedged portfolio, but risk is much lower (Table II-1). Over the longer period, the optimal static hedge ratio is about 70%, which is actually quite close to the 50% hedge, as shown in Table II-2. On a five-year rolling basis, as shown in Chart II-2, the ITTM-based dynamic risk/return profile also prevails. Current State: Currently AUD investors should only be hedging their exposure in Swiss francs and U.S. dollars, the two "safe haven" currencies. Actually, our indicators show a close to 100% hedge of the Swiss franc, as shown in Chart II-3, which did hurt the risk/return profile during the GFC period despite an outstanding full-period performance. Table II-1Risk/Return Profile For Global Equity In AUD (2001-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Table II-2Risk/Return Profile For Global Equity In AUD (1976-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Chart II-1Australian Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Australian Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Australian Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Chart II-2Australian Perespective: Dynamic Vs. Static Hedging Australian Perespective: Dynamic Vs. Static Hedging Australian Perespective: Dynamic Vs. Static Hedging Chart II-3Australian Perspective: Swiss Index Dynamically Hedged Australian Perspective: Swiss Index Dynamically Hedged Australian Perspective: Swiss Index Dynamically Hedged 2.2 The Canadian Perspective Correlations: For Canadian investors, foreign currencies on aggregate have a negative correlation with the country's domestic equity index, but the correlation with unhedged foreign equities has oscillated in both positive and negative territory. The correlation between Canadian equities and unhedged foreign equities has been always positive, in the range of 0.4-0.8 (Chart II-4). So hedging away foreign currency exposure will increase total risk within a global portfolio. This is why a fully hedged portfolio has the highest risk (Chart II-5, Table II-3 and Table II-4). Historical Performance: Since 2001, the ITTM-based dynamic hedging has produced the highest annualized return for the global portfolio in CAD without significantly increasing volatility from the unhedged scenario. In terms of risk-adjusted return, dynamic hedging has outperformed the best static hedging scenario (40% hedged) by about 46% (Table II-3). On a five-year rolling basis, as shown in Chart II-5, the dynamic risk/return profile also prevails. Current State: Currently Canadian investors should be hedging all foreign currencies except for the Australian dollar. Chart II-6 shows how CAD investors dynamically hedge their exposure to the Swedish krona. Table II-3Risk/Return Profile For Global Equity In CAD (2001-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Table II-4Risk/Return Profile For Global Equity In CAD (1976-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Chart II-4Canadian Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Canadian Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Canadian Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Chart II-5Canadian Perspective: Dynamic Vs. Static Hedging Canadian Perspective: Dynamic Vs. Static Hedging Canadian Perspective: Dynamic Vs. Static Hedging Chart II-6Canadian Perspective: Swedish Index Dynamically Hedged Canadian Perspective: Swedish Index Dynamically Hedged Canadian Perspective: Swedish Index Dynamically Hedged 2.3 The Japanese Perspective Correlations: For Japanese investors, correlations among foreign currencies, foreign equities and domestic equities seem to have gone through regime changes since the GFC, as shown in Chart II-7. These regime changes in correlations explain the evolving risk/return profile of the static hedges in Chart II-8. Before the GFC, full hedge and 50% hedge had similar risk profiles, but after the GFC full hedge reduced total risk significantly due to the sharp increase in correlations. Historical Performance: Since 2001, the ITTM-based dynamic hedging has produced the highest risk-adjusted return for the global portfolio in JPY, with a much higher return and slightly higher risk (Table II-5). Fully hedged has the lowest risk in both periods, and 50% is close to the "optimal" static hedge in both periods as well (Table II-5 and II-6). On a five-year rolling basis, as shown in Chart II-8, the ITTM-based dynamic risk/return profile. The 50% static hedge has similar risk profile to the ITTM-based dynamic hedge, but with lower returns. Current State: Currently JPY investors should be only hedging their exposure in Swiss francs and U.S. dollars. Chart II-9 shows how Japanese investors should have hedged CAD exposure. Table II-5Risk/Return Profile For Global Equity In JPY (2001-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Table II-6Risk/Return Profile For Global Equity In JPY (1976-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Chart II-7Japanese Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Japanese Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Japanese Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Chart II-8Japanese Perspective: Dynamic Vs. Static Hedging Japanese Perspective: Dynamic Vs. Static Hedging Japanese Perspective: Dynamic Vs. Static Hedging Chart II-9Japanese Perspective: Canadian Index Dynamically Hedged Japanese Perspective: Canadian Index Dynamically Hedged Japanese Perspective: Canadian Index Dynamically Hedged 2.4 The U.S. Perspective Correlations: For U.S. investors, correlations among foreign currencies, foreign equities and domestic equities seem to have gone through regime changes since the GFC, as shown in Chart II-10. These regime changes in correlation explain the evolving risk/return profile of the static hedges in Chart II-11. Before the GFC, full hedge and 50% hedge had similar risk profiles, but after the GFC full hedge exhibited significantly reduced total risk due to the sharp increase in correlations. Historical Performance: Since 2001, the ITTM-based dynamic hedging has produced the highest risk-adjusted return for the global portfolio in USD, with a much higher return and slightly lower risk compared to the 50%, which is the best static hedge for the period (Table II-7). Fully hedged had the lowest risk in both periods, but the return profiles of the static hedges were very similar, supporting the widely held belief that in the long run currency returns are close to zero (Table II-7 and II-8). On a five-year rolling basis, as shown in Chart II-11, the dynamic risk/return profile is close to that of the 50%. Current State: Currently U.S. investors should only be hedging their exposure in euros (Chart II-12). Table II-7Risk/Return Profile For Global Equity In USD (2001-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Table II-8Risk/Return Profile For Global Equity In JPY (1976-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Chart II-10U.S. Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies U.S. Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies U.S. Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Chart II-11U.S. Perspective: Dynamic Vs. Static Hedging U.S. Perspective: Dynamic Vs. Static Hedging U.S. Perspective: Dynamic Vs. Static Hedging Chart II-12U.S. Perspective: EMU Index Dynamically Hedged U.S. Perspective: EMU Index Dynamically Hedged US INVESTOR: EMU INDEX DYNAMIC HEDGE U.S. Perspective: EMU Index Dynamically Hedged US INVESTOR: EMU INDEX DYNAMIC HEDGE 2.5 The Euro Perspective Correlations: For investors that call the euro home currency, the correlation and foreign equities has been positive. The correlation between foreign currencies and domestic equity index, however, has been changing signs over time, currently sitting at near zero! (Chart II-13). This explains the shape of the risk/return profile in Chart II-14 and Table II-9. Historical Performance: Since 2001, the ITTM-based dynamic hedging has produced the highest risk-adjusted return for the global portfolio in euros, which has a higher return and lower risk than the best static hedge of 80% (Table II-9). Over the longer period, the optimal hedge ratio is about 50% hedge, which is actually quite close to those between 40-70%, as shown in Table II-10. On a five-year rolling basis, as shown in Chart II-14, the dynamic risk/return profile definitely prevails. Current State: Currently euro investors should not be hedging any foreign exposure, based on our indicators. Chart II-15 shows how euro investors should have hedged JPY exposure over time since 2001. Table II-9Risk/Return Profile For Global Equity In Euro (2001-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Table II-10Risk/Return Profile For Global Equity In Euro (1976-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Chart II-13Domestic And Unhedged Foreign Equities Vs. Foreign Currencies CHART EMU2: DOMESTIC AND UNHEDGED FOREIGN EQUITIES VS. FOREIGN CURRENCIES EURO AREA Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies CHART EMU2: DOMESTIC AND UNHEDGED FOREIGN EQUITIES VS. FOREIGN CURRENCIES EURO AREA Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Chart II-14Euro Area Perspective: Dynamic Vs. Static Hedging Euro Area Perspective: Dynamic Vs. Static Hedging Euro Area Perspective: Dynamic Vs. Static Hedging Chart II-15Euro area Perspective: Japanese Index Dynamically Hedged Euro area Perspective: Japanese Index Dynamically Hedged Euro area Perspective: Japanese Index Dynamically Hedged 2.6 The British Perspective Correlations: For British investors, correlations between foreign currencies and domestic equities have gone through several regime changes over time in both positive and negative territory, as shown in Chart II-16. The positive correlation between foreign and domestic equities has also increased over time. This would definitely make static hedging worse off (Table II-11 and II-12). Historical Performance: Not surprisingly, since 2001, dynamic hedging has produced the highest risk-adjusted return for the global portfolio in pounds, which has a higher return and lower risk than the best static hedge of 20% (Table II-11). Over the longer period, the optimal hedge ratio is about 90% hedge, Table II-12. On a five-year rolling basis, as shown in Chart II-17, the dynamic risk/return profile prevails, as it shares similar risk as the 50% hedge but with a higher return. Current State: Currently the British investors should not be hedging CAD and Swedish krona, while all six other currencies should be hedged. Chart II-18 shows how U.K. investors should have hedged their AUD exposure over time since 2001. Table II-11Risk/Return Profile For Global Equity In GBP (2001-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Table II-12Risk/Return Profile For Global Equity In GBP (1976-2017) Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Currency Hedging: Dynamic Or Static? - A Practical Guide For Global Equity Investors Chart II-16Domestic And Unhedged Foreign Equities Vs. Foreign Currencies CHART UK2: DOMESTIC AND UNHEDGED FOREIGN EQUITIES VS. FOREIGN CURRENCIES U.K. Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies CHART UK2: DOMESTIC AND UNHEDGED FOREIGN EQUITIES VS. FOREIGN CURRENCIES U.K. Perspective: Domestic And Unhedged Foreign Equities Vs. Foreign Currencies Chart II-17Dynamic Vs. Static Hedging CHART UK1: DYNAMIC VS. STATIC HEDGING U.K. Perspective: Dynamic Vs. Static Hedging CHART UK1: DYNAMIC VS. STATIC HEDGING U.K. Perspective: Dynamic Vs. Static Hedging Chart II-18U.K. Perspective: Australian Index Dynamically Hedged U.K. Perspective: Australian Index Dynamically Hedged UK INVESTOR: AU INDEX DYNAMIC HEDGE U.K. Perspective: Australian Index Dynamically Hedged UK INVESTOR: AU INDEX DYNAMIC HEDGE Trades & Forecasts Forecast Summary Core Portfolio Closed Trades

Liquidity is the lifeblood of the economy and financial markets, but it is a slippery concept that means different things to different people. Liquidity falls into four categories: monetary, balance sheet, financial market transaction liquidity, and funding liquidity. Overall liquidity conditions are reasonably constructive for risk assets at the moment. Financial market and balance sheet liquidity are adequate. Monetary policy is extremely easy, although the low level of money and credit growth underscores that the credit channel of monetary policy is still somewhat impaired. Funding liquidity is as important as monetary liquidity for financial markets. It has recovered from the Great Financial Crisis (GFC) lows, but it is far from frothy. Unwinding the Fed's balance sheet represents a risk to investors because QE played such an important role in reducing risk premia in financial markets. The unwind should not affect transactions liquidity or balance sheet liquidity. It should not affect the broad monetary aggregates either. The bond market's reaction will be far more important than balance sheet shrinkage. As long as the Fed can limit the bond market damage via forward guidance, then funding liquidity should remain adequate and risk assets should take the Fed's unwind in stride. It will be a whole different story, however, if inflation lurches higher. The technical impact of balance sheet unwind on the inner workings of the credit market is very complicated. Asset sales could lead to a shortage of short-term high-quality assets, unless it is offset with increased T-bill issuance. However, a smaller balance sheet could, in fact, improve funding liquidity to the extent that it frees up space on banks' balance sheets. Liquidity has been an integral part of BCA's approach to financial markets going back to the early days of the company under the tutelage of Editor-in-Chief Hamilton Bolton from 1949 to 1968. Bolton was ahead of his time in terms of developing monetary indicators to forecast market trends. Back then, the focus was on bank flows such as the volume of checks cashed because capital markets were still developing and most credit flowed through the banking system. Times changed, monetary policy implementation evolved and financial markets became more important and sophisticated. When money targeting became popular among central banks in the 1970s, central bank liquidity analysis focused more on the broader monetary aggregates. These and other monetary data were used extensively by Anthony Boeckh, BCA's Editor-in-Chief from the 1968 to 2002, to forecast the economy and markets. He also highlighted the importance of balance sheet liquidity (holdings of liquid assets), and its interplay with rising debt levels. Martin Barnes continued with these themes when writing about the Debt Supercycle in the monthly Bank Credit Analyst. "Liquidity" is a slippery concept, and it means different things to different people. In this Special Report, we describe BCA's approach to liquidity and highlight its critical importance for financial markets. We provide a list of indicators to watch, and also outline how the pending shrinkage of the Fed's balance sheet could affect overall liquidity conditions. A Primer On Liquidity We believe there are four types of liquidity that are all interrelated: Central Bank Liquidity: Bank reserves lie at the heart of central bank liquidity. Reserves are under the direct control of the central bank, which are used as a tool to influence general monetary conditions in the economy. The latter are endogenous to the system and also depend on the private sector's desire to borrow, spend and hold cash. Bullish liquidity conditions are typically associated with plentiful bank reserves, low interest rates and strong growth in the monetary aggregates. Balance Sheet Liquidity: A high level of balance sheet liquidity means that plenty of short-term assets are available to meet emergencies. The desire of households, companies and institutional investors to build up balance sheet liquidity would normally increase when times are bad, and decline when confidence is high. Thus, one would expect strong economic growth to be associated with declining balance sheet liquidity, and vice versa when the economy is weak. Of course, deteriorating balance sheet liquidity during good times is a negative sign to the extent that households or business are caught in an illiquid state when the economy turns down, jobs are lost and loans are called. Financial Market Transaction Liquidity: This refers to the ability to make transactions in securities without triggering major changes in prices. Financial institutions provide market liquidity to securities markets through their trading activities. Funding Liquidity: The ability to borrow to fund positions in financial markets. Financial institutions provide funding liquidity to borrowers through their lending activities. The conditions under which these intermediaries can fund their own balance sheets, in turn, depend on the willingness of banks and the shadow banking system to interact with them. The BIS definition of funding liquidity is a broad concept that captures a wide range of channels. It includes the capacity of intermediaries that participate in the securitization chain to access the necessary funding to originate loans, to acquire loans for packaging into securities, and finance various kinds of guarantees. The availability and turnover of collateral for loans is also very important for generating funding liquidity, as we discuss below. These types of liquidity are interrelated in various ways, and can positively or negatively reinforce each other. It is the interaction of these factors that determines the economy's overall ease of financing. See Box II-1 for more details. BOX II-1 How Liquidity Is Inter-Related Central bank liquidity, which is exogenously determined, is the basis for private liquidity creation (the combination of market transaction and funding liquidity). The central bank determines the short-term risk-free rate and the official liquidity that is provided to the banking system. If the central bank hikes rates or provides less official liquidity, appetite for private lending begins to dry up. Private sector liquidity is thus heavily influenced by monetary policy, but can develop a life of its own, overshooting to the upside and downside with swings in investor confidence and risk tolerance. Financial market liquidity and funding liquidity are closely interrelated. When times are good, markets are liquid and funding liquidity is ample. But when risk tolerance takes a hit, a vicious circle between market transaction and funding liquidity develops. The BIS highlights the procyclical nature of private liquidity, which means that it tends to exhibit boom-bust cycles that generate credit excesses that are followed by busts.1 The Great Financial Crisis of 2008 is a perfect example. The Fed lifted the fed funds rate by 400 basis points between 2004 and 2006. Nonetheless, the outsized contraction in private liquidity, resulting from the plunge in asset prices related to U.S. mortgage debt, was a key driver of the crash in risk asset prices. Liquidity Indicators: What To Watch (1) Monetary Liquidity Key measures of central bank liquidity include the monetary base and the broad money aggregates, such as M1 and M2 (Chart II-1). Central banks control the amount of reserves in the banking system, which is part of base money, but they do not control the broad monetary aggregates. The latter is determined by the desire to hold cash and bank deposits, as well as the demand and supply of credit. Box II-2 provides some background on the monetary transmission process and quantitative easing. BOX II-2 The Monetary Transmission Process And Qe Before the Great Recession and Financial Crisis, the monetary authorities set the level of short-term interest rates through active management of the level of bank reserves. Reserves were drained as policy tightened, and were boosted when policies eased. The level of bank reserves affected banks' lending behavior, and shifts in interest rates affected the spending and investment decisions of consumers and businesses. Of course, it has been a different story since the financial crisis. Once short-term interest rates reached the zero bound, the Fed and some other central banks adopted "quantitative easing" programs designed to depress longer-term interest rates by aggressively buying bonds and thereby stuffing the banking system with an excessive amount of reserves. Many feared the onset of inflation when QE programs were first announced because investors worried that this would contribute to a massive increase in credit and the overall money supply. Indeed, there could have been hyper-inflation if banks had gone on a lending spree. But this never happened. Banks were constrained by insufficient capital ratios, loan losses and intense regulation, while consumers and businesses had no appetite for acquiring more debt. The result was that the money multiplier - the ratio of broad money to the monetary base - collapsed (top panel in Chart II-1). Bank lending standards eventually eased and credit demand recovered. Broad money growth has been volatile since 2007 but, despite quantitative easing, it has been roughly in line with the decade before. The broad aggregates lost much of their predictive power after the 1980s. Financial innovation, such as the use of debit cards and bank machines, changed the relationship between broad money on one hand, and the economy or financial markets on the other. Despite the structural changes in the economy, investors should still keep the monetary aggregates and the other monetary indicators discussed below in their toolbox. While the year-to-year wiggles in M2, for example, have not been good predictors of growth or inflation on a one or two year horizon, Chart II-2 shows that there is a long-term relationship between money and inflation when using decade averages. Chart II-1The Monetary Aggregates The Monetary Aggregates The Monetary Aggregates Chart II-2Long-Run Relationship Between M2 And Inflation October 2017 October 2017 Other monetary indicators to watch: M2 Divided By Nominal GDP (Chart II-3): When money growth exceeds that of nominal GDP, it could be interpreted as a signal that there is more than enough liquidity to facilitate economic activity. The excess is then available to purchase financial assets. Monetary Conditions Index (Chart II-3): This combines the level of interest rates and the change in the exchange rate into one indicator. The MCI has increased over the past year, indicating a tightening of monetary conditions, but is still very low by historical standards. Dollar Based Liquidity (Chart II-3): This includes Fed holdings of Treasurys and U.S. government securities held in custody for foreign official accounts. Foreign Exchange Reserves (Chart II-3): Central banks hold reserves in the form of gold, or cash and bonds denominated in foreign currencies. For example, when the People's Bank of China accumulates foreign exchange as part of its management of the RMB, it buys government bonds in other countries, thereby adding to liquidity globally. Interest Rates Minus Nominal GDP Growth (Chart II-4): Nominal GDP growth can be thought of as a proxy for the return on capital. If interest rates are below the return on capital, then there is an incentive for firms to borrow and invest. The opposite is true if interest rates are above GDP growth. Currently, short-term rates are well below nominal GDP, signaling that central bank liquidity is plentiful. Chart II-3Monetary Indicators (I) Monetary Indicators (I) Monetary Indicators (I) Chart II-4Monetary Indicators (II) Monetary Indicators (II) Monetary Indicators (II) (2) Balance Sheet Liquidity Chart II-5 presents the ratio of short-term assets to total liabilities for the corporate and household sectors. It is a measure of readily-available cash or cash-like instruments that make it easier to weather economic downturns and/or credit tightening phases. The non-financial corporate sector is in very good shape from this perspective. The seizure of the commercial paper market during the GFC encouraged firms to hold more liquid assets on the balance sheet. However, the uptrend began in the early 1990s and likely reflects tax avoidance efforts. Households are also highly liquid when short-term assets are compared to income. Liquidity as a share of total discretionary financial portfolios is low, but this is not surprising given extraordinarily unattractive interest rates. The banking system is being forced to hold more liquid assets under the new Liquidity Coverage Ratio requirement (Chart II-6). This is positive from the perspective of reducing systemic risk, but it has negative implications for funding liquidity, as we will discuss below. Chart II-5Balance Sheet Liquidity Balance Sheet Liquidity Balance Sheet Liquidity Chart II-6Bank Balance Sheet Liquidity Bank Balance Sheet Liquidity Bank Balance Sheet Liquidity (3) Financial Market Transaction Liquidity: Transactions volumes and bid-ask spreads are the main indicators to watch to gauge financial market transaction liquidity. There was a concern shortly after the GFC that the pullback in risk-taking by important market-makers could severely undermine market liquidity, leading to lower transaction volumes and wider bid-ask spreads. The focus of concern was largely on the corporate bond market given the sharply reduced footprint of investment banks. The Fed's data on primary dealer positioning in corporates shows a massive decline from the pre-crisis peak in 2007 (Chart II-7). This represents a decline from over 10% of market cap to only 0.3%. The smaller presence of dealers could create a liquidity problem for corporate debt, especially if market-making dealers fail to adequately match sellers with buyers during market downturns. Yet, as highlighted by BCA's Global Fixed Income Strategy team, corporate bond markets have functioned well since the dark days of the Lehman crisis.2 Reduced dealer presence has not resulted in any unusual widening of typical relationships like the basis between Credit Default Swaps and corporate bond spreads. Other market participants, such as Exchange Traded Funds, have taken up the slack. Daily trading volume as a percent of market cap has returned to pre-Lehman levels in the U.S. high-yield market, although this is not quite the case for the investment-grade market (Chart II-8). Chart II-7Less Market Making Less Market Making Less Market Making Chart II-8Corporate Bond Trading Volume Corporate Bond Trading Volume Corporate Bond Trading Volume That said, it is somewhat worrying that average trade sizes in corporates are smaller now compared to pre-crisis levels - perhaps as much as 20% smaller according to estimates by the New York Fed. This is likely the result of the reduced risk-taking by the dealers and the growing share of direct electronic trading. Thus, it may feel like liquidity is impaired since it now takes longer to execute a large bond trade, even though transaction costs for individual trades have not been increasing. The bottom line is that financial market liquidity is not as good as in the pre-Lehman years. This is not a problem at the moment, but there could be some dislocations in the fixed-income space during the next period of severe market stress when funding liquidity dries up. (3) Funding Liquidity: There are few direct measures of funding liquidity. Instead, one can look for its "footprint" or confirming evidence, such as total private sector credit. If credit is growing strongly, it is a sign that funding liquidity is ample. Box II-3 explains why international credit flows are also important to watch for signs of froth in lending. BOX II-3 The Importance Of International Credit Flows The BIS highlights that swings in international borrowing amplify domestic credit trends. Cross border lending tends to display even larger boom-bust cycles than domestic credit, as can be seen in the major advanced economies in the lead up to the GFC, as well as some Asian countries just before the Asian crisis in the late 1990s (Chart II-9). When times are good, banks and the shadow banking system draw heavily on cross-border sources of funds, such that international credit expansion tends to grow faster during boom periods than the credit granted domestically by banks located in the country. Since G4 financial systems intermediate a major share of global credit, funding conditions within the G4 affect funding conditions globally, as BIS research shows.3 This research also demonstrates that financial cycles have become more highly correlated across economies due to increased financial integration. Booms in credit inflows from abroad are also associated with a low level of the VIX, which is another sign of ample funding liquidity conditions (Chart II-10). These periods of excessive funding almost always end with a financial crisis and a spike in the VIX. Chart II-9International Credit Is Highly Cyclical International Credit Is Highly Cyclical International Credit Is Highly Cyclical Chart II-10International Credit Booms Lead Spikes In The VIX International Credit Booms Lead Spikes In The VIX International Credit Booms Lead Spikes In The VIX Other measures of funding liquidity to watch include: Chart II-11Market Measures Of Funding Liquidity Market Measures Of Funding Liquidity Market Measures Of Funding Liquidity Libor-OIS Spread (Chart II-11): This is a measure of perceived credit risk of LIBOR-panel banks. The spread tends to widen during periods of banking sector stress. Spreads are currently low by historical standards. However, libor will be phased out by 2021, such that a replacement for this benchmark rate will have to be found by then. Bond-CDS Basis (Chart II-11): The basis is roughly the average difference between each bond's yield spread to Treasurys and the cost of insuring the bond in the CDS market. Arbitrage should keep these two spreads closely aligned, but increases in funding costs tied to balance sheet constraints during periods of market stress affect this arbitrage opportunity, allowing the two spreads to diverge. The U.S. high-yield or investment grade bond markets are a good bellweather, and at the moment they indicate relatively good funding liquidity. FX Basis Swap (Chart II-11): This is analogous to the bond-CDS basis. It reflects the cost of hedging currencies, which is critically important for international investors and lending institutions. The basis swap widens when there is financial stress, reflecting a pullback in funding liquidity related to currencies. The FX swap basis widened during the GFC and, unlike other spreads, has not returned to pre-Lehman levels (see below). Bank Leverage Ratios (Chart II-12): The ratio of loans to deposits is a measure of leverage in the banking system. Banks boost leverage during boom times and thereby provide more loans and funding liquidity to buy securities. In the U.S., this ratio has plunged since 2007 and shows no sign of turning up. Primary Dealers Securities Lending (Chart II-13): This is a direct measure of funding liquidity. Primary dealers make loans to other financial institutions with the purpose of buying securities, thereby providing both funding liquidity and market liquidity. Historically, shifts in dealer lending have been correlated with bid-ask spreads in the Treasury market. Securities lending is also correlated with the S&P 500, although it does not tend to lead the stock market. Dealer loans soared prior to 2007, before collapsing in 2008. Total loans have recovered, but have not reached pre-crisis highs, consistent with stricter regulations that forced the deleveraging of dealer balance sheets. Chart II-12U.S. Bank Leverage U.S. Bank Leverage U.S. Bank Leverage Chart II-13Securities Lending And Margin Debt bca.bca_mp_2017_10_01_s2_c13 bca.bca_mp_2017_10_01_s2_c13 NYSE Margin Debt (Chart II-13): Another direct measure of funding liquidity. The uptrend in recent years has been steep, although it is less impressive when expressed relative to market cap. Bank Lending Standards (Chart II-14): These surveys reflect bank lending standards for standard loans to the household or corporate sectors, but their appetite for lending for the purposes of securities purchases is no doubt highly correlated. Lending standards tightened in 2016 due to the collapse in oil prices, but they have started to ease again this year. Table II-1 provides a handy list of liquidity indicators split into our four categories. Taking all of these indicators into consideration, we would characterize liquidity conditions in the U.S. as fairly accommodative, although not nearly as abundant as the period just prior to the Lehman event. Monetary conditions are super easy, while balance sheet and financial market liquidity are reasonably constructive. In contrast, funding liquidity, while vastly improved since the GFC, is still a long way from the pre-Lehman go-go years according to several important indicators such as bank leverage. Moreover, the Fed is set to begin the process of unwinding the massive amount of monetary liquidity provided by its quantitative easing program. Chart II-14Bank Lending Standards Bank Lending Standards Bank Lending Standards Table II-1Liquidity Indicators To Watch October 2017 October 2017 Fed Balance Sheet Shrinkage: What Impact On Liquidity? Given that the era of quantitative easing has been a positive one for risk assets, it is unsurprising that investors are concerned about the looming unwind of the Fed's massive balance sheet. For example, Chart II-15 demonstrates the correlation between the change in G4 balances sheets and both the stock market and excess returns in the U.S. high-yield market. Chart II-16 presents our forecast for how quickly the Fed's balance sheet will contract. Following last week's FOMC meeting we learned that balance sheet reduction will begin October 1. For the first three months the Fed will allow a maximum of $6 billion in Treasurys and $4 billion in MBS to run off each month. Those caps will increase in steps of $6 billion and $4 billion, respectively, every three months until they level off at $30 billion per month for Treasurys and $20 billion per month for MBS. Chart II-15G4 Central Bank Balance Sheets G4 Central Bank Balance Sheets G4 Central Bank Balance Sheets Chart II-16Fed Balance Sheet Fed Balance Sheet Fed Balance Sheet We have received no official guidance on the level of bank reserves the Fed will target for the end of the run-off process. However, New York Fed President William Dudley recently recommended that this level should be higher than during the pre-QE period, and should probably fall in the $400 billion to $1 trillion range.4 In our forecasts we assume that bank reserves will level-off once they reach $650 billion. In that scenario the Fed's balance sheet will shrink by roughly $1.4 trillion by 2021. The level of excess reserves in the banking system will decline by a somewhat larger amount ($1.75 trillion). In terms of the impact of balance sheet shrinkage on overall liquidity conditions, it is useful to think about the four categories of liquidity described above. (1) Monetary Liquidity The re-absorption of excess reserves will mean that base money will contract (i.e. the sum of bank reserves held at the Fed and currency in circulation). However, we do not expect this to have a noticeable impact on the broader monetary aggregates, credit growth, the economy or inflation, outside of any effect it might have on the term premium in the bond market. The reasoning is that all those excess reserves did not have a major impact on growth and inflation when they were created in the first place. This was because the credit channel of monetary policy was blocked by a lack of demand (private sector deleveraging) and limited bank lending capacity (partly due to regulation). Banks were also less inclined to lend due to rising loan losses. Removing the excess reserves should have little effect on banks' willingness or ability to make new loans. In terms of asset prices, some investors believe that when the excess reserves were created, a portion of it found its way out of the banking system and was used to buy assets directly. That is not the case. The excess reserves were left idle, sitting on deposit at the Fed. They did not "leak" out and were not used to purchase assets. Thus, fewer excess bank reserves do not imply any forced selling. Nonetheless, the QE program certainly affected asset prices indirectly via the portfolio balance effect. Asset purchases supported both the economy and risk assets in part via a weaker dollar and to the extent that the policy lifted confidence in the system. But most importantly, QE depressed long-term interest rates, which are used to discount cash flows when valuing financial assets. QE boosted risk-seeking behavior and the search for yield, partly through the signaling mechanism that convinced investors that short-term rates would stay depressed for a long time. The result was a decline in measures of market implied volatility, such as the MOVE and VIX indexes. Could Bond Yields Spike? The risk is that the portfolio balance effect goes into reverse as the Fed unwinds the asset purchases. The negative impact on risk assets will depend importantly on the bond market's response. As highlighted in the Overview section, there will be a sharp swing in the flow of G4 government bonds available to the private sector, from a contraction of US$600 billion in 2017 to an increase of US$200 billion in 2018. Focusing on the U.S. market, empirical estimates suggest that the Fed's shedding of Treasurys could boost the 10-year yield by about 80 basis points because the private sector will require a higher term premium to absorb the higher flow of bonds. However, the impact on yields is likely to be tempered by two factors: Banks are required by regulators to hold more high-quality assets than they did in the pre-Lehman years in order to meet the new Liquidity Coverage Ratio. The BCA U.S. Bond Strategy service argues that growing bank demand for Treasurys in the coming years will absorb much of the net flow of Treasurys that the Fed is no longer buying.5 As the FOMC dials back monetary stimulus it will be concerned with overall monetary conditions, including short-term rates, long-term rates and the dollar. If long-term rates and/or the dollar rise too quickly, policymakers will moderate the pace of rate hikes and use forward guidance to talk down the long end of the curve so as to avoid allowing financial conditions to tighten too quickly. Thus, the path of short-term rates is dependent on the dollar and the reaction of the long end of the curve. It is difficult to estimate how it will shake out, but the point is that forward guidance will help to limit the impact of the shrinking Fed balance sheet on bond yields. Indeed, the Fed is trying hard to sever the link in investors' minds between balance sheet policy and signaling about future rate hikes, as highlighted by Chair Yellen's Q&A session following the September FOMC meeting. The bottom line is that the impact on monetary liquidity of a smaller Fed balance sheet should be minimal, although long-term bond yields will be marginally higher as a result. That said, much depends on inflation. If the core PCE inflation rate were to suddenly shift up to the 2% target or above, then bond prices will be hit hard, the VIX will surge and risk assets will sustain some damage. The prospect of a more aggressive pace of monetary tightening would undermine funding liquidity, compounding the negative impact on risk assets. (2) Funding Liquidity Chart II-17Tri-Party Repo Market Has Shrunk Tri-Party Repo Market Has Shrunk Tri-Party Repo Market Has Shrunk By unwinding its balance sheet, the Fed will be supplying securities into the market and removing cash. This will be occurring at a time when transactions in the tri-party repo market have fallen to less than half of their peak in 2007 due to stricter regulation (Chart II-17). This market has historically been an important source of short-term funding, helping to meet the secular rise in demand for short-term, low-risk instruments, largely from non-financial corporations, asset managers and foreign exchange reserve funds. If the Fed drains reserves from the system and T-bill issuance does not increase substantially to compensate, a supply shortage of short-maturity instruments could develop. We can see how this might undermine the Fed's ability to shift short-term interest rates higher under its new system of interest rate management, where reverse repos and the interest rate paid on reserves set the floor for other short-term interest rates. However, at the moment we do not see the risk that fewer excess reserves on its own will negatively affect funding liquidity. Again, any impact on funding liquidity would likely be felt via a sharp rise in interest rates and pullback in the portfolio balance effect, which would occur if inflation turns up. But this has more to do with rising interest rates than the size of the Fed's balance sheet. Indeed, balance sheet shrinkage could actually improve funding liquidity provided via the bilateral repo market, securities-lending, derivatives and prime brokerage channels. These are important players in the collateral supply chain. A recent IMF working paper emphasizes that collateral flows are just as important in credit creation as money itself.6 Collateral refers to financial instruments that are used as collateral to fund positions, which can be cash or cash-like equivalents. Since pledged collateral can be reused over and over, it can generate significantly more total lending than the value of the collateral itself. The Fed's overnight reverse-repo facility includes restrictions that the collateral accessed from its balance sheet can only be used in the tri-party repo system. Thus, the Fed's presence in the collateral market has reduced the "velocity of collateral." Table II-2 shows that the reuse rate of collateral, or its velocity, has fallen from 3.0 in 2007 to 1.8 in 2015. Table II-2Collateral Velocity October 2017 October 2017 The combination of tighter capital regulations and Fed asset purchases has severely limited the available space on bank balance sheets to provide funding liquidity. Regulations force banks to carry more capital for a given level of assets. Fed asset purchases have forced a large portion of those assets to be held as reserves, limiting banks' activity in the bilateral repo market. There is much uncertainty surrounding this issue, but it appears that an unwind the Fed's balance sheet will free up some space on bank balance sheets, possibly permitting more bilateral repo activity and thus a higher rate of collateral velocity. It may also relieve concerns about a shortage of safe-haven assets. Nonetheless, we probably will not see a return of collateral velocity to 2007 levels because stricter capital regulations will still be in place. What About Currency Swaps? Some have argued that this removal of cash could also lead to an appreciation of the U.S. dollar. In particular, Zoltan Pozsar of Credit Suisse has observed a correlation between U.S. bank reserves and FX basis swap spreads.7 There is also a strong correlation between FX swap spreads and the U.S. dollar (Chart II-18). Chart II-18FX Basis Swap And Reserves FX Basis Swap And Reserves FX Basis Swap And Reserves One possible chain of events is that, as the Fed drains cash from the market, there will be less liquidity in the FX swap market. Basis swap spreads will widen as a result, and this will cause the dollar to appreciate. In this framework, the unwinding of the Fed's balance sheet will put upward pressure on the U.S. dollar. However, it is also possible that the chain of causation runs in the other direction. The BIS has proposed a model8 where a stronger dollar weakens the capital positions of bank balance sheets. This causes them to back away from providing liquidity to the FX swap market, leading to wider basis swap spreads. In this model, a strong dollar leads to wider basis swap spreads and not the reverse. If this is the correct direction of causation, then we should not expect any impact on the dollar from the unwinding of the Fed's balance sheet. At the moment it is impossible to tell which of the above two theories is correct. All we can do is monitor the correlation between reserves, FX basis swap spreads and the dollar going forward. Conclusions: Overall liquidity conditions are reasonably constructive for risk assets at the moment. Financial market and balance sheet liquidity are adequate. Monetary policy is extremely easy, although the low level of money and credit growth underscores that the credit channel of monetary policy is still somewhat impaired and/or constrained relative to the pre-Lehman years. Funding liquidity has recovered from the Great Financial Crisis lows, but it is far from frothy. More intense regulation means that funding liquidity will probably never again be as favorable for risk assets as it was before the crisis. But, hopefully, efforts by the authorities to reduce perceived systemic risk mean that funding liquidity may not be as quick to dry up as was the case in 2008, in the event of another negative shock. Unwinding the Fed's balance sheet represents a risk to investors because QE played such an important role in reducing risk premia in financial markets. However, we believe that the bond market's reaction will be far more important than balance sheet shrinkage. As long as the Fed can limit the bond market damage via forward guidance, then risk assets should take the Fed's unwind in stride. It will be a whole different story, however, if inflation lurches higher. The technical impact of balance sheet unwind on the inner workings of the credit market is very complicated and difficult to forecast. Asset sales could lead to a shortage of short-term high-quality assets. However, this is more a problem in terms of the Fed's ability to raise interest rates than for funding liquidity. A smaller balance sheet could, in fact, improve funding liquidity to the extent that it frees up space on banks' balance sheets. Mark McClellan Senior Vice President The Bank Credit Analyst Ryan Swift Vice President U.S. Bond Strategy 1 D. Domanski, I. Fender and P. McGuire, "Assessing Global Liquidity," BIS Quarterly Review (December 2011). 2 Please see BCA Global Fixed Income Strategy Weekly Report, "Global Interest Rate Strategy For The Remainder Of 2017," dated July 18, 2017, available at gfis.bcaresearch.com 3 E. Cerutti, S. Claessens and L. Ratnovski, "A Primer on 'Global Liquidity'," CEPR Policy Portal (June 8, 2014). 4 William C. Dudley, "The U.S. Economic Outlook and the Implications for Monetary Policy," Federal Reserve Bank of New York (September 07, 2017). 5 Please see BCA U.S. Bond Strategy Weekly Report, "The Great Unwind," dated September 19, 2017, available at usbs.bcaresearch.com 6 M. Singh, "Collateral Reuse and Balance Sheet Space," IMF Working Paper (May 2017). 7 Alexandra Scaggs, "Where would you prefer your balance sheet: Banks, or the Federal Reserve?" Financial Times Alphaville (April 13, 2017). 8 S. Avdjiev, W. Du, C. Koch, and Hyun S.Shin, "The dollar, bank leverage and the deviation from covered interest parity," BIS Working Papers No.592 (Revised July 2017).