Sectors

Highlights China's high-profile jawboning draws attention to tightness in metals markets, and raises the odds the State Reserve Board (SRB) will release some of its massive copper and aluminum stockpiles in the near future. Over the medium- to long-term, the lack of major new greenfield capex raises red flags for the IEA's ambitious low-carbon pathway released last week, which foresees the need for a dramatic increase in renewable energy output and a halt in future oil and gas investment to achieve net-zero emissions by 2050. Copper demand is expected to exceed mined supply by 2028, according to an analysis by S&P, which, in line with our view, also sees refined-copper consumption exceeding production this year (Chart of the Week). A constitution re-write in Chile and elections in Peru threaten to usher in higher taxes and royalties on mining in these metals producers, placing future capex at risk. Chile's state-owned Codelco, the largest copper producer in the world, fears a bill to limit mining near glaciers could put as much as 40% of its copper production at risk. We remain bullish copper and look to get long on politically induced sell-offs as the USD weakens. Feature Politicians are inserting themselves in the metals markets' supply-demand evolutions to a greater degree than in the past, which is complicating the short- and medium-term analysis of prices. This adds to an already-difficult process of assessing markets, given the opacity of metals fundamentals – particularly inventories, which are notoriously difficult to assess. Chinese Communist Party (CCP) jawboning of market participants in iron ore, steel, copper and aluminum markets over the past two weeks has weakened prices, but, with the exception of steel rebar futures in Shanghai – down ~ 17% from recent highs, and now trading at ~ 4911 RMB/MT –  the other markets remain close to records.  Benchmark 62% Fe iron ore at the port of Tianjin was trading ~ 4% lower at $211/MT, while copper and aluminum were trading ~ 5.5% and 6.5% off their recent records at $4.535/lb and $2,350/MT, respectively. In addition to copper, aluminum markets are particularly tight (Chart 2). Jawboning aside, if fundamentals continue to keep prices elevated – or if we see a new leg up – China's high-profile jawboning could presage a release by the State Reserve Board (SRB) of some of its massive copper and aluminum stockpiles in the near term. In the case of copper, market guesses on the size of this stockpile are ~ 2mm to 2.7mm MT. On the aluminum side, Bloomberg reported CCP officials were considering the release of 500k MT to quell the market's demand for the metal. Chart of the WeekContinue Tightening In Copper Expected Chart 2Aluminum Remains Tight Brownfield Development Not Sufficient Our balances assessments continue to indicate key base metals markets are tight and will remain so over the short term (2-3 years). Economies ex-China are entering their post-COVID-19 recovery phase. This will be followed by higher demand from renewable generation and grid build-outs that will put them in direct competition with China for scarce metals supplies for decades to come. Markets will continue to tighten. In the bellwether copper market, we expect this tightness to remain a persistent feature of the market over the medium term – 3 to 5 years out – given the dearth of new supply coming to market. Copper prices are highly correlated with the other base metals (Chart 3) – the coefficient of correlation with the other base metals making up the LME's metals index is ~ 0.86 post-GFC – and provide a useful indicator of systematic trends in these markets. Chart 3Copper Correlation With LME Index Ex-Copper Copper ore quality has been falling for years, as miners focused on brownfield development to extend the life of mines (Chart 4). In Chart 5, we show the ratio of capex (in billion USD) to ore quality increases when capex growth is expanding faster than ore quality, and decreases when capex weakens and/or ore quality degradation is increasing. Chart 4Copper Capex, Ore Quality Declines Chart 5Capex-to-Ore-Quality Decline Set Market Up For Higher Prices Falling prices over the 2012-19 interval coincide with copper ore quality remaining on a downward trend, likely the result of previous higher prices that set off the capex boom pre-GFC. The lower prices favored brownfield over greenfield development. Goehring and Rozencwajg found in their analysis of 24 mines, about 80% of gross new reserves booked between 2001-2014 were due not to new mine discoveries but to companies reclassifying what was once considered to be waste-rock into minable reserves, lowering the cut-off grade for development.1 This is consistent with the most recent datapoints in Chart 5, due to falling ore grade values, as companies inject less capex into their operations and use it to expand on brownfield projects. Higher prices will be needed to incentivize more greenfield projects. A new report from S&P Global Market Intelligence shows copper reserves in the ground are falling along with new discoveries.2 According to the S&P analysts, copper demand is expected to exceed mined supply by 2028, which, in line with our view, sees refined-copper consumption exceeding production this year. Renewables Push At Risk Just last week, the IEA produced an ambitious and narrow path for governments to collectively reach a net-zero emissions (NZE) goal by 2050.3 Among its many recommendations, the IEA singled out the overhaul of the global electric grid, which will be required to accommodate the massive renewable-generation buildout the agency forecasts will be needed to achieve its NZE goals. The IEA forecasts annual investment in transmission and distribution grids will need to increase from $260 billion to $820 billion p.a. by 2030. This is easier said than done. Consider the build-out of China's grid, which is the largest grid in the world. To become carbon neutral by 2060, per its stated goals, investment in China’s grid and associated infrastructure is expected to approach ~ $900 billion, maybe more, over the next 5 years.4 The world’s largest fossil-fuel importer is looking to pivot away from coal and plans to more than double solar and wind power capacity to 1200 GW by 2030. Weening China off coal and rebuilding its grid to achieve these goals will be a herculean lift. It comes as no surprise that IEA member states have pushed back on the agency's NZE-by-2050 plan. This primarily is because of its requirement to completely halt fossil-fuel exploration and spending on new projects. Japan and Australia have pushed back against this plan, citing energy security concerns. Officials from both countries have stated that they will continue developing fossil fuel projects, as a back-up to renewables. Japan has been falling behind on renewable electricity generation (Chart 6). Expensive renewables and the unpopularity of nuclear fuel could make it harder for the world’s fifth largest fossil fuels consumer to move away from fossil fuels. Around the same time the IEA released its report, Australia committed $464 million to build a new gas-fired power station as a backup to renewables. Chart 6Japan Will Continue Building Fossil-Fuel Back-Up Generation Just days after the IEA report was published, the G7 nations agreed to stop overseas coal financing. This could have devastating effects for emerging and developing nations‘ electricity grids which are highly dependent on coal. In 2020 70% and 60% of India and China’s electricity respectively were produced by coal (Chart 7).5 Chart 7EM Economies Remain Reliant On Coal-Fired Generation Near-Term Copper Supply Risks Rise Even though inventories appear to be rebuilding, mounting political risks keep us bullish copper (Chart 8). Lawmakers in Chile and Peru are in the process of re-writing their constitutions to, among other things, raise royalties and taxes on mining activities in their respective countries. This could usher in higher taxes and royalties on mining for these metals producers, placing future capex at risk. In addition, Chile's state-owned Codelco, the largest copper producer in the world, fears a bill to limit mining near glaciers could put as much as 40% of its copper production at risk.6 None of these events is certain to occur. Peruvian elections, for one thing, are too close to call at this point, and Chile has a history of pro-business government. However, these are non-trivial odds – i.e., greater than Russian roulette odds of 1:6 – and if any or all of these outcomes are realized, higher costs in copper and lithium prices would result, and miners would have to pass those costs on to buyers. Bottom Line: We remain bullish base metals, especially copper. Another leg up in copper would pull base metals higher with it. We would look to get long on politically induced sell-offs, particularly with the USD weakening, as expected Chart 8Global Copper Inventories Rebuilding But Still Down Y/Y   Robert P. Ryan Chief Commodity & Energy Strategist rryan@bcaresearch.com Ashwin Shyam Research Associate Commodity & Energy Strategy ashwin.shyam@bcaresearch.com     Commodities Round-Up Energy: Bullish Next Tuesday's OPEC 2.0 meeting appears to be a fairly staid affair, with little of the drama attending previous gatherings. Russian minister Novak observed the coalition would be jointly "calculating the balances" when it meets, taking into account the likely official return of Iran as an exporter, according to reuters.com. We expect a mid-year deal on allowing Iran to return to resume exports under the nuclear deal abrogated by the Trump administration in 2019, and reckon Iran has ~ 1.5mm b/d of production it can bring back on line, which likely would return its crude oil production to something above 3.8mm b/d by year-end. We are maintaining our forecast for Brent to average $64.45/bbl in 2H21; $75 and $78/bbl, in 2022 and 2023, respectively. By end 2023, prices trade to $80/bbl. Our forecast is premised on a wider global recovery going into 2H21, and continued production discipline from OPEC 2.0 (Chart 9). Base Metals: Bullish Our stop-losses was elected on our long Dec21 copper position on May 21, which means we closed the position with 48.2% return. The stop loss on our long 2022 vs short 2023 COMEX copper futures backwardation recommendation also was elected on May 20, leaving us with a return of 305%. We will be looking for an opportunity to re-establish these positions. Precious Metals: Bullish We expect the collapse in bitcoin prices, the US Fed’s decision to not raise interest rates, and a weakening US dollar to keep gold prices well bid (Chart 10). China’s ban on cryptocurrency services and Musk’s acknowledgment of the energy intensity of Bitcoin mining sent Bitcoin prices crashing. The Fed’s decision to keep interest rates constant, despite rising inflation and inflation expectations will reduce the opportunity cost of holding gold. According to our colleagues at USBS, the Fed will make its first interest rate hike only after the US economy has reached "maximum employment". The Job Openings and Labor Turnover Survey reported that job openings rose nearly 8% in March to 8.1 million jobs, however, overall hiring was little changed, rising by less than 4% to 6 million. As prices in the US rise and the dollar depreciates, gold will be favored as a store of value. On the back of these factors, we expect gold to hit $2,000/oz. Ags/Softs: Neutral Corn futures were trading close to 20% below recent highs earlier in the week at ~ $6.27/bu, on the back of much faster-than-expected plantings. Chart 9 Chart 10     Footnotes 1     Please refer to Goehring & Rozencwajg’s Q1 2021 market commentary. 2     Please see Copper cupboard remains bare as discoveries dwindle — S&P study published by mining.com 20 May 2021. 3    Please see Net Zero by 2050 – A Roadmap for the Global Energy Sector, published by the IEA. 4    Please see China’s climate goal: Overhauling its electricity grid, published by Aljazeera.  5    We discuss this in detail in Surging Metals Prices And The Case For Carbon-Capture published 13 May 2021, and Renewables ESG Risks Grow With Demand, which was published 29 April 2021.  Both are available at ces.bcaresearch.com. 6    Please see A game of chicken is clouding tax debate in top copper nation, Fujimori looks to speed up projects to tap copper riches in Peru and Codelco says 40% of its copper output at risk if glacier bill passes published by mining.com 24, 23 and 20 May 2021, respectively.    Investment Views and Themes Strategic Recommendations Tactical Trades Commodity Prices and Plays Reference Table Trades Closed in 2021 Summary of Closed Trades

Underweight As a follow up to yesterday’s Sector Insight report where we reiterated our S&P financials downgrade, today we cover banks that were used as the vehicle to trim financials to a neutral allocation. Housing starts and permits came off the boil last week and failed to live up to economists’ upbeat expectations. Lumber is getting clobbered and entered a bear market having first surged to five standard deviations above its five decade mean. Moreover, the latest news from the University of Michigan survey of consumers’ sentiment on buying conditions for houses made for grim reading signaling that a key bank loan category, mortgage credit, is in for a rough summer/fall season (top panel). Tack on the nosedive in mortgage applications for purchasing a new home courtesy of rising mortgage rates, albeit from a low base, and factors are falling into place for a housing-catalyzed underperformance phase in banks (bottom panel). Bottom Line: This week we trimmed the S&P banks index to underweight. The ticker symbols for the stocks in this index are: BLBG: S5BANKX – JPM, BAC, C, WFC, USB, PNC, TFC, FRC, FITB, SIVB, KEY, MTB, RF, CFG, HBAN, CMA, ZION, PBCT. For more details, please refer to this Tuesday's Strategy Report.

Special Report

Highlights House prices are rising rapidly across the developed markets, in response to the extraordinary monetary and fiscal policy stimulus implemented to fight the pandemic. Evidence points to the house price surge being driven by monetary policy that has left real interest rates far below equilibrium levels. Supply factors are a secondary cause of the house price boom. Financial stability risks stemming from rising house prices are less acute than the pre-2008 experience, as overall household leverage has grown more slowly during the pandemic and global banks are better capitalized. Rapidly rising house prices are forcing some central banks to turn less accommodative earlier than expected. The recent hawkish turns by the Bank of Canada and Reserve Bank of New Zealand may be canaries in the coal mine for other central banks – perhaps even the Fed – if house prices and household leverage start rising together. Feature The COVID-19 pandemic led to the sharpest economic recession since World War II, alongside an enormous rise in unemployment. Consensus expectations call for the output gap to be closed (or mostly closed) in most advanced economies by the end of this year, but it remains an open question how quickly these economies will be able to return to full employment amid potentially permanent shifts in demand for office space and goods sold at physical, “brick and mortar” retail locations. Despite this sizeable and swift economic shock, house price appreciation accelerated last year in the developed world. Chart II-1 highlights that US house prices rose at an 18% annualized pace in the second half of 2020, whereas they accelerated at a high-single digit pace in developed markets ex-US (on a GDP-weighted basis). This, in conjunction with a sharp rise in the household sector credit-to-GDP ratio (Chart II-2), has unnerved some investors while raising questions about the implications for monetary policy. Chart II-1House Prices Are Surging Around The World Chart II-2Rising Fears About Deteriorating Household Balance Sheets Before we discuss the investment implications of the global housing boom, however, we must first accurately determine the reasons why it is happening. The Work-From-Home Effect: Less Than Meets The Eye When analyzing the surprising behavior of the housing market last year, the working-from-home effect brought upon by the pandemic emerges as an obvious factor potentially explaining house price gains. Last year, following recommended or mandatory stay-at-home orders from governments, most office-based businesses rapidly shifted to work-from-home arrangements as an emergency response. However, in the month or two following the beginning of stay-at-home orders, several national US surveys found many office workers preferred the flexibility afforded by work-from-home arrangements. Many employers, correspondingly, found that the productivity of their employees did not suffer while working from home, or that it even improved. Several prominent corporations in the US have subsequently made some work-from-home options permanent, or even allowed employees to work from offices in a different city than they did prior to the pandemic. Newfound work-from-home options have undoubtedly created new demand for housing, and thus explained the surge in house prices seen over the past year in the minds of some investors. However, in our view, evidence from the US, the UK, and France suggests that the work-from-home effect better explains differences in price gains across housing types and within large metropolitan areas, rather than aggregate or national-level changes in house prices. Chart II-3 provides some quantification of the impact of work-from-home policies by plotting US resident migration patterns by city. This data has been compiled by CBRE, and the impact of COVID is shown as the change in net move-ins from 2019 to 2020 per 1000 people. This helps control for the underlying migration pattern that existed in US cities prior to the pandemic. Chart II-3Work From Home Policies Have Impacted Migration Trends… The chart highlights that the negative migration impact from COVID has been mostly concentrated in New York City and the three most populous cities on the West Coast (by metro area): Los Angeles, San Francisco, and Seattle. And yet, Chart II-4 highlights that house price inflation in these four cities has accelerated to a double-digit pace, only modestly below the national average. Chart II-4...But Cities With Outward Migration Still Have Very Strong House Price Gains The house price indexes shown in Chart II-4 represent aggregate, metro area trends, and clearly some regions within these metro areas have experienced house price deceleration or outright deflation versus gains in areas outside the urban core. But Chart II-5 highlights that house prices have declined in Manhattan basically in line with the change in net move-ins as a share of the population, underscoring that double-digit metro area-wide house price gains appear to be vastly disproportionate to changes in net migration. Similarly, Chart II-6 highlights that rents decelerated in the US over the past year but remained in positive territory and grew at a 3.5% annualized rate from February to April. Chart II-5In Manhattan, House Prices Have Tracked Net Migration Chart II-6Rent Costs Have Decelerated, But Have Not Contracted Evidence from Paris and London also suggests that a work-from-home effect is insufficient to explain broad house price gains. Panel 1 of Chart II-7 highlights that house prices in France have accelerated significantly, but that apartment prices have decelerated only fractionally in lockstep. Panel 2 shows that the acceleration in house prices does reflect a work-from-home effect, as prices have risen faster in inner Parisian suburbs. Panel 3, however, highlights that Parisian apartment prices, the dominant property type in the urban core, have decelerated modestly. Chart II-8 highlights that house price gains have not even decelerated in greater London; they have been merely been modestly outstripped by gains in Outer South East (outside of the Outer Metropolitan Area). Chart II-7In France, Parisian Apartment Prices Are Simply Lagging, Not Falling Chart II-8In The UK, Greater London Property Prices Are Accelerating     The Policy Effect: The Fundamental Driver Of The Housing Market Despite the broader location flexibility that work-from-home policies now provide to potential homeowners, it seems inconceivable that the housing market would have responded in the manner that it has over the past year given the size of the economic shock brought on by the pandemic without significant support from policy. Above-the-line fiscal measures to the pandemic have totaled in the double-digits in advanced economies (Chart II-9), and monetary policy has contributed to easier financial conditions via rate cuts, asset purchases, and sizeable programs to support financial market liquidity. Chart II-9There Has Been A Massive Fiscal Policy Response To The Crisis In fact, Charts II-10-II-13 present compelling evidence that fiscal and monetary policy have been the core drivers of significant house price gains over the past year. Charts II-10 and II-11 plot the above-the-line fiscal response of advanced economies against the year-over-year growth rate in house prices as well as its acceleration (the change in the year-over-year growth rate). The charts show a clearly positive relationship, with a stronger link between the pandemic fiscal response and the acceleration in house prices. Chart II-10Differences In Last Year’s Fiscal Response… Chart II-11…Help Explain Differences In House Price Gains Chart II-12Pre-Pandemic Differences In The Monetary Policy Stance… Chart II-13…Do An Even Better Job Of Explaining 2020 House Price Gains   Charts II-12 and II-13 highlight the even stronger link between house prices and the pre-pandemic monetary policy stance in advanced economies, defined as the difference between each country’s 2-year government bond yield and its Taylor Rule-implied policy interest rate as of Q4 2019. We construct each country’s Taylor Rule using the original specification, with core consumer price inflation, a 2% inflation target, and real potential GDP growth as the definition of the real equilibrium interest rate. The charts make it clear that easy monetary policy strongly explains house price gains in 2020, particularly the year-over-year percent change rather than its acceleration. This makes sense, given that monetary policy was already quite easy in many countries at the onset of the pandemic – meaning that changes were less pronounced than they would have been had interest rates been higher. The explanation that emerges from Charts II-10-II-13 is that historic fiscal easing, combined with an easy starting point for monetary policy – that became even easier last year – enabled demand from work-from-home policies to manifest during an extremely severe recession. We agree that work-from-home policies have shifted the geographic preferences of some home buyers and likely provided a new source of net demand from renters in urban cores purchasing homes in outlying areas. But we strongly doubt that the net effect of work-from-home policies in the midst of an extreme shock to economic activity would have caused the rise in house prices that we have observed, certainly not to this level, without major support from policy. This underscores that policy, and not the work-from-home effect, has and will likely remain the core driver of the global housing market. The Supply Effect: Mostly A Red Herring Chart II-14Countries Fall Into Two Groups In Terms Of The Relative Trend In Real Residential Investment One perennial question that emerges when analyzing the housing market, particularly in markets with outsized house price gains, is the impact of constrained supply. It is frequently argued that constrained supply is squeezing prices higher in many markets, and that the appropriate policy solution to extreme house price gains is to enable widespread housing construction – not to raise interest rates. We do not rule out the potential impact of constrained supply in certain cities or regional housing markets, and we have highlighted in previous research that a positive relationship does exist between population density in urban regions and median house price-to-income ratios.1 But as a broad explanation for supercharged house price gains, the supply argument appears to fall flat. Chart II-14 presents the most standardized measure of cross-country housing supply available for several advanced economies, the trend in real residential investment relative to real GDP over time. These series are all rebased to 100 as of 1997, prior to the 2002-2007 US housing market boom. The chart makes it clear that advanced economies generally fall into two groups based on this metric: those that have seen declines in real residential investment relative to GDP, especially after the global financial crisis (panel 1), and those that have experienced either an uptrend in housing construction relative to output or have seen a flat trend (panel 2). If scarce housing supply was the core driver of outsized house price gains, then we would expect to see stronger gains in the countries shown in panel 1 and smaller gains in the countries shown in panel 2. In fact, mostly the opposite is true: Charts II-15 and II-16 highlight that the relationship between the level of these indexes today relative to their 1997 or 2005 levels is positively related to the magnitude of house price gains last year, suggesting that housing market supply has generally been responding to demand over the past decade. The US and possibly New Zealand stand as possible exceptions to the trend, suggesting that relatively scarce supply may be boosting prices even further in these markets beyond what fiscal and monetary policy would suggest. Chart II-15Countries That Have Seen A Stronger Pace Of Residential Investment… Chart II-16…Have Experienced Stronger House Price Gains   Chart II-17Is This Not Enough Supply, Or Too Much Demand? As a final point about the inclination of investors to gravitate towards supply-side arguments related to the housing market, Chart II-17 presents a simple thought experiment. The chart shows a simple housing supply-demand curve diagram, in a scenario where the demand curve for housing has shifted out more than the supply curve has (thus raising house prices). Is this a scenario in which supply is too tight? Or is it a case in which demand is too strong? In our view, the tight supply answer is reasonable in circumstances where the increase in demand is normal or otherwise sustainable. But Charts II-10-II-13 clearly showed that housing demand is being boosted by easy policy, which in the case of some countries has occurred for years: interest rates have remained well below levels that macroeconomic theory would traditionally consider to be in equilibrium, and this has occurred alongside significant household sector leveraging (Chart II-18). As such, in our view, investors should be more inclined to view the global housing market as generally being driven by demand-side rather than supply-side factors. This Is Not 2007/08 … Yet We highlighted in Chart II-2 above that the household sector debt-to-GDP ratio increased sharply last year, which has raised some questions about debt sustainability among investors. For the most part, the rise in this ratio actually reflects denominator effects (namely a sharp contraction in nominal GDP) rather than a huge surge in household debt. Chart II-19 shows BIS data for the annual growth in total household debt in developed economies was roughly stable last year, at least until Q3 (the most recent datapoint available from the BIS). Chart II-18Low Interest Rates Have Fueled Household Leveraging Chart II-19Total Credit Growth Has Been Stable, But Mortgage Credit Growth Is Accelerating Chart II-20US Mortgage Growth Is Picking Up, As Repayments Slow Consumer Credit Growth But Chart II-19 shows the recent trend in total household debt, which masks diverging mortgage and non-mortgage debt trends. In the US, euro area, Canada, and Sweden, household mortgage debt has accelerated to varying degrees, underscoring that households have likely paid down non-mortgage debt with some of the savings that they have accumulated from a significant reduction in spending on services. Chart II-20 shows this effect directly in the case of the US; mortgage debt growth accelerated by roughly 1.5 percentage points in the second half of the year, whereas consumer credit growth (made up of student loans, auto loans, credit cards, and other revolving credit) decelerated significantly. This aligns with data showing that US households have used some of their savings windfall to pay down their credit card balances. This changing mix within household debt - less higher-interest-rate consumer credit, more lower-interest-rate collateralized mortgage debt – could, on the margin, help mitigate financial stability risks from the housing boom by moderating overall debt service burdens. The starting point for the latter matters, though, in accurately assessing the risks from rising house prices and increased mortgage debt, particularly in countries where household debt levels are already high. According to data from the BIS, the US already has one of the lowest household debt service ratios (7.6%) among the developed economies (Chart II-21).2 This compares favorably to the double-digit debt service ratios in the “higher-risk” countries like Canada (12.6%), Sweden (12.1%) and Norway (16.2%). On top of that, US commercial banks have become far more prudent with mortgage loan underwriting standards since the 2008 financial crisis. The New York Fed’s Household Debt and Credit report shows that an increasing majority of mortgage lending made by US banks since the 2008 crisis has been to those with very high FICO credit scores (Chart II-22). This is in sharp contrast to the steady lending to “subprime” borrowers with poor credit scores that preceded the 2008 financial crisis. The median FICO score for new mortgage originations as of Q1 2021 was 788, compared to 707 in Q4 2006 at the peak of the mid-2000s US housing boom. Chart II-21Diverging Trends In Global Household Debt Servicing Costs Chart II-22US Banks Have Become More Prudent With Mortgage Lending   US bank balance sheets are also now less directly exposed to a fall in housing values. Residential loans now represent only 10% of the assets on US bank balance sheets, compared to 20% at the peak of the last housing bubble (Chart II-23). This puts the US in the “lower-risk” group of countries in Europe, the UK and Japan where mortgages are less than 20% of bank balance sheets. This compares favorably to the “higher risk” group of countries where residential loans are a far larger share of bank assets (Chart II-24), like Canada (32%), New Zealand (49%), Sweden (45%) and Australia (40%). Chart II-23Banks Have Limited Direct Exposure To Housing Here Chart II-24Banks Are Far More Exposed To Housing Here   Like nature, however, the financial ecosystem abhors a vacuum. “Non-bank” mortgage lenders have filled the void from traditional US banks reducing their lending to lower-quality borrowers, and they now represent around two-thirds of all US mortgage origination, a big leap from the 20% origination share in 2007. Non-bank lenders have also taken on growing shares of new mortgage origination in other countries like the UK, Canada and Australia. Chart II-25Global Banks Can Withstand A Housing Shock Non-bank lenders do not take deposits and typically fund themselves via shorter-term borrowings, which raises the potential for future instability if credit markets seize up. These lenders also, on average, service mortgages with a higher probability of default, so they are exposed to greater credit losses when house prices decline. However, the risk of a full-blown 2008-style commercial banking crisis, with individual depositors’ funds at risk from a bank failure, are reduced with a greater share of riskier mortgage lending conducted by non-bank entities. This is especially true with global commercial banks far better capitalized today, with double-digit Tier 1 capital ratios (Chart II-25), thanks to regulatory changes made after the Global Financial Crisis. Net-net, we conclude that the overall financial stability implications of the current surge in house prices in the developed economies are relatively modest on average. The acceleration in mortgage growth has occurred alongside reductions in non-mortgage growth, at a time when banks are better able to withstand a shock from any sustained future downturn in house prices. However, if house prices continue to accelerate and new homebuyers are forced to take on ever increasing amounts of mortgage debt, financial stability issues could intensify in some countries. Services spending will recover in a vaccinated post-COVID world, as economies reopen and consumer confidence improves, which will likely end the trend of falling non-residential consumer debt offsetting rising mortgage debt in countries like the US and Canada. Overall levels of household debt could begin to rise again relative to incomes, building up future financial stability risks when central banks begin to normalize pandemic-related monetary policies – a process that has already started in some countries because of the housing boom. The Monetary Policy Implications Of Surging House Prices Rapidly appreciating house prices are becoming an area of concern for policymakers in countries like Canada and New Zealand, where the affordability of housing is becoming a political, as well as an economic, issue. In the case of New Zealand, the government has actually altered the remit of the Reserve Bank of New Zealand (RBNZ) to more explicitly factor in the impact of monetary policy on housing costs. The Bank of Canada announced in April that it would taper its pace of government debt purchases and signaled that its decision was based, at least in small part, on signs of speculative behavior in Canada’s housing market. Macroprudential measures like limiting loan-to-value ratios of new mortgage loans are a policy option that governments in those countries have already implemented to try and cool off housing demand. Yet while such measures can help alleviate demand-supply mismatches in certain cities and regions, the efficacy of such measures in sustainably slowing the ascent of house prices on a national scale is unclear. In the April 2021 IMF Global Financial Stability Report, researchers estimated that, for a broad group of countries, the implementation of a new macro-prudential measure designed to cool loan demand reduced national household debt/GDP ratios by a mere one percentage point, on average, over a period encompassing four years.3 If macroprudential measures are that ineffective in sustainably reducing demand for mortgage loans, then the burden of slowing house price appreciation will have to fall on the more blunt instruments of monetary policy. Importantly, surging house price inflation is not likely to give a boost to realized inflation measures – an important issue given the current backdrop of rapidly rising realized inflation rates in many countries. Housing costs do represent a significant portion of consumer price indices in many developed countries, ranging from 19% in New Zealand to 33% in the US (Chart II-26), with the euro area being the outlier with housing having a mere 2% weighting in the headline inflation index. Chart II-26A Limited Impact On Actual Inflation From Housing Yet those so-called “housing” categories overwhelmingly measure only housing rental costs and not actual house prices. This is an important distinction because rents – which are often imputed measures like in the US and not even actual rental costs - are rising at a far slower pace than actual house prices in most countries, so the housing contribution to realized inflation is relatively modest. So the good news is that booming house prices will not worsen the acceleration of realized global inflation that has concerned investors and policymakers in 2021. Yet that does not mean that central bankers will not be forced to tighten policy to cool off red-hot housing demand that is clearly being fueled by persistently negative real interest rates. In Chart II-27 and Chart II-28, we show both nominal and real policy interest rates for the “lower risk” and “higher risk” country groupings that we described earlier. The real policy rates are nominal policy rates versus realized headline CPI inflation. The dotted lines in the charts represent the future path of rates discounted by markets. Specifically, the projection for nominal rates is taken from overnight index swap (OIS) forward curves, while the projection for real rates is calculated by subtracting the discounted path of inflation expectations extracted from CPI swap forwards. Chart II-27Markets Discounting Negative Real Rates For The Next Decade Chart II-28Negative Real Rates Are Unsustainable During A Housing Bubble   There are two key takeaways from these charts: Real policy interest rates are at or very close to the most deeply negative levels seen since the 2008 financial crisis. Markets are discounting that real rates will be at or below 0% for most of the next decade. Admittedly, there is room for debate over what the equilibrium level of real interest rates (a.k.a. “r-star”) should be in the coming years. However, we deem it a major stretch to believe that real rates need to be persistently low or negative for the next ten years to support even trend growth across the developed economies. In our view, the current boom in housing demand and mortgage borrowing provides clear evidence that negative real rates are below equilibrium and, thus, are stimulating credit demand. Thus, the only way for a central bank to cool off housing demand will be to raise both nominal and, more importantly, real interest rates. Canada and New Zealand will be the “canaries in the coal mine” among developed market central banks for such a move. According to the latest Bank of Canada Financial Stability Review, nearly 22% of Canadian mortgages are highly levered, with a loan-to-value ratio greater than 450%, a greater share of such mortgages than during the 2016/17 housing boom (Chart II-29). Canadian house prices have risen to such an extent that home prices in major cities like Toronto, Vancouver and Montreal are among the most expensive in North America.4  Stunningly, a recent Bloomberg Nanos opinion poll revealed that nearly 50% of Canadians would support Bank of Canada rate hikes to cool off the red-hot housing market (Chart II-30). The central bank will be unable to resist the pressure to use monetary policy to slam on the brakes of the housing market – investors should expect more tapering and, eventually, rate hikes from the Bank of Canada over at least the next couple of years. Chart II-29Canadians Are Leveraging Up To Buy Expensive Homes Chart II-3050% Of Canadians Want A Rate Hike To Cool Housing   In New Zealand, worsening housing affordability has reached a point where a 20% down payment on the median national house price is equal to 223% of median disposable income (Chart II-31). This is forcing more first-time home buyers to take on levels of mortgage debt that the RBNZ deems highly risky (top panel). Like the Bank of Canada, the RBNZ will prove to be one of the most hawkish central banks in the developed world over the next couple of years as the central bank follows their newly-revised remit to try and cool off housing demand in New Zealand. Who is next? Housing values, measured by the ratio of median national house prices to median national household incomes, are rising in the US and UK but are still below the peaks of the mid-2000s housing bubble (Chart II-32). Meanwhile, housing is becoming more expensive across the euro area, but not in a consistent manner, with valuations in Germany and Spain having increased far more than in France or Italy. Housing valuations have actually improved in Australia over the past couple of years on a price-to-income basis. The most likely candidates for a housing-related hawkish turn are in Scandinavia, with housing valuations in Sweden and Norway closing in on Canada/New Zealand levels. Chart II-31New Zealand Housing Is Wildly Unaffordable Chart II-32Global House Price/Income Ratios Are Trending Higher   Investment Conclusions The current acceleration in global house prices is an inevitable outcome of the extraordinary monetary and fiscal easing implemented during the pandemic. Higher realized inflation is pushing real rates deeper into negative territory in many countries, fueling the demand for housing. Central banks in countries with more stretched housing valuations will be forced to turn more hawkish sooner than expected, leading to tapering and, eventually, rate hikes to cool housing demand. This has negative implications for government bond markets in countries where housing is more expensive and real yields remain too low, like Canada, New Zealand and Sweden (Chart II-33). Investors should limit exposure to government bonds in those markets over the next 6-12 months. Chart II-33Negative Real Yields & Expensive Housing Valuations – An Unsustainable Mix Bond markets in countries where house prices are not rising rapidly enough to force policymakers to turn more hawkish more quickly – like core Europe, Australia and even Japan - are likely to be relative outperformers. The US and UK are “cuspy” bond markets, as housing valuations are becoming more expensive in those two countries but the Fed and Bank of England are not facing the same domestic political pressure to use monetary policy tools to fight the growing unaffordability of housing. That could change, though, if overall household leverage begins to rise alongside house price inflation as the US and UK economies emerge from the pandemic. Current pricing in OIS curves shows that markets expect the RBNZ and Bank of Canada to begin hiking rates in May 2022 and September 2022, respectively (Table II-1). This is well ahead of expectations for “liftoff” from other developed markets central banks, including the Fed in April 2023. The cumulative amount of rate hikes following liftoff to the end of 2024 is highest in Canada, New Zealand, the US and Australia. Those are also countries with currencies that are trading at or above the purchasing power parity levels derived from our currency strategists’ valuation models. This highlights the difficult choice that central bankers facing housing bubbles must confront, as the rate hikes that will help cool off housing demand will lead to currency appreciation that could impact other parts of their economies like exports and manufacturing. Table II-1Hawkish Central Banks Must Live With Currency Strength Tracking the second-round economic consequences of eventual monetary policy actions to control excessive house price inflation, particularly in “higher risk” countries, is likely to be the subject of future Bank Credit Analyst / Global Fixed Income Strategy reports. Jonathan LaBerge, CFA Vice President The Bank Credit Analyst Robert Robis, CFA Chief Fixed Income Strategist Footnotes 1 Please see Global Investment Strategy "Canada: A (Probably) Happy Moment In An Otherwise Sad Story," dated July 14, 2017, available at gis.bcaresearch.com 2 Importantly, the BIS debt service ratios include the payment of both principal and interest, thus making it a true measure of debt service costs that includes repayment of borrowed funds – a critical issue in countries with high loan-to-value ratios for home mortgages. 3 Please see page 46 of Chapter 2 of the April 2021 IMF Global Financial Stability Report, which can be found here: https://www.imf.org/en/Publications/GFSR/Issues/2021/04/06/global-finan… 4 “Vancouver, Toronto and Hamilton are the least affordable cities in North America: report”, CBC News, May 20, 2021

Neutral In this Tuesday’s Strategy Report we closed our overweight financials call and moved this GICS1 sector to neutral from previously overweight capitalizing 20% in relative gains, since last November’s inception. This move is a hedge to our rising inflation view, and we would rather stick to overweighting energy and industrials as ways to express our inflation protection theme as opposed to maintaining an above benchmark allocation in financials. There are some warning signs for the sector as well. The Fed’s easing cycle has reached a zenith and, at the margin, this will weigh on relative financials profitability (bottom panel). The shadow fed funds rate (courtesy of Leo Krippner1) has also troughed and is closing in on the zero line (middle panel). Finally, using the 10-year/shadow fed funds rate yield curve also signals that the yield curve may have peaked already, at least for this early part of the business cycle (top panel). Bottom Line: We downgraded the S&P financials sector to neutral in yesterday’s Strategy Report and pocketed gains to the tune of 20%, since inception.   Footnotes 1https://www.ljkmfa.com/test-test/international-ssrs/

Special Report

Highlights We update our assumptions for the likely 10-15 year return for a wide range of different asset classes. Our methodology is basically unchanged from our last Return Assumptions report published in 2019, though we have refined our analysis and use of data in some areas. Returns over the next decade will be very low compared to history. We project that a standard global portfolio (50% equities, 30% bonds, and 20% alternatives) will return only 3.0% a year in nominal terms. That compares to a historic return of 6.3%. There are still some assets that will produce better returns, most notably small caps (4.9% a year in the US) and alternatives (6.2% for private equity, for example). But they also carry higher risk. Spreadsheets are available with detailed data. Introduction This is the third edition of our work on return assumptions. Since publishing the previous reports in November 2017 and June 2019, we have had many opportunities to discuss our methodologies with clients and in the Global Asset Allocation course at the BCA Academy. This has allowed us to test and, in many cases, refine our approach. We believe the methodologies we use have stood the test of time. We have always emphasized that this sort of capital markets assumptions (CMA) analysis is an art, not a precise science. We continue to prefer to project returns over a somewhat undefined 10-15 year period, since this allows us to think about the underlying trend of likely returns. Many other CMA papers use five (or even three) year time horizons which, in our view, are problematical since they rely heavily on a forecast of the timing, length, and severity of the next recession. Our approach is based on the concept that the return on the risk-free long-term government bond is the cornerstone to projecting asset returns, and that this return is rather predictable: It is approximately the current yield. Most other asset returns can be built up from that – the return on high-yield bonds, for example, by assuming that their historic spread over government bonds, and default and recovery rates will continue in the future. For equities, we continue to use six different methodologies, which are based on a mixture of valuation and projected earnings growth. This approach – that assumed returns can be built up from a combination of current yield plus forecast future growth in capital values – also works for most alternative asset classes, for example real estate. We have made a few minor changes to our methodology in this edition. We have, for example, made our use of historical data (for spreads, profit margins, growth relative to GDP, etc.) more consistent, using the 20-year average where possible. The biggest change this time is that clients can download here a spreadsheet with all the data in this report in order, for example, to use the data as inputs into their own optimizers. In addition, we have set up our detailed spreadsheet to allow clients to see the underlying inputs, the formulae behind our methodologies, and to input their own assumptions. This will also allow us to update the results of our analysis as often as needed. Please let us know here if you would like more details about this additional service. This Special Report is structured as follows. First, we analyze the overall results: What is the probable return from each asset class over the next 10-15 years, and how do these differ from historical returns. Next, we describe in detail the methodologies we use, for (1) economic growth, (2) fixed-income instruments, (3) equities, and (4) 12 different alternative asset classes. Then, we describe our way of forecasting currency returns, and show the return assumptions in different base currencies. Finally, we update the numbers for volatility and correlations, which many investors need as inputs into optimization programs. The summary of our results is shown in Table 1. The results are all average annual nominal total returns, in local currency terms (except for global indexes, which are in US dollars). The data is updated to end-April 2021 (except for some alternative asset classes where only quarterly data is available). Table 1BCA Assumed Returns Overall Results Returns over the coming decade are likely to be very disappointing compared to history. Our assumptions suggest a typical global portfolio, consisting of 50% large-cap equities, 30% bonds, and 20% alternatives, will produce an annual nominal return of only 3.0%, compared to an average of 6.3% over the past 20 years. A US-only portfolio with a similar composition is likely to produce only a 3.1% return, compared to 7% in history. The reason is simple: Valuations currently are very stretched in almost every asset class. The risk-free rate (the 10-year government bond yield) in the US is 1.6% (compared to a 20-year average of 3.1%). It is negative in the euro area (in nominal terms) and zero in Japan. These rates are the anchor for the returns of all other asset classes, which are theoretically priced off the risk-free rate plus a risk premium. We have long argued that valuations are not a good timing tool for investors. An asset can remain very expensive or very cheap for a considerable period. But all the evidence shows that the valuation at the starting point is a very powerful indicator of long-run returns. The yield on government bonds, for example, has a strong correlation with their 10-year return (Chart 1). In the equity market, the Shiller PE has historically had little correlation with the return over one or two years, but has a 90% correlation with the return over the subsequent 10 years (Chart 2). Chart 1Starting Yield Determines Bond Returns Chart 2Valuation Drive Long-Run Equtiy Returns     With valuations in equity markets now expensive relative to history (for example, forward PE for US stocks of 22x compared to a 20-year average of 16x, and 18x in the euro zone compared to 13x), investors should expect that equity market returns will be low relative to history. Our assumptions point to a 2.6% annual return from US stocks, 2.3% from the euro zone, and 1.6% from Japan (compared to 8.5%, 3.9%, and 3.5% over the past 20 years). Our assumptions are significantly lower than when we last published our analysis in 2019; then we projected 5.6% for US stocks, 4.7% for the euro zone, and 6.2% for Japan. The difference is that equity multiples have risen and risk-free rates have fallen significantly since then. So what should investors do? They have only two choices: Lower their return assumptions, or increase their weightings in riskier asset classes. Chart 3Hard To See How US Pension Funds Will Achieve Their Targets The average US public pension fund (Chart 3) still assumes a return of 7% a year, and private pension funds’ assumption is not much lower. And yet corporate pension funds have been pushed by their consultants in recent years to increase their weighting in bonds, to more closely match their liabilities (Chart 4). It is almost mathematically impossible to achieve their targets with that sort of portfolio. In other countries, such as Australia or Canada, pension funds’ return targets are typically inflation or cash plus 3-4 percentage points. But even those targets are challenging.   Chart 4...Especially With Over 50% In Bonds There are asset classes which will produce higher returns. For example, we project a return of 4.9% from US small-cap stocks – and 9.7% from UK small caps. US high-yield bonds should produce a return of 3.2% a year (even after defaults) and Emerging Markets local currency sovereign debt 2.7% (in USD terms) – not exactly exciting, but at least a pick-up over other fixed-income securities. The projected returns from illiquid alternative assets continue to look relatively attractive. An equal-weighted portfolio of the 12 alternatives we cover is projected to return 5.7% a year, not much lower than the forecast of 6.1% from our 2019 report (and compared to an average of 7.1% of the past 20 years). There are some alt assets where returns have started to trend down: Private equity, for instance, is projected to return 6.2% a year, compared to 11.1% in history, and hedge funds 4.5%, compared to 5.9%. But the illiquidity premium should not disappear completely, even if the move of alternative investments to become more mainstream has reduced it to a degree. So adding more risky assets to a portfolio is an answer, at least for those investors with a long enough time-horizon that allows them to bear the inevitable big drawdowns that come with having a more volatile portfolio. And, unfortunately, lower returns mean that the incremental return gained for each unit of risk taken has declined compared to the past 10 or 20 years (Chart 5) – the efficient frontier has flattened significantly. Chart 5You Need To Take More Risk To Produce Return How We Came Up With The Assumptions GDP Growth Several of our methodologies use assumptions (for example, in equity methods (2) and (3), based on projections of earnings growth, real-estate capital-value growth, and commodities prices) which require estimates of nominal GDP growth in each country and region. To make these forecasts, we assume that nominal GDP growth can be decomposed into: (1) growth of the working-age population, (2) productivity growth, and (3) inflation. This ignores capital intensity, but it has been relatively stable over history and is difficult to forecast. Table 2 shows the assumptions we use, and our forecasts for real and nominal GDP in each country and region. Table 2Calculations Of Trend GDP Growth For population growth we use the United Nations’ median forecast of annual growth in the population aged 25-54 between 2020 and 2040. This ranges from -1% in Japan to +1% in Emerging Markets – although note that the range of forecast population growth in EM varies widely from 1.2% in India to -1.1% in Korea (and in China, too, is negative at -0.7%). This estimate is reasonably reliable, although it does miss some possible factors, such as changes in the female participation rate, hours worked, and changing openness to immigration. Productivity is much harder to forecast. Over the past 10 to 20 years, productivity growth has trended down in most countries (Charts 6A & B). We take a slightly more optimistic view, assuming that productivity growth over the next 10-15 years will equal the 20-year average. We base this on the belief that part of the decline in productivity since the Global Financial Crisis is due to cyclical reasons which are now dissipating, and also to expectations that new technologies coming through (artificial intelligence, big data, automation, robotics etc) will boost productivity in the coming years. Others take a more pessimistic view. The Congressional Budget Office’s forecast of trend real US GDP growth in 2022-2031 of 1.8%, for example, is lower than our estimate of 2.2% mainly because of its more cautious estimate of productivity growth. Chart 6AProductivity Growth (I) Chart 6BProductivity Growth (II)   To derive nominal GDP growth, we assume that inflation over the next 10 years will be on average the same as over the past 20 years, for example 2% in the US, 1.6% in the euro area, 0.1% in Japan, and 3.9% in Emerging Markets (using a weighted average of EM by equity market cap). This estimate, too, has a high degree of uncertainty. One could imagine a scenario whereby inflation picks up significantly over the next decade due to excessively easy monetary policy, overly generous fiscal spending, growth in protectionism, rising labor pressure for wage increases, and the effects of a rising dependency ratio (the ratio of non-working people, especially retirees, to total population).1 But another scenario of continued “secular stagnation” and disinflation, caused by automation-driven job losses and a chronic lack of aggregate demand, is also conceivable. We think our middle-path forecast is the most sensible one to use in projecting likely asset returns, but investors might also want to plan based on these alternative scenarios too. Note that for Emerging Markets, we continue to show two different scenarios, which vary according to different projections of productivity growth. EM productivity growth has been declining steadily since around 2010, and in all major emerging economies, not just China. Our first scenario assumes that this decline ends and that, as in our assumption for developed economies, productivity growth reverts to the 20-year average. The more pessimistic (and, in our view, more likely) scenario assumes that the deterioration in productivity continues and that in 10 years’ time, EM productivity is the same as the average of developed economies. Which scenario will be correct depends on whether emerging economies, not least China, are able to implement structural reforms over the next decade, for example liberalizing the labor market, allowing a greater role for the private sector, improving corporate governance, and institutionalizing more orthodox fiscal and particularly monetary policy. Fixed Income Our anchor for calculating assumed returns is the return on long-term risk-free assets, specifically the 10-year government bond in the strongest countries. It is a reasonable assumption that an investor who buys, for example, a 10-year Treasury bond today and holds it for 10 years will make 1.6% a year in nominal US dollar terms. While this is not perfectly mathematically correct (since it ignores reinvested interest payments, for instance), empirically the return on government bonds has been very closely linked to the yield at the start-point in history (see Chart 1). From this starting-point in each country, we can easily build up the return for other fixed-income assets. These assumptions and the results are shown in Table 3. Table 3Fixed-Income Return Calculations Government bonds in most countries have an average duration of less than 10 years. Over the past five years, in the US it has averaged 6.4 years, and in the euro area 8.0 years. Only in the UK is the average over 10 years: 12.4 years to be precise. To calculate the return from the government bond index for each country we therefore assume that the shape of the yield curve (using the spread between 7-year and 10-year bonds) in future will be the same as the historic 20-year average. Cash. We assume that over the next 10 years the yield on cash will gradually revert to an equilibrium level. We calculate a market-implied real long-term neutral rate from the 10-year historical average of 5-year/5-year OIS implied forwards deflated by the 5-year/5-year implied CPI swap rate. This is a change from the methodology we used in 2019, when we based this off the neutral rate, r*, as calculated by the Holston Laubach-Williams model. But the New York Fed has temporarily stopped updating its calculation of this due to pandemic-induced volatility in the data, and anyway it was not available for every country. We turn the real cash rate into a total nominal return using our assumption for inflation described in detail in the GDP section above, the 20-year historical average of CPI. For inflation-linked securities, such as TIPS, we take the average yield over the past 10 years (a 20-year average was not available in many markets) and add the assumption for inflation described above. Corporate credit. We assume that spreads, and default and recovery rates, while highly volatile over the cycle, remain stable in the long run (Chart 7). We use 20-year averages for these, except that data for investment-grade default rates in Japan, the UK, Canada, and Australia are not available and so we use the average of the US and the euro zone. High-yield default rates are not available for the UK either, and so we do the same. Other bonds. For government-related debt (which is a big part of some bond indexes, 28% in the US for example) we assume that the 20-year historical average of the option-adjusted spread over government bonds will apply in the future too. We use the same methodology for securitized debt (for example, mortgage- and asset-based bonds): The 20-year average spread over the return on government bonds. Emerging Market debt. The assumptions and results for the three categories of EM debt (US dollar sovereign debt, US dollar corporate debt, and local currency sovereign debt) are shown in Table 4. We here assume that the 20-year average historical spread will continue in future. Default and recovery rates are a little harder to calculate, due to a lack of data. For USD sovereign debt (where defaults are rare and so hard to project), we use the rating-based default rate, calculated by Aswath Damodaran of NYU Stern School of Business.2 For USD-denominated EM corporate debt, we use the historical average, calculated by Moody's 2.5%.3 For local-currency debt, we use the same rating-based default rate as for USD sovereign debt. To translate the return into hard currency, we assume that currencies will move in line with the inflation differential between Emerging Markets and the US. For EM inflation we use an average of the IMF’s inflation forecasts for the nine largest emerging markets weighted by their weights in the J.P. Morgan GBI-EM Global Diversified local government bond index, and compare this to our US inflation forecast. This produces an EM inflation forecast of 2.9% a year, compared to 2.2% for the US, thus lowering the USD-based return from local EM debt by 0.7 percentage point. (See a more detailed discussion of forecasting long-term EM currency changes in the Currency section below). Index returns. Table 3 also shows the assumed return for the Bloomberg Barclays bond index for each country and for the global bond index, based on a weighted average of our assumption for each fixed-income asset class and country. Chart 7ACredit Spreads & Default Rates (I) Chart 7BCredit Spreads & Default Rates (II)   Table 4Emerging Market Debt   Equities The assumptions and detailed results for seven different equity markets are shown in Table 5. We have not made any substantial changes to our methodology for equities. We continue to use the average of six different methods to calculate the probable equity returns over the next 10-15 years. These are: Equity Risk Premium (ERP). The return from equities equals the yield on government bonds (we use 10-year bonds) plus an equity risk premium. For the US, we use an equity risk premium of 3.5%. This is based on work by Dimson, Marsh and Staunton4 showing that this is approximately the average excess return of equities over bonds in developed economies since 1900. We scale the equity risk premium for other countries using their average beta to the US market over the past 10 years. This varies from 0.66 for Japan (giving an ERP of 2.3%) and 1.2 in the euro area (ERP is 4.2%). Growth model. Here we assume that the return from equities equals the current dividend yield plus dividend growth. We need to adjust the dividend yield, however, to take into account that in some countries, particularly the US, it is more tax efficient for companies to do buybacks than to pay out dividends. We do this by adding equity withdrawals to the dividend yield. But this needs to be done on a net basis (taking into account equity issuance). We calculate this using the average annual change in the index divisor over the past 10 years. For the US, this is -0.8%, meaning there are more buybacks than new share issues. But in all other regions, the number is positive, and as high as 5.9% a year for Emerging Markets. This dilution is something that many calculations of assumed equity returns miss. For dividend growth, we assume that the dividend payout ratio remains stable, and that earnings growth is correlated with nominal GDP growth. However, history shows that earnings grow more slowly than GDP (logically so, when you consider that companies usually grow fastest before they list on a stock exchange). So we deduct 1% from nominal GDP growth to derive our earnings growth assumption. Note that for Emerging Markets, we use two different measures of dividend growth, depending on future productivity growth, as detailed above in our explanation of the GDP projections. Growth model (with reversion to mean). To take into account that valuations and profit margins typically revert to mean over the long run, we adjust the standard growth model (No. 2 above) by assuming that the current 12-month forward PE ratio and forward net profit margin for each country gradually revert over the next 10 years to their 20-year average. In the US, for example, that would mean that the current 12-month forward PE of 22.5x falls back to 16.0x, and profit margin of 12.5% falls to 10.7%. In every country and region, the profit margin is currently above the long-run average, and in all except the UK the PE is too. Note that we have changed from using the trailing PE and margin, because to use these now would be misleading given the big pandemic-driven decline in profits in 2020. Earnings yield. An intrinsically intuitive (and empirically demonstrable) way of estimating future returns is to use the earnings yield. This is based on the idea that an investor’s return from owning a stock comes either from the company paying a dividend, or from it investing retained earnings and paying a dividend in future. In the US, for example, a forward PE of 22.5x translates into an earnings yield of 4.4%. Again, here we switched this time to using 12-month forward forecast earnings yield, rather the trailing. Shiller PE. There is a strong correlation between valuation at the starting-point and the subsequent return from equities, at least over the long-run, although not over a period of less than 3-5 years (Chart 2). We regressed the Shiller PE (current price divided by average real earnings over the past 10 years) against the return from equities over the subsequent 10 years for each country and region. Composite valuation metric. The Shiller PE has its detractors. Using a fixed 10-year period does not reflect the different lengths of recessions and bull markets. It may say more about the mean-reverting nature of earnings than about whether the current price level is too high. So we also use the BCA Compositive Valuation Metric, which comprises eight indicators including, besides standard valuation measures such as price/sales and price/book, more esoteric ones such as market cap/GDP and Tobin’s Q. Again, we regress the metric against the subsequent 10-year return. Table 5Equity Return Calculations Alternative Assets Real Estate & REITs. We use the same basic methodology for both: The current yield (cap rate or dividend yield) plus projected capital value appreciation (linked to GDP growth). For US direct real estate, for example, we use the simple average cap rate of the five categories of commercial real estate (CRE), apartments, office, retail, industrial, and hotels in major cities: 6.1%. We also use the simple average of available city and category data for other countries. Cap rates are notoriously hard to estimate precisely; our data include a range of real estate, not just prime locations. We assume that capital values will grow in line with nominal GDP growth (using the same assumptions for this as we used for equities, 4.2%). We then deduct 0.5% for maintenance. This produces an expected return of 9.8% for the US. The only difference for REITs is that we do not deduct maintenance since this should already be reflected in the dividend yield. US REITs have a dividend yield currently of 3.5%, which produces an assumed return of 7.7% (Table 6). One risk with this methodology is that in the post-pandemic world, work and life practices might change. This will hurt office and residential real estate in major cities (which are overrepresented in investible CRE), though smaller cities and rural areas might benefit. As a result, capital values might fall. Table 6Alternatives Return Calculations Farmland & Timberland. Our methodology is similar to that for real estate: Current yield plus projected growth in capital values. For farmland, we use the farmland renter yield, sourced from the US Department of Agriculture. To estimate future land values, we take the gap between land value growth over the past 40 years (3.7%) and nominal growth of world GDP over that time (5.2%), assume that gap will continue and so deduct it from our estimate of global nominal GDP growth going forward (3.6%). This gives a result of 6.5%. For timberland, we assume that annualized returns in the future are the same as over the past 20 years. This produces a return assumption of 5.7%, which is (logically) moderately lower than our assumed return for farmland. Private Equity & Venture Capital. We project the return for private equity (PE) using the 30-year time-weighted average of the three-year rolling annualized return of PE over US large-cap equities, 3.6% (Chart 8). This produces an assumed return of 6.2%. For venture capital (VC), we use the same historical average for VC over PE (0.4%) to arrive at an assumed return of 6.6%. Hedge Funds. We use the 20-year time-weighted return of the Hedge Fund Composite Index over cash, 3.5% (Chart 9). This projects a future annual nominal return of 4.5%. Commodities. We previously used a methodology based on the idea that commodities’ bear markets in history have been rather fairly consistent, lasting on average 17 years, with an average decline of 50%, and that the current bear market began in 2012 (Chart 10). However, there are arguments that a new “commodities super-cycle” may be starting, driven by government infrastructure spending, and investment in alternative energy.5 We are agnostic for now on whether that will be the case, but it makes sense to switch to a neutral methodology, more in line with what we use for other assets classes: The return from commodities relative to GDP over the long run. Specifically, the CRB Raw Industrials Index has risen by an annualized 1.6% since 1951, during which time US nominal GDP growth averaged 6% (Chart 11). We assume that the differential will continue in future (although we calculate growth using global, not US, GDP), giving an annual return from commodities over the next 10-15 years of -0.9%. Gold. We calculate this using a regression of the gold price against nominal GDP growth and the annual change in the real 10-year yield over the past 40 years. For the forward-looking return assumption, we use a forecast of real rates (based on the equilibrium cash rate plus the average historical spread between the 10-year yield and cash) and a forecast of global nominal GDP growth. This produces an assumed return of 3.8%. Structured products. This asset class consists mainly of mortgage-backed and other asset-backed securitized instruments. In the US, these have historically returned 0.6% over US Treasurys. We assume that this premium continues, producing a total future return of 1.1% a year. Chart 8Private Equity Premium Chart 9Hedge Fund Return Over Cash     Chart 10Commodity Prices In History Chart 11Commodity Prices Vs. GDP Growth     Currencies Chart 12Currencies Tend To Revert To PPP To translate our local currency returns into an investor’s base currency, we need to arrive at some projections for FX movements over the next decade. Fortunately, for developed market currencies at least, it is relatively straightforward to use purchasing power parities (PPP) to do this since, over the long run, all the major currencies have tended to revert to PPP (Chart 12). We assume that in 10 years’ time all currencies will trade at PPP. We use the IMF’s estimate of today’s PPP for each currency to calculate the current under- or over-valuation. We assume that PPP will change in future years according to the relative inflation between each country and the US. The IMF provides five-year inflation forecasts and we assume that inflation will continue at this rate until 2031. For the euro zone, we calculate the PPP of the euro using the GDP-weighted PPPs of the five largest economies. The results (Table 7) suggest that the US dollar is currently overvalued and, given the forecast of higher inflation in the US than elsewhere in the future, will depreciate significantly against all major currencies except the Australian dollar. The USD is projected to depreciate by 1.7% a year against the euro and 1.1% against the yen over the next 10 years. It is likely to appreciate by 1.3% a year against the AUD, however. Table 7Currency Return Calculations Emerging Markets (Table 8) are more complicated. There is no evidence that EM currencies move towards PPP over time. All the major EM currencies are currently very cheap versus PPP (varying from 34% undervalued for the Chinese yuan to 67% for the Indonesian rupiah) but they were 10 years ago, too, and have not significantly moved towards PPP over that time. Table 8EM Currencies To calculate likely EM currency moves against the USD, therefore, we carry out a regression of the nine largest EM currencies against their relative CPI inflation rate to US inflation in history. We assume an intercept of zero. The regression coefficients vary from +0.5 for China to -1.7 for Malaysia. Apart from China, Malaysia, Poland and South Africa, the coefficients were negative, meaning that historically the USD has strengthened against the EM currency at least partly in line with relative inflation. To calculate likely future currency movements, we use the IMF’s five-year inflation forecasts and assume that the same rate of inflation will continue for our whole projection period. This methodology points to moderate annual depreciation of most EM currencies against the USD, varying from 0.8% a year for the Russian ruble to 0.1% for the Indonesia rupiah. The Chinese yuan and Taiwanese dollar are projected to appreciate moderately. We calculate the average EM currency movement using the weights of these nine large economies in the EM J.P. Morgan GBI-EM Global Diversified local-currency sovereign bond index. This produces a small (0.1%) a year appreciation. However, the IMF’s EM inflation forecasts may be too optimistic. It forecasts, for example, that Brazilian inflation will be only 3.3% a year in future, compared to an average of 6.1% over the past 20 years, and Russian inflation 4.0% versus a historical average of 9.3%. This suggests that EM currency performance could be worse than our projections. Table 9 shows the returns for the major asset classes expressed in local currency terms for six base currencies, based on the calculations explained above. Table 9Returns In Different Base Currencies Correlation And Volatility Below, in Table 10, we provide correlations for clients who need these inputs for their optimization calculations. Table 10Long-Run Correlation Matrix Returns can be calculated using the sort of forward-looking methodologies we have described above. For volatility, we think it is reasonable to use historical average data (Table 1, far right column), since volatility does not tend to trend over the long run (Chart 13). But correlation is a different matter. Correlations have varied significantly in history due to structural changes or regime shifts. The correlation of equities to bonds, it is well known, has moved from positive in the 1980s and 1990s, to negative since 2000 – probably because inflation disappeared as a factor moving bond prices (Chart 14). The correlation between equity market has risen as a result of the globalization of investment flows, though note that it fell back in 2010-2019. Chart 13Volatility Is Fairly Stable In The Long Run Chart 14Correlations Are Not Stable   So what correlations should investors use in an optimizer? Our recommendation would be to use the longest period of history available. A US investor, for example, might take the average correlation between Treasury bonds and large-cap US equities since 1945, 0.1%. Table 10 shows the correlation since 1973 of all the major asset classes for which data is available. Unfortunately, this misses some important asset classes such as high-yield bonds and Emerging Market equities, whose history does not go back that far. The results are intuitive – and prudent. From these numbers, it would seem sensible to use an assumption of a small positive correlation between US Treasurys and US equities, for example. US investment-grade debt has a correlation of 0.4 against equities. Global equity markets are all fairly highly correlated to each other, ranging mostly from 0.4 to 0.7. The most non-correlated asset class is commodities, especially gold.   Garry Evans, Senior Vice President Global Asset Allocation garry@bcaresearch.com   Amr Hanafy, Senior Analyst Global Asset Allocation amrh@bcaresearch.com   Footnotes 1 These are themes that BCA Research has been writing about for several years. See, for example, please see Global Investment Strategy, "1970s-Style Inflation: Could It Happen Again? (Part 1)," dated August 10, 2018; and " 1970s-Style Inflation: Could It Happen Again? (Part 2)," dated August 24, 2018. 2 Please see http://pages.stern.nyu.edu/~adamodar/New_Home_Page/datafile/ctryprem.html 3 Annual Emerging Markets Default Study: Coronavirus Will Push Up Default Rates https://www.moodys.com/researchdocumentcontentpage.aspx?docid=PBC_1214906 4 Please see, for example, https://www.credit-suisse.com/media/assets/corporate/docs/about-us/research/publications/credit-suisse-global-investment-returns-yearbook-2021-summary-edition.pdf. 5 Please see Commodity & Energy Strategy, "Industrial Commodities Super-Cycle Or Bull Market?", dated March 4, 2021.

Highlights The Seventh National Population Census highlights the seriousness of China’s demographic deterioration; apart from a shrinking working-age population, the nation’s fertility and birth rates have dropped meaningfully. China’s urbanization rate will likely slow in the second half of this decade. The country’s urban population growth is only slightly positive, while the rural population is declining and aging. Demand for housing will experience a structural downshift, particularly in less developed regions.  Competition for labor will become fiercer among regions and sectors, and wage growth will continue to accelerate. However, the manufacturing sector will remain competitive regardless of wage inflation, thanks to the rising quality of China’s labor force and innovation. Interest rates will structurally shift to a lower range, providing some tailwind to Chinese equities and government bonds. Feature The Seventh Population Census, conducted by the National Bureau of Statistics every 10 years, reinforced the magnitude of China’s demographic challenge. The nation’s population is not only aging but is set to start shrinking due to extremely low birth and fertility rates. The main implication is that China’s urbanization rate will slow and property market will likely encounter a structural downshift, tied to declining demand from both its working-age (age 15 to 64) and total population. Demand for housing will increasingly concentrate in top-tier cities because these metropolitan areas have more advantages attracting labor. Secondly, manufacturing will likely maintain its share of GDP, despite China’s push for consumption and growth in the service sector. Importantly, interest rates will continue to shift downward along with a decelerating potential growth; waning interest rates will create a tailwind to China’s capital market in the long term.  Highlights From The Census The Census showed three meaningful shifts in China’s demographics in the past decade:  1.  China is getting old before getting rich. China is experiencing a worse demographic transition than Japan in the early 1990s, with a lower level of per capita wealth than Japan attained when its working-age population peaked (Chart 1). Over the past ten years China’s population has only expanded by 5.4%, the lowest rate since the first census in 1953. Moreover, the country’s oldest cohort rose from 8.9% in 2010 to 13.5% and the working-age population is falling more quickly than in Japan. China’s working-age population peaked in 2010 and then fell by 6.79 percentage points in the next 10 years. In contrast, Japan’s working-age population peaked in 1992 and fell by 2.18 percentage points in the subsequent decade (Chart 1, top panel). 2.  China’s total population is set to start declining in five years. Some demographers project that China’s total population will peak in 2027,1 but a high-level Chinese official recently predicted that the country’s population will start to trend down as early as in 2025.2 The relaxation of the one-child policy in 2015 helped to lift the birthrate (births per 1,000 people) briefly in 2016, before falling sharply again in 2017. The population’s natural growth rate, calculated as birthrate minus deathrate, is rapidly approaching zero (Chart 2). Chart 1China's Working Population Falling Faster Than Japan's In 1990s Chart 2China's Population Growth Will Turn Negative In Mid-2020s The birthrate is the main determinant of the population’s natural growth rate given that China’s deathrate has been steady for decades.  If the birthrate continues to fall at the current rate, then China will undoubtedly reach a population turning point and will join nations such as Japan, Germany and South Korea, which have negative population growth.  3.  A low fertility trap. Chart 3China's Alarmingly Low Fertility Rate Is Set To Decline Even Further... China’s extremely low fertility rate3 is a major contributor to its falling birthrate.  The current 1.3 reading is less than in many developed countries, such as Japan with 1.4 and the US with 1.6, and it is far below the fertility rate of 2.1 needed to stabilize a population, according to the United Nations (Chart 3). China’s fertility rate is set to dive even further in the coming years due to structural factors such as a dwindling number of childbearing-age women linked to the one-child policy implemented in the 1980s (Chart 4). China’s high female labor participation rate and low propensity among young people to get married, and the high cost of raising children in urban areas, all are long-standing socio-economic issues hindering the Chinese from having more babies (Chart 5). Chart 4…Due To Fewer Childbearing-Age Women And… Chart 5...Structural Issues That Curb Chinese Propensity To Produce Babies Bottom Line: These structural trends will take decades to reverse. China faces a dramatic plunge in its population in the very near future if the authorities do not enact significant and immediate policy changes.   Urbanization Pace Will Slow The Census indicates that rapid urbanization continued through 2020, with the rate hitting 64% of the population, up 14 percentage points from 2010. However, the headline number in the urbanization rate understates China’s progress in industrialization, i.e. the country’s rural-to-urban transition has entered a late stage and the current pace cannot be sustained in the future. Significantly, China’s underlying demographic shifts will likely lead to a passive increase in the urbanization rate in the second half of this decade. This trend will curb rather than boost demand in urban areas.  The experience of developed countries suggests that the pace of urbanization begins to slow when the rate reaches around 70% (Chart 6). Based on China’s current level, the country should reach the 70% threshold in just six to seven years. Meanwhile, China is much more industrialized than generally perceived: the country’s industrialization rate is currently 85%, which means that 85% of jobs in China are in non-agricultural sectors (Chart 7). Chart 6Urbanization Progress Stabilizes When Reaching 70% Chart 7China Is Much More Industrialized Than Commonly Believed Furthermore, a higher urbanization reading may be the result of negative natural population growth. Given that the urbanization rate is calculated as a percentage of urban population in the total population, a decline in the absolute level of total population (the denominator) could lead to a passive increase in the numerator. Chart 8Japan Has Had A "Passive" Increase In Urbanization Since 2012 For example, Japan’s urbanization rate rose significantly during the 2000s, and maintained an upward momentum even as its total population peaked in 2010. However, its urban population growth rate dropped dramatically and turned negative in 2012 – suggesting the increase in the urbanization rate is due to a shrinking total population instead of expanding urbanities (Chart 8). The rising deathrate of the rural elderly population is another important reason for the accelerated increase in Japan's urbanization rate. China’s urban population growth is on a sharp down trend, although it is still slightly positive (Chart 9). However, the rural population has shrunk and aged, which limits future migration from rural to urban areas (Chart 10).  China’s rural population has shrunk by almost half from its peak in 1995 to 2020. The share of the rural population 50 years and older doubled in the same period. Chart 9China's Urban Population Growth Is On The Decline... Chart 10...While Rural Population Has Shrunk And Aged Thus, China’s rural-to-urban migration has slowed in the past decade (the trend turned negative last year due to the pandemic). The number of new migrant workers moving from the country to the city tumbled from 12.5 million a year to 2.5 million, and the number of younger migrants (50 years and younger) has contracted since 2017 (Chart 11). Chart 11The Number Of Young Migrant Workers Started Contracting In 2017 Bottom Line: Country-to-city migration will be smaller going forward based on a diminishing rural population, an increasing number of elders and a reduced proportion of young people in rural areas. When China’s population peaks, which is highly likely by 2025, its urbanization progress will turn passive and the aggregate population growth in urban areas may also turn negative. Aggregate Housing Demand Will Dwindle The demographic shifts described above will impact the demand for properties and accentuate regional divergences in housing demand and prices.   Historically, changes in the working-age population led residential home sales by five to six years. Home sales have fluctuated in a downward trend in the past five years along with a peak in the working-age population in 2015 (Chart 12). Moreover, the sharp deterioration in China’s birthrate means that home sales will be significantly reduced in the next 15-20 years. Chart 12Aggregate Demand For Housing Will Dwindle Along With Smaller Labor Force Chart 13Population Is An Important Driver For Urban Development The regional divergence in the demand for housing will also widen. Population, especially the labor force, is an important driver for urban development and housing (Chart 13 above). Population migration mainly occurs among 15-59-year-olds, and this cohort is also the main homeowner group. As China’s labor force increasingly flocks to developed areas, the economic development of less developed areas will face greater challenges (Chart 14). Those areas will encounter a combination of declining birthrate and outflow of labor force. This demographic shift is already evident in many two- and third-tier cities where housing prices have lagged far behind the tier-one cities (Chart 15). Chart 14Less Developed Regions Have Seen Net Population Losses In The Past Decade… Chart 15...And Softening Housing Prices Bottom Line: The drop in China’s birthrate and working-age population will lead to less demand for housing. However, China’s first-tier cities (and core metropolitan areas) will likely continue to outperform third- and fourth-tier cities in terms of labor growth, consumption and home prices. Labor Measures And Manufacturing Competitiveness Labor shortages in selected sectors and upward pressure on wages will likely intensify in the coming decade. While labor quantity will decrease, the quality of China’s labor force will remain competitive. From an aggregate economy perspective, improving labor productivity and automation can help to offset the smaller number of workers (Chart 16). Following two decades of rapid expansion in the industrial sector, China’s labor shortages began to multiply when the country’s urbanization ratio rose to between 50% and 60%. Looking at Japan and Korea, for example, a shortage in manufacturing labor emerged when the countries’ manufacturing/agricultural employment ratio climbed above one. China’s employment ratio likely have crossed this threshold in the mid-2010s, coinciding with a rollover in its working-age population and a massive jump in wage growth (Chart 17). Chart 16Improving Labor Quality To Offset Smaller Labor Quantity Chart 17Manufacturing Labor Shortage And Wage Pressure Intensified In Mid-2010s The manufacturing and service sectors will continue to compete with agriculture for labor. The wage gap between urban and rural areas is disappearing and there are signs of labor market tightness in urban settings (Chart 18).  While the demand for labor has been flat, labor supply peaked in 2013/14 and has been on the wane since that time, which has resulted in an ascending demand-to-supply ratio in China’s urban labor market (Chart 19). Chart 18Wage Gap Between Urban And Rural Areas Is Disappearing Chart 19Urban Labor Supply Can't Keep Up With Demand The bright side is that China’s labor shortage and escalating wages have not eroded the competitiveness of its manufacturing sector. Impressive labor productivity gains and progressively improving labor quality have trumped higher input costs (Chart 20). Consistent with improved productivity, China’s share of global trade continues to build regardless of higher wages, a stronger currency, and import tariffs from the US (Chart 21). The manufacturing sector has gradually climbed the value-added chain in recent years and mounting wage pressures will likely push the corporate sector, particularly in more developed coastal regions, to move further away from a labor-intensive model. Chart 20Rising Wages But Stable Unit Labor Costs Chart 21Chinese Exporters Have Maintained Their Global Market Share Despite Higher Costs The 14th Five-Year Plan outlined policymakers’ decision to maintain the share of manufacturing in GDP, which is around 30%. Labor productivity in the manufacturing sector is notably higher than in the service sector. In an environment of shrinking labor, keeping workers in a high-productivity sector may be a better way to stabilize potential growth. Bottom Line: The competition for labor between sectors will intensify. Meanwhile, manufacturing’s share of China’s economy will likely be sustained in this decade, which will help to mitigate the speed of the deceleration in China’s growth.  Implications On Policy Setting Chart 22AInterest Rates Drop With Aging Population The combination of a weak fertility/birthrate and a decline in the working-age population will weigh on consumption and investment growth, bringing deflationary headwinds to the economy. China’s interest rate regime will likely follow its Asian neighbors to downshift structurally (Chart 22). Despite moderating potential economic growth, a low interest rate environment may be positive for China’s financial asset prices.  Chart 22BInterest Rates Drop With Aging Population Chart 22CInterest Rates Drop With Aging Population Chart 23Support Ratios Are Declining Globally One could argue that a falling support ratio – measured by the number of workers relative to consumers – can lead to inflation (Chart 23). This could happen to the US where baby boomers retire but continue to spend particularly on healthcare, while production falls along with the available workers. As production falls in relation to consumption, inflation could rise. However, this is not the case in China where both production and consumption will fall. Demand from an aging population may increase pockets of inflationary pressures, such as healthcare and elderly care, but it is unlikely to fully offset weakening demand from a declining working-age population and total population. In other words, both the numerator (workers) and denominator (consumers) will be falling in China. While a weakening demographic profile is negative for economic growth, lower prices on capital will make corporate debt-servicing cheaper. Further industrial consolidation aimed at supply-side reforms will also improve corporate profitability. Cheaper capital, improving productivity and efficiency could provide tailwinds to Chinese stocks and government bonds in the long run.   Jing Sima China Strategist jings@bcaresearch.com   Footnotes 1As of 2020, China’s total population is at 1411.78 million. 2"China faces an economic crisis as a population peak nears," South China Morning Post, April 18, 2021. 3The total fertility rate is based on the number of newborns by women in child-bearing years, which is ages 15-44 or 15-49 by international statistical standards.  Cyclical Investment Stance Equity Sector Recommendations

Highlights Portfolio Strategy The rising shadow fed funds rate and related flattening of the yield curve, eerie similarities with the 2009/10 episode, overbought technicals, and extended sector breadth, all signal that financials are due for a breather. Downgrade to neutral and lock in relative gains of 20% since inception. Early signs of housing related euphoria turning into consternation, lack of an overall bank credit impulse, relative share price overbought conditions, a looming increase in bank non-performing loans as government spending programs are set to expire in the autumn, will more than offset compelling bank valuations and rising interest rates. Trim the S&P banks index to underweight.   Recent Changes We trigger our downgrade alert and trim the S&P financials sector to neutral today cementing gains of 20% since inception. Downgrade the S&P banks index to underweight today. Table 1 Feature Following the 9/11 attacks, the great Alan Abelson of Barron’s “Up And Down Wall Street” column, eloquently wrote: “The market is a mechanism for allocating capital and, of course, making us all rich. What it most decidedly isn't is a forum for venting civic sentiment. To equate buying stock with patriotism or selling stock with a lack of patriotism is balderdash, the equivalent of praising or damning a thermometer for the temperature it records (emphasis ours).” This last part of the quote has been with me ever since, and is relevant today in the context of rising inflation, the related further bond market selloff and the equity market’s looming reaction to it. Currently, one cannot blame the stock market for not really caring about inflation as it is the equivalent of blaming mercury-in-glass for taking the temperature. However, the Fed’s tapering of asset purchases is coming later this fall and there will be a market shakeout before the SPX reaches a new equilibrium, likely 10% lower than current levels. Over the past few weeks we highlighted ten reasons to lighten up on equities and five technical reasons not to chase equities higher in the near-term. Today we reiterate our short-term cautiousness on the prospects of the stock market and below is a detailed reminder of our thesis. Fourteen months ago we penned a report titled “20 Reasons To Buy Equities” and now that the SPX is up 2,000 points since that trough, the risk/reward tradeoff is to the downside and we are compelled to book gains and raise some cash. On May 3 we upgraded health care to overweight and added some defensive exposure to our portfolio and last week we highlighted five technical reasons not to chase equities higher in the near term. What follows are 10 reasons to lighten up on stocks and therefore await a better entry point to deploy fresh capital later this summer: 1. The Fed and other developed global central banks’ easing has reached a peak. In fact, taper has started at the BoC and the BoE announced a quasi-taper, the ECB is rumored to commence decreasing asset purchases this summer and the Fed will likely taper by yearend (Chart 1). 2. US fiscal easing has also hit an apex and a large fiscal cliff looms in 2022 a mid-term election year (Chart 2). Chart 1Yellow… 3. The bulls have taken full control of the equity market and our Risk Appetite Indicator recently touched the four standard deviations line (Chart 2). 4. The ISM manufacturing survey peaked near 65 and the non-manufacturing hit an all-time high (Chart 2). Chart 2…Flags… 5. China’s is in a slowdown mode and BCA’s total social financing projections indicate a further deceleration in the back half of the year (Chart 1).  6. Equity market internals have been signaling trouble since February, warning that this bifurcated market is in desperate need of a breather (Chart 3). 7. The VIX in mid-April had a 15 handle for the first time since early last year, warning that investors are complacent (Chart 3). 8. Similarly, the junk bond option adjusted spread is at cyclical lows, and financial conditions are as good as they get probing all-time lows (Chart 2). 9. SPX profit growth is slated to jump 34% in calendar 2021, according to the latest I/B/E/S estimates with EPS on track to hit an all-time high level of $188 (Chart 3). 10. Finally, valuations remain lofty with the forward P/E ratio hovering near 21 an historically high level (Chart 3). Bottom Line: The easy money has been made since the March 23, 2020 trough when the SPX was 2,000 points lower. Our sense is that the next 10% move in the SPX is lower (close to 3,800) rather than higher and a healthy and much needed reset looms. Thus, we recommend investors book some gains, raise some dry powder and be prepared to deploy fresh capital later this summer. This week we take profits on an early cyclical sector and trim to neutral, and downgrade one of its key industry groups to underweight. Chart 3…Waving Don’t Overstate Your Welcome In Financials Last November, we boosted the S&P financials sector to overweight as soon as we could following the Pfizer/BioNTech COVID-19 vaccine efficacy news, and since then this interest rate-sensitive sector has bested the SPX by 20%. Our sense is that the easy money has been made on this position and today we recommend investors lock in profits and downgrade exposure to neutral. There are a few reasons why we are compelled to monetize our handsome gains accrued over the past six months. First, this is a hedge to our rising inflation view, and we would rather stick to overweighting energy and industrials as ways to express our inflation protection theme as opposed to maintaining an above benchmark allocation in financials. The second part of our inflation Special Report on May 10 also warns against hiding in financials during bouts of inflation, further cementing our view of booking these significant relative gains for our portfolio. Second, the Fed’s easing cycle has reached a zenith and at the margin this will weigh on relative financials profits (fed funds rate shown as a year-over-year change and on an inverted scale, bottom panel, Chart 4). The shadow fed funds rate (courtesy of Leo Krippner)1 has troughed and is closing in on the zero line (shadow fed funds rate shown inverted, middle panel, Chart 4). Using the 10-year/shadow fed funds rate yield curve also signals that the yield curve may have peaked already, at least for this early part of the business cycle (top panel, Chart 4). Chart 4Don’t Overstay Your Welcome Chart 5Gruesome Parallel Third, typically, financials explode right out of the gate following a recession and if we use 2009/10 as a close parallel then there are high odds that financials stocks are entering a rather gruesome period as far as relative returns are concerned. Chart 5 plots relative share prices and has aligned the November 2020 bottom with the March 2009 trough. Early in the year, we posited that the SPX was following the 2009/10 episode to the tee and if history at least rhymes, financials are also in for a rude awakening. Fourth, technicals are overbought and near a level that has marked previous easing off phases in relative share prices (second panel, Chart 6). Moreover, breadth is as good as it gets: not only are the number of financials subgroups trading higher than their 40-week moving average glued to the 100% ceiling, but also earnings breadth has nowhere to go but down (third & bottom panels, Chart 6). However, we refrain from turning outright bearish on this early-cyclical sector as valuations remain bombed out and provide a large enough cushion to absorb any shocks (Chart 7). Chart 6Overstretched… Chart 7…But Undervalued In sum, the rising shadow fed funds rate and related flattening of the yield curve, eerie similarities with the 2009/10 episode, overbought technicals, and extended sector breadth, all signal that financials are due for a breather. Bottom Line: We trigger our downgrade alert and crystalize gains in the S&P financials sector of 20% since inception and downgrade exposure to neutral, today. Shy Away From Banks We execute our downgrade in the S&P financials sector to neutral by trimming the S&P banks index to a below benchmark allocation. Investors can treat this downgrade as a hedge to our oil & gas exploration & production and rails overweights, as well as a hedge against a failure of inflation rising further in the coming months. Importantly, there are clear elements of cooling in the red-hot housing market. Housing starts and permits came off the boil last week and failed to live up to economists’ upbeat expectations. Lumber is getting clobbered and entered a bear market having first surged to five standard deviations above its five decade mean. Moreover, the latest news from the University of Michigan survey of consumers’ sentiment on buying conditions for houses (top panel, Chart 8) made for grim reading, signaling that a key bank loan category, mortgage credit, is in for a rough summer/fall season. Chart 8Is Housing Cresting? Tack on the nosedive in mortgage applications for purchasing a new home courtesy of rising mortgage rates, albeit from a low base, and factors are falling into place for an underperformance phase in banks (bottom panel, Chart 8). Were it only for housing related credit, we would overlook it as a single yellow flag. However, our credit impulse diffusion indicator – gauging the eight credit categories that the Fed tracks – is sinking like a stone, especially on a 13- and 52-week basis (Chart 9). Such broad based weakness warns that organic growth in bank profits (as opposed to buybacks) will be hard to come by in the coming quarters. Stimulus checks and a sharply rising fiscal deficit have served as a shot in the arm for consumers, businesses, landlords and banks, and have kept the economy going. However, as these liquidity taps dry out come autumn, it will be more difficult to continue to kick the proverbial can down the road. In other words, delinquency rates should tick higher and further infect non-performing loans (Chart 10). Granted, banks had provisioned aggressively last year and have been releasing reserves of late, but at the margin this will likely prove a net negative for their earnings.   Chart 9No Credit Pulse Chart 10NPLs On The Rise Two additional words of caution. First, cyclical momentum is as good as it gets for relative share prices. Banks have run too far too fast and a lot of the good news is already baked in as the middle panel of Chart 11 highlights. Second, while valuations remain bombed out, it is worrisome that banks have failed to make any real progress on narrowing the gap between ROE and P/B metrics since the GFC, unlike following the Savings & Loans and 9/11 catalyzed recessions (bottom panel, Chart 11). The implication is that banks are a value trap rather than a value opportunity. Finally, one key risk to our modestly bearish bank undertone, is the US 10-year Treasury yield. Relative bank performance and interest rates have been joined at the hip since the GFC aftermath as the Fed anchored short rates on the zero lower bound, thus shifting the sensitivity of bank profits to the long end of the curve versus the shape of the curve. If interest rates started galloping higher investors would initially seek the “safety” of bank earnings that would get a fillip from rising net interest margins and put our negative bank view offside (Chart 12). Chart 11Highest Momentum Since the GFC, But Valuations Are Nonresponsive Chart 12Risks To Monitor Netting it all out, early signs of housing related euphoria turning into consternation, lack of an overall bank credit impulse, relative share price overbought conditions, a looming increase in bank non-performing loans as government spending programs are set to expire in the autumn, will more than offset compelling bank valuations and rising interest rates. Bottom Line: Trim the S&P banks index to underweight, today.  The ticker symbols for the stocks in this index are: BLBG: S5BANKX – JPM, BAC, C, WFC, USB, PNC, TFC, FRC, FITB, SIVB, KEY, MTB, RF, CFG, HBAN, CMA, ZION, PBCT.   Anastasios Avgeriou US Equity Strategist anastasios@bcaresearch.com   Footnotes 1     https://www.ljkmfa.com/test-test/international-ssrs/ Current Recommendations Current Trades Strategic (10-Year) Trade Recommendations ​​​​​​​ Size And Style Views February 24, 2021 Stay neutral cyclicals over defensives January 12, 2021  Stay neutral small over large caps June 11, 2018 Long the BCA Millennial basket  The ticker symbols are: (AAPL, AMZN, UBER, HD, LEN, MSFT, NFLX, SPOT, ABNB, V). January 22, 2018 ​​​​​​​Favor value over growth

The SPX has been striving to find direction over the past couple of weeks in the seasonally weak month of May, as “transitory inflation” may actually morph into more semi-permanent inflation. The Fed’s latest minutes signaled that tapering is likely on its way, especially if non-farm payrolls resume increasing month-over-month near the one million mark as the economy will be in full reopening mode this Memorial Day. Historically, there is some turbulence that comes with the transition from ultra-easy monetary policy stance to, at the margin, less easy monetary policy warning that a shakeout equity market phase still looms. Tack on the modestly negative signal from investor positioning in the options market (top panel) and a volatile summer is likely upon us. Finally, news of China’s crackdown on cryptocurrencies has taken a bite out of Bitcoin that has been experiencing wild intra-day swings of late. Some of these apparent liquidation pressures have spilled over to the S&P 500 and, given the recent tight positive correlation between Bitcoin and the SPX (bottom panel), warn that some caution is still warranted in the equity space, at least in the near-term.  

Special Report

Highlights The selloff in crypto-currencies on May 19 may be overblown but the risk of government intervention is a rising headwind for this asset class. While environmental concerns are a threat to Bitcoin, the entire crypto-currency complex faces a looming confrontation over governance. Digital currencies are a natural evolution of money following coinage and paper. Moreover a sizable body of consumers is skeptical of governments and traditional banking. Loose monetary conditions are fueling a speculative mania. However, governments fought for centuries to gain a monopoly over money. As crypto-currencies become more popular, governments will step in to regulate and restrict them. Central bank digital currencies (CBDCs) threaten to remove the speed and transactional advantage of crypto-currencies, leaving privacy/anonymity as their main use-case. Feature The prefix “crypto” derives from the Greek kruptos or “hidden.” This etymology highlights one of the biggest problems confronting the crypto-currency craze in financial markets today. Speed and anonymity are the greatest assets of the digital tokens. But the former advantage is being eroded by competitors while the latter is becoming a political liability. In the 2020s, governments are growing stronger and more interventionist, not weaker and more laissez faire. Chart 1Loose Money Fuels Crypto Mania Bitcoin and rival crypto-currency Ethereum fell by 29.5% and 43.2% in intra-day trading on May 19, only to finish the day down by 13.8% and 27.2%, respectively. The market panicked on news that China’s central bank had banned firms from handling transactions in crypto-currencies. What really happened was that China’s National Internet Finance Association, China Banking Association, and Payment and Clearing Association issued a statement merely reiterating a 2013 and 2017 policy that already banned firms from handling transactions in crypto-currencies. These three institutions also warned about financial speculation regarding crypto-currencies.1 The crypto market suffered a spike in volatility because it is in the midst of a speculative mania. In the last five years, total market capitalization of crypto-currencies has risen from around $7 billion to $2.3 trillion,2 recording a 34,000% gain. Some crypto-currencies have even recorded returns in excess of that number over a shorter horizon. Price gains have been driven by retail buyers who may or may not know much about this new asset class (Chart 1). Prior to the May 19 selloff, prices had grown overextended and recent concerns over the environment, sustainability, and governance (ESG) had shaken confidence in Bitcoin and its peers. Chinese authorities have already banned financial firms from providing crypto services in a bid to deter ownership of crypto-currencies. And China is not alone. The latest market jitters are a warning sign that government interference in the crypto-currency market is a real threat. Regulation and sovereign-issued digital currencies are starting to enter the fray. While ultra-dovish central bank policies are not changing soon, and therefore crypto-currency price bubbles can continue to grow, crypto-currencies will remain subject to extreme volatility and precipitous crashes. In this report we argue that the fundamental problem with crypto-currencies is that they threaten the economic sovereignty of nation-states. Environmental degradation, financial instability, and black market crime, and other concerns about cryptos have varying degrees of merit. But they provide governments with ample motivation to pursue a much deeper interest in regulating a technological innovation that has the power to undermine state influence over the economy and society. Government scrutiny is a legitimate reason for crypto buyers to turn sellers. Does The World Need Crypto-Currencies? Broadly speaking, there are two primary justifications for crypto-currencies, centered on a transactional basis: speed and privacy/anonymity. The crux of crypto-currency creation rests on these two use cases.3 The speed of crypto-currencies comes from their ability to increase efficiency in local and global payment systems by facilitating financial transactions without the need of a third party (e.g. a financial institution). Cross-border settlement of traditional (fiat) currency transactions processed through the standard SWIFT communications system takes up to two business days. Most transactions involving crypto-currencies over a blockchain network are realized in less than an hour, cross-border or not.4 The fees involved with third-party payments are often more expensive than transacting with crypto-currencies. Simply put, excluding the “middleman” can save money. This is a selling point in a global market that expects to see retail cross-border transactions reach $3.5 trillion by the end of 2021, of which up to 5% are associated with transaction-based fees.5 But this breakthrough in payment system technology can be overstated and is not the main reason for using crypto-currency. Speculation drives current use, especially given that there is speculative behavior even among those who believe that cryptos are safe-haven assets or promising long-term investments (Chart 2). Chart 2Crypto-Currency Use Driven By Speculation Chart 3Consumers Growing Skeptical Of Banking Regulation If a person wants to buy an item from a company in a distant country, that person could use a crypto-currency just as he or she could use a credit card. Both parties would have a secure medium of exchange but, unlike with a credit card, both would avoid using fiat currencies. Neither party could conduct the same transaction using gold or silver. The crucial premise is the existence of an online community of individuals and firms who for one reason or another want to avoid fiat currencies. From a descriptive point of view, the crypto-currency phenomenon implies a lack of trust in modern governments, or at least their monetary systems, and an assertion of individual property rights. The list of crypto-currencies continues to grow. To date, there are approximately 9,800 of them. Some are trying to prove their economic value or use, while others have been created with no intended purpose or problem to solve. Even so, there has yet to be a crypto-currency that overwhelms the use of slower fiat money. In a recent Special Report, BCA Research’s Foreign Exchange Strategist Chester Ntonifor showed that crypto-currencies still have a long way to go to have a chance at replacing fiat monies. While crypto-currencies are showing signs of significant improvement as mediums of exchange, they still fall short as stores of value and units of account. The other primary case for crypto-currencies is privacy or anonymity. The bypassing of intermediaries implies a greater control of funds by the two parties of a transaction. Crypto-currencies are said to be more “private” compared to fiat money. Fiat money is controlled by governments and banks while crypto-currencies have only “owners.” Crypto-currencies are anonymous because they are stored in digital wallets with alphanumeric sequences – there is a limited personal data trail that follows crypto-currency compared to those of electronic fiat currency transactions. In a post-9/11, post-GFC, post-COVID world where a sizable body of consumers is growing more skeptical of government surveillance and regulation and banking industry practices (Chart 3), crypto-currencies give users more than just a means to transact with. However, privacy is not the same as security. Hacking and fraud can affect cryptos as well as other forms of money and attacks will increase with the value of the currencies. Bitcoin At The Helm Of Crypto-Currency Market Chart 4Bitcoin Slows Bitcoin has cemented its status as the number one currency in the crypto-verse.6 It is considered to be the first crypto-currency created, it is the most widely accepted, it is touted as a store of value or “digital gold,” and it is the most featured in quoting alternative crypto-currency pairs across crypto exchanges. As it stands, Bitcoin accounts for around 42% of total crypto-currency market capitalization.7 This share has declined from around 65% at the start of 2021 on the back of the frenzied rise of several alternative coins.8 But rising risks to Bitcoin’s standing will cause the entire crypto-market to retreat. In a Special Report penned in February, BCA Research’s Chief Global Strategist Peter Berezin argued that Bitcoin is more of a trend than a solution and that its usefulness is diminishing. Bitcoin’s transaction speed is slowing and its transaction cost is rising (Chart 4). Slowing speed and rising cost on the Bitcoin network are linked to a scalability problem. The crypto-currency’s network has a limited rate at which it can process transactions related to the fact that records (or “blocks”) in the Bitcoin blockchain are limited in size and frequency. This means that one of its fundamental justifications, transactional speed, will become less attractive over time, should the network not address these issues. Bitcoin also consumes a significant amount of energy, a controversy that is gaining traction in the crypto-currency market after Elon Musk, the “techno-king” of Tesla, cited environmental concerns in reversing his decision to accept Bitcoin payment for his company’s electric vehicles. Energy consumption rises as more coins are mined, since mining each new Bitcoin becomes more computer-power intensive. The need for computing power and energy will continue to increase until all 21 million Bitcoins (total supply) are mined, which is currently estimated to occur by the year 2140. Strikingly, the energy needed to mine Bitcoin over a year are comparable to a small country’s annual power consumption, such as Sweden or Argentina (Chart 5). Chart 5Bitcoin Consumes More Energy Than A Small Country … Bitcoin also generates significant quantities of electronic waste (Chart 6). Chart 6… And Generates A Lot Of Electronic Waste Bitcoin mining is heavily domiciled in China, which accounts for 65% of global mining activity (Figure 1). China’s energy mix is dominated by coal power, which makes up approximately 65% of the country’s total energy mix even after a decade of aggressive state-led efforts to reduce coal reliance. Of this, coal powered energy makes up approximately 60% of Bitcoin’s energy mix in China.9 With several countries aiming to minimize carbon emissions, and with approximately 60% of Bitcoin mining powered by coal-fired energy globally,10 Bitcoin imposes a major negative environmental impact. Figure 1Bitcoin Mining Well Anchored In Asia Bitcoin does not shape up well when compared to gold’s energy intensity either. Bitcoin mining now consumes more energy than gold mining over a single year. While the energy difference is not large, the economic value is. Gold’s energy consumption to economic value trade-off is lower than that of Bitcoin. The production value of gold in 2020 was close to $200 billion, while Bitcoin was measured at less than $25 billion (Chart 7A). On a one-to-one basis, gold even has a lower carbon footprint than Bitcoin (Chart 7B). Chart 7AGold Outshines Bitcoin On Production Value And Carbon Footprint Chart 7BGold Outshines Bitcoin On Production Value And Carbon Footprint Crypto-currency energy consumption and carbon footprint will attract the attention of government regulators. Of course, not all crypto-currencies are heavy polluters. But if the supply of cryptos is constrained by mining difficulties then they will require a lot of energy. If the supply is not constrained then the price will be low. Government Regulation Is Coming Environmental concerns point to the single greatest threat to crypto-currencies – the Leviathan, i.e. the state. In this sense the crypto market’s wild fluctuations on May 19, at the mere whiff of tougher Chinese regulation, are a sign of what is to come. Governments around the world have so far left crypto-currencies largely unregulated but this laissez-faire attitude is already changing. Environmental regulation has already been mentioned. Governments will also be eager to expand their regulatory powers to “protect” consumers, businesses, and banks from extreme volatility in crypto markets. But investors will underrate the regulatory threat if they focus on these issues. At the most basic level, governments around the world will not sit idly by and lose what could become significant control of their monetary systems. The ability to establish and control legal tender is a critical part of economic sovereignty. Governments won control of the printing press over centuries and will not cede that control lightly. If crypto-currencies are adopted widely, then finance ministries and central banks will lose their ability to manipulate the money supply and the general level of prices effectively. Politicians will lose the ability to stimulate the economy or keep inflation in check. Most importantly, while one may view such threats as overblown, it is governments, not other organizations, that will make the critical judgment on whether crypto-currencies threaten their sovereignty. Throughout the world, most crypto-currency exchanges are regulated to prevent money laundering. Crypto-currencies are not legal tender and, aside from Bitcoin, their use is mostly banned in China (Table 1). However, more specialized regulation that targets energy and economic use has yet to be brought into law across the world. Table 1World Governments Will Not Relinquish Hard-Fought Monopolies Over Money Supply In China, initial coin offerings (ICOs – the equivalent of an initial public offering on the stock market) and trading platforms are banned from engaging in exchanges between the yuan and crypto-currencies or tokens. In fact, China recognizes crypto-currencies only as virtual commodities or virtual property. India is another country where exchanges and ICOs are banned. While crypto-currencies are not banned, they are not legal tender. Indian policymakers have recently proposed banning crypto-currencies, however. The proposed legislation is one of the world’s strictest policies against crypto-currencies. It would criminalize possession, issuance, mining, trading, and transferring crypto-assets. If the ban becomes law, India would be the first major economy to make holding crypto-currency illegal. Even China, which has banned mining and trading, does not penalize possession. In the US, Secretary of the Treasury Janet Yellen has already expressed concerns regarding the illicit use of cryptos for supposed criminal gain.11 She is in alignment with European Central Bank President Christine Lagarde. Because of the anonymity of crypto-currencies, identifying users behind illicit transactions is difficult. This means regulators face headwinds in identifying transactions that are made for criminal gain, as compared to fiat transactions. Governments have long dealt with the anonymity of cash but they have ways of monitoring bank accounts and paper bills. Crypto-currencies are beyond their immediate sight of control and therefore will attract growing scrutiny and legislative action in this regard. The Colonial Pipeline ransomware attack on May 7, which temporarily shuttered about 45% of the fuel supply line for the eastern United States, illustrates the point. The DarkSide group of hackers who orchestrated the attack demanded a ransom payment of $4.4 million worth of Bitcoin, which Colonial Pipeline paid them on May 7. Shortly thereafter, unspecified “law enforcement agencies” clawed back the $4.4 million from the hackers’ account (transferring it to an unknown address) and DarkSide lost access to its payment server, DOS servers, and blog. This episode should not be underrated. It was a successful, large-scale cyber-attack on critical infrastructure in the world’s most powerful country. It highlighted the illicit uses to which crypto-currencies can be put. True, criminals demand ransoms in fiat money as well – and many crypto-currency operators will distance themselves from the criminal underworld. Nevertheless governments will give little slack to an emerging technology that presents big new law enforcement challenges and is not widely used by the general public. Ultimately governments will pursue their sovereign interests in controlling money, the economy, and trade, listening to their banking lobby, expanding their remit to “protect” consumers, and cracking down on illicit activity. Governments are not capable of abolishing crypto-currencies altogether, or the underlying technology of blockchain. But they will play a large and growing role in regulating them. Central Banks Advancing On Digital Currencies Central bank digital currencies (CBDCs) will leave crypto-currencies in the realm of speculative assets. CBDCs are a form of digital money denominated in a country’s national unit of account and represent a liability on a central bank’s balance sheet. This is different from current e-money that represents a claim on a private financial institution’s balance sheet. It is also different from crypto-currencies, because there is a central authority behind a CBDC, unlike with crypto-currencies due to their decentralized nature. In China, the People’s Bank of China (PBoC) has suggested its rollout of a digital yuan is “ready” despite no release to date. Beta testing is ongoing in several provinces. The PBoC’s justification for a digital yuan comes from China’s growing cashless economy. The transition away from cash is largely thanks to mobile payment platforms like Alibaba’s Alipay and Tencent’s WeChat Pay, which, between the two of them, control almost the entire mobile payments market of some 850 million users. There is a significant amount of systemic risk in this system – one reason why Chinese authorities have recently subjected these companies to new scrutiny and regulation. Should Alibaba or Tencent go bankrupt, the local payment system will crash. The PBoC’s efforts will increase competition in the local payments space and reduce this systemic risk. Policymakers are also concerned that as Chinese citizens choose to hold their money in digital wallets provided by Alibaba and Tencent instead of bank accounts, liquidity is being drained from the traditional banking system, putting deposit levels at banks under strain, and posing risks to liability matching. The digital yuan will still involve a third party, unlike crypto-currencies which do not. Doing away with commercial banks is not a reality – indeed the Chinese Communist Party seeks to buttress the state-owned commercial banks in order to maintain control of the economy. What the digital yuan does, and other CBDCs will do too, is utilize blockchain technology, which is faster and more secure than traditional payment networks. In the US, the Fed has been studying the viability of a CBDC US dollar. The Fed has stated that it is carefully exploring whether a CBDC will lead to “safer, less expensive, faster, or otherwise more efficient payments.” While the Fed has yet to find a single standout case for a CBDC US Dollar, Fed Chair Jerome Powell said last year that the US has a “competitive payments market” with “fast and cheap services, particularly in comparison to other nations exploring a CBDC.” To date, the Fed’s observation is that many of the challenges that CBDCs hope to address do not apply to the US, including disuse of physical cash, narrow reach or high concentration of banking, and weak infrastructure for payment systems. Rather, the Fed is more focused on developing the FedNow real-time payment system for private banks. This is much the same as in Europe, where physical cash still plays a major role in day-to-day economic activity and where local payment systems are fast and secure. But central banks around the world continue to engage in work centered around CBDCs (Charts 8A and 8B) – and China’s progress will encourage others to move faster. Advanced economies are mostly interested in creating a safer and more efficient payment system, while emerging and developed economies have interest across several areas such as financial stability, monetary policy setting, and inclusiveness of banking, as well as efficiency and safety (Chart 9). CBDCs are especially attractive to emerging market policy makers at targeting those who lack access to traditional banking. Chart 8ACentral Banks Advancing On CBDC Work Chart 8BCentral Banks Advancing On CBDC Work Chart 9Central Banks CBDC Interest Areas In remote areas, access to banking is scarce and expensive. CBDCs can help solve this problem. Individuals would have CBDC accounts directly on a central bank ledger. They could then access their money and transact through a digital wallet application that is linked to the CBDC account. Giving people access to digital currency would allow them to transact quickly, in remote settings, without the need of hard currency. Monetary policy transmission is also better in advanced economies. In emerging markets, there are bottlenecks in local financial markets. Looser central monetary policy does not always translate into cheaper financing across the economy. In remote and poverty stricken areas, monetary policy transmission is sticky, meaning high costs of borrowing can persist even through accommodative policy cycles. This is a smaller issue in advanced economies. Payment systems in advanced economies are due an overhaul in security and efficiency, and CBDCs and blockchain technology will provide this. CBDCs will prove to be just as efficient to transact with as any crypto-currencies available today. CBDCs will also be legal tender and accepted by all vendors. The anonymity factor will be lost but this will not be a problem for most users (whereas legal issues will become a problem for crypto-currencies). The probability of central banks issuing CBDCs in both the short and medium term, both in the retail and wholesale space, is rising. If advanced economies like those of the G7 issue CBDCs soon, policy makers will undoubtedly ensure the use of it over the currently circulating and partially accepted crypto-currencies. The endgame will leave crypto-currencies in the highly speculative asset class, perhaps even in the black market where anonymity is valued for transactions that wish not to be tracked. Investment Takeaways Prices of crypto-currencies may continue to rise given sky-high fiat money creation amid the COVID pandemic and ultra-low interest rates. Digitalization is the natural next step in the evolution of money from precious metals to paper banknotes to electronic coin. But the market leader, Bitcoin, is encountering more headwinds. The primary case for the use of Bitcoin is challenged due to slowing transaction speeds and rising transaction costs. The virtual currency is primarily mined using coal-powered energy, resulting in growing scrutiny from governments and consumers. Government regulation is entering the ring and policymakers will take an increasingly heavy-handed role in trying to ensure that cryptos do not undermine economic sovereignty, financial stability, and law and order. When central banks begin to rollout digital currencies, especially those domiciled in advanced economies, crypto-currencies as medium of exchange will lose much of their allure. Crypto-currencies will remain as anti-fiat currencies and speculative assets. Risks To The View Given the controversy surrounding crypto-currencies, it is only fair to state outright the risks to our view. We would also recommend clients read our colleague Dhaval Joshi’s latest bullish take on Bitcoin. First, scaling up Bitcoin’s network and processing transactions in batches instead of single transactions will resolve transaction time and cost risks, restoring efficiency. This is a clear solution to efficiency concerns. However, scaling and batching transactions are not on the immediate horizon of Bitcoin developers. Bitcoin’s network will still need to undergo another “halving” in order for this risk to subside and for the network to scale. A halving of the network will only occur again in 2024.12 Second, on the environment: Bitcoin mining is not solely dependent on fossil fuel energy that gives it a “dirty” footprint. Renewables already make up some 25% of Bitcoin mining. Increasing the use of renewables in Bitcoin’s energy mix will help lower its environmental impact. However, this is easier said than done. Global renewable energy has yet to scale up to a point where it can consistently out-supply existing fossil-fuel energy. Mining hardware also has its associated carbon footprint that would need to be addressed. And location matters too. Crypto-currency mining farms are large-scale projects. Simply uprooting operations to a country that could lower the carbon footprint of a mining farm or two is not viable due to the costs involved. Hence crypto-currency mining will probably continue to be a “dirty” operation but a rapid shift to renewables would challenge our thesis. Bitcoin’s network is also based off a “proof of work” protocol. Miners must prove that a certain amount of computational effort has been expended for confirming blocks on the network, allowing transactions to be processed. Proof of work is energy intensive. Other crypto-currencies, like Ethereum, will adopt a “proof of stake” protocol. Simply put, transactions are confirmed by users and their stake in the associated crypto-currency. Proof of stake is less energy intensive compared to proof of work. Third, as to government regulation, the longer policymakers take to enact legislation targeting crypto-currencies, the larger their market will grow. Regulation in China and India may set a benchmark for major economies but not all will follow in the Asian giants’ footsteps. Some governments have been slow to study crypto-currencies, meaning legislation aimed at governing or regulating them may still be long in coming. Innovation is a good thing and free economies will not wish to restrain crypto-currencies or blockchain technology unduly, for fear of missing out. Fourth, on CBDCs, some central banks may only adopt them based on their respective economic needs. However, rising crypto-currency populism drives associated economic risks which can force the hands of central banks to adopt CBDCs in lieu of said needs. Each country faces unique challenges. Some central banks may not want to be left behind even if they believe their policy framework is facilitating economic activity efficiently. While the Fed has stated that it will not adopt a CBDC for the primary reason of ensuring payment security since it believes it already has a safe system in place, this view will change. The Fed could justify a move to a CBDC US dollar on the single basis of transitioning to a more sophisticated technology for the future. The Fed will not want to be caught behind the curve considering the PBoC is priming its digital yuan for release soon. Technological leadership is a strategic imperative of the United States and that imperative applies to financial technology as well as other areas.   Guy Russell Research Analyst GuyR@bcaresearch.com Matt Gertken Vice President Geopolitical Strategy mattg@bcaresearch.com Footnotes 1 Muyao Shen, “China Reiterates Crypto Bans From 2013 and 2017”, coindesk, May 18, 2021, coindesk.com. 2 As of May 11, 2021. 3 There are several other reasons or “problems” that crypto-currencies are created for or to solve, but speed and privacy form the basis of crypto-currencies first coming into existence. 4 Not all crypto-currencies transact in less than an hour. But there are many that transact in several minutes and in some cases, mere seconds. As the leading crypto-currency, Bitcoin takes approximately one hour for a transaction to be fully verified over its network. 5 “McKinsey’s Global Banking Annual Review”, McKinsey, Dec. 9, 2020, mckinsey.com. 6 We use Bitcoin as an example to understand the risk and impact of forthcoming government regulation and competition. Because of Bitcoin’s status, any significant risks that threaten the crypto-currency’s standing as the number one currency will threaten the entire market. 7 As of May 20, 2021. Figure varies daily. See www.coinmarketcap.com for more information. 8 Alternative currencies such as Ethereum, Ripple, Binance Coin, Dogecoin, and Cardano have chipped away at Bitcoin’s crypto-market dominance through 2021. 9 According to The Center For Alternative Finance, The University Of Cambridge. 10 According to The Center For Alternative Finance, The University Of Cambridge. 11 Data on the use of crypto-currencies for illicit activitiessays otherwise. Of all crypto-currency transactions, it is estimated that only 2.1% are used for illicit activities. See “2021 Crypto Crime Report”, Chainalysis, chainalysis.com. 12 A Bitcoin halving is when the reward for mining Bitcoin transactions is cut in half. This event also cuts Bitcoin's inflation rate and the rate at which new Bitcoins enter circulation, in half. Bitcoin last halved on May 11, 2020.