Global

Highlights Global growth is still slowing. Having rallied since the start of the year, global stocks will likely enter a “dead zone” over the next six-to-eight weeks as investors nervously await the proverbial green shoots to sprout. We think they will appear in the second quarter, setting the scene for a reacceleration in global growth in the second half of the year, and an accompanying rally in global risk assets. Investors should overweight stocks and spread product while underweighting safe government bonds over a 12-month horizon. The U.S. dollar will strengthen a bit over the next few months, but should start to weaken in the summer as the global economy catches fire. Stronger global growth and a weaker dollar in the back half of the year will benefit EM assets and European stocks. Feature I skate to where the puck is going to be, not to where it has been. — Wayne Gretzky How To Be A Good Macro Strategist To paraphrase Gretzky, a mediocre macro strategist draws conclusions based solely on incoming data. A good macro strategist, in contrast, tries to figure out where the data is heading. How can one predict how the economic data will evolve? Examining forward-looking indicators is helpful, but it is not enough. One also has to understand why the data is evolving the way it is. If one knows this, one can then assess whether the forces either hurting or helping growth will diminish, intensify, or remain the same.  What Accounts For the Growth Slowdown? There is little mystery as to why global growth slowed in 2018. Chinese credit growth fell steadily over the course of the year, which generated a negative credit impulse. Unlike in the past, China is now the most important driver of global credit flows (Chart 1). Chart 1Global Credit Flows Are Increasingly Driven By China Meanwhile, the global economy was rocked by rising oil prices. Brent rose from $55/bbl on October 5, 2017 to $85/bbl on October 4, 2018. Government bond yields also increased, with the 10-year U.S. Treasury yield rising from 2.05% on September 7, 2017 to 3.23% on October 5, 2018 (Chart 2). Chart 2Rising Oil Prices And Bond Yields Contributed To Slower Global Growth Last Year A mediocre macro strategist draws conclusions based solely on incoming data. A good macro strategist, in contrast, tries to figure out where the data is heading. In an ironic twist, Jay Powell’s ill-timed comment that rates were “a long way” from neutral marked the peak in bond yields. Unfortunately, the subsequent decline in yields was accompanied by a vicious stock market correction and a widening in credit spreads. This led to an overall tightening in financial conditions, which further hurt growth (Chart 3). Chart 3Financial Conditions Tightened In 2018, Especially After Powell's Hawkish Comments The critical point is that all of these negative forces are behind us: Financial conditions have eased significantly over the past two months; oil prices have rebounded, but are still well below their 2018 highs; and as we explain later on, Chinese growth is likely to bottom by the middle of this year. This means that global growth should start to improve over the coming months. The United States: Better News Ahead The latest U.S. economic data has been weak, with this morning’s disappointing ISM manufacturing print being the latest example. The New York Fed’s GDP Nowcast is pointing to annualized growth of 0.9% in the first quarter. While there is no doubt that underlying growth has decelerated, data distortions have probably also contributed to the perceived slowdown. For instance, the dismal December retail sales report reduced the base for consumer spending going into 2019, thus shaving about 0.4 percentage points off Q1 growth. The drop in real personal consumption expenditures (PCE) cut the New York Fed’s Q1 growth estimate by a further 0.15 percentage points. We suspect that much of the weakness in December retail sales and PCE was linked to the government shutdown. The closure caused some of the surveys used to compile these reports to be postponed until January, which is historically the weakest month for retail sales. The Johnson Redbook Index – which covers 80% of the retail sales surveyed by the Department of Commerce – as well as the sales figures from Amazon and Walmart all point to strong spending during the holiday season (Chart 4). Chart 4The December U.S. Retail Sales Report Was Probably A Fluke Fundamentally, U.S. consumers are in good shape (Chart 5). As a share of disposable income, household debt is over 30 percentage points lower than it was in 2007. The savings rate stands at an elevated level, which gives households the wherewithal to increase spending. Job openings hit another record high, while wage growth continues to trend upwards. Fundamentally, U.S. consumers are in good shape. Chart 5U.S. Consumer Fundamentals Are Solid The housing market should improve. Rising mortgage rates weighed on housing last year. However, rates have been declining for several months now, which augurs well for home sales and construction over the next six months (Chart 6). Chart 6Mortgage Rates Will Not Be A Headwind For U.S. Housing Activity Over The Next 6 Months While capex intention surveys have come off their highs, they still point to reasonably solid expansion plans (Chart 7). Rising labor costs and high levels of capacity utilization will induce firms to invest in more capital equipment, which should support business spending. Chart 7U.S. Capex Plans Have Come Off Their Highs, But Remain Solid Government expenditures should also recover. By most estimates, the shutdown shaved one percentage point from Q1 growth. This is likely to be completely reversed in the second quarter. The End Of The Chinese Deleveraging Campaign? The popular narrative about weaker Chinese growth has focused on the trade war. While trade uncertainty undoubtedly hurt growth last year – and has continued to weigh on growth so far this year – most of the weakness in the Chinese economy can be traced to the deleveraging campaign which started in 2017, long before the surge in trade flow angst. Fixed investment spending in China is generally financed through credit markets. Chart 8 shows that the contribution of investment spending to GDP growth has declined in tandem with decelerating credit growth.   Most of the weakness in the Chinese economy can be traced to the deleveraging campaign which started in 2017, long before the surge in trade flow angst. Chart 8China: Deleveraging Means Less Investment-Led Growth Chinese credit growth has typically reaccelerated whenever it has dipped towards trend nominal GDP growth. We may have already reached this point (Chart 9). New credit formation came in well above expectations in January. Given possible distortions caused by the timing of the Chinese lunar new year, investors should wait until the February data is released in mid-March before drawing any firm conclusions. Nevertheless, it is starting to look increasingly likely that credit growth has bottomed. The 6-month credit impulse has already surged (Chart 10). The 12-month impulse should also begin moving up provided that month-over-month credit growth simply maintains its recent trend (Chart 11). Chart 9Historically, China Has Scaled Back On Deleveraging When Credit Growth Has Fallen Close To Nominal GDP Growth Chart 10A Rebound In The Chinese 6-Month Credit Impulse Chart 11The 12-Month Impulse Is Set To Turn Up On the trade front, President Trump’s decision to delay the implementation of tariffs on $200 billion in Chinese imports is a step in the right direction. Nevertheless, gauging whether the trade war will continue to de-escalate is extraordinarily difficult. There is no major constituency within the Republican Party campaigning for protectionism. It ultimately boils down to what one man – Trump – wants. Our best guess is that President Trump will try to score a few political points by “declaring victory” – deservedly or not – in his battle with China in order to pivot to more pressing domestic issues such as immigration. However, there can be no assurance of this, which is why China’s leaders are likely to prioritize growth over deleveraging, at least for the time being. They know full well that the only way they can credibly threaten to walk away from the negotiating table is if their economy is humming along. Europe: From Headwinds To Tailwinds? Slower global growth, higher oil prices, and a spike in Italian bonds yields all contributed to the poor performance of the European economy last year. Economic activity was further hampered by a decline in German automobile production following the introduction of more stringent emission standards. The good news is that these headwinds are set to reverse course. Italian bond yields are well off their highs, as are oil prices (Chart 12). German automobile production is recovering (Chart 13). In addition, the European Commission expects the euro area fiscal thrust to reach 0.40% of GDP this year, up from 0.05% of GDP last year (Chart 14). This should add about half a percentage point to growth. Finally, if our expectation that Chinese growth will bottom out by mid-year proves correct, European exports should benefit. If neither the political establishment nor the general public favor Brexit, it will not happen. Chart 12Headwind No More (I): Italian Bond Yields Chart 13Headwind No More (II): German Auto Sector Chart 14The Euro Area Will Benefit From A Modest Amount Of Fiscal Easing This Year Brexit still remains a risk, but a receding one. We have consistently argued that the political establishment on both sides of the British channel will not accept anything resembling a hard Brexit. As was the case with the EU treaty referendums involving Denmark and Ireland in the 1990s, the European political elites will insist on a “No fair! Let’s play again! Best two-out-of-three?” do-overs until they get the result they want. Theresa May’s efforts to cobble together a parliamentary majority that precludes a hard Brexit, along with the Labor Party’s increasing willingness to pursue a second vote, is consistent with our thesis. Fortunately for the “remain” side, public opinion is shifting in favor of staying in the EU (Chart 15). Focusing on the minutiae of various timetables, rules, and regulations is largely a waste of time. If neither the political establishment nor the general public favor Brexit, it will not happen. We are short EUR/GBP, a trade recommendation that has gained 5.2% since we initiated it. We continue to see upside for the pound. Chart 15The ''Remain'' Side Would Likely Win Another Referendum Investment Conclusions Global growth is still slowing. Having rallied since the start of the year, global stocks will likely enter a “dead zone” for the next six-to-eight weeks as investors nervously await the proverbial green shoots to sprout. We think they will appear in the second quarter, setting the scene for a reacceleration in global growth in the second half of the year, and an accompanying rally in global risk assets. The dollar is a countercyclical currency, meaning that it moves in the opposite direction of the global business cycle (Chart 16). The greenback will strengthen a bit over the next few months, but should start to weaken in the summer as the global economy catches fire. Chart 16The Dollar Is A Countercyclical Currency We sold our put on the EEM ETF for a gain of 104% on Jan 3rd, and are now outright long EM equities. We do not have a strong view on EM versus DM equities at the moment, but expect to shift EM to overweight once we see more confirmatory evidence that Chinese growth is stabilizing. Having rallied since the start of the year, global stocks will likely enter a “dead zone” for the next six-to-eight weeks as investors nervously await the proverbial green shoots to sprout. In conjunction with our expected upgrade on EM assets, we will move European equities to overweight. Stronger global growth will benefit European multinational exporters, while brisker domestic growth should allow the market to price in a few more ECB rate hikes starting in 2020. The latter will lead to a somewhat steeper yield curve which, along with rising demand for credit, should boost financial sector earnings (Chart 17). This will give European bank stocks a welcome boost. Chart 17Stronger Euro Area Credit Growth Will Boost Bank Earnings Japanese equities will also benefit from faster global growth, but domestic demand will suffer from the government’s ill-advised plan to raise the sales tax in October. As such, we do not anticipate upgrading Japanese stocks. We also expect the yen to come under some pressure as the BoJ is forced to maintain its ultra-accommodative monetary policy stance, while bond yields elsewhere move modestly higher.      Peter Berezin Chief Global Investment Strategist peterb@bcaresearch.com   Strategy & Market Trends* MacroQuant Model And Current Subjective Scores Tactical Trades Strategic Recommendations Closed Trades

  Highlights Global growth is still slowing. Having rallied since the start of the year, global stocks will likely enter a “dead zone” over the next six-to-eight weeks as investors nervously await the proverbial green shoots to sprout. We think they will appear in the second quarter, setting the scene for a reacceleration in global growth in the second half of the year, and an accompanying rally in global risk assets. Investors should overweight stocks and spread product while underweighting safe government bonds over a 12-month horizon. The U.S. dollar will strengthen a bit over the next few months, but should start to weaken in the summer as the global economy catches fire. Stronger global growth and a weaker dollar in the back half of the year will benefit EM assets and European stocks. Feature I skate to where the puck is going to be, not to where it has been.  — Wayne Gretzky Gretzky's Doctrine To paraphrase Gretzky, a mediocre macro strategist draws conclusions based solely on incoming data. A good macro strategist, in contrast, tries to figure out where the data is heading. How can one predict how the economic data will evolve? Examining forward-looking indicators is helpful, but it is not enough. One also has to understand why the data is evolving the way it is. If one knows this, one can then assess whether the forces either hurting or helping growth will diminish, intensify, or remain the same. What Accounts For The Growth Slowdown? There is little mystery as to why global growth slowed in 2018. Chinese credit growth fell steadily over the course of the year, which generated a negative credit impulse. Unlike in the past, China is now the most important driver of global credit flows (Chart I-1). Meanwhile, the global economy was rocked by rising oil prices. Brent rose from $55/bbl on October 5, 2017 to $85/bbl on October 4, 2018. Government bond yields also increased, with the 10-year U.S. Treasury yield rising from 2.05% on September 7, 2017 to 3.23% on October 5, 2018 (Chart I-2). In an ironic twist, Jay Powell’s ill-timed comment that rates were “a long way” from neutral marked the peak in bond yields. Unfortunately, the subsequent decline in yields was accompanied by a vicious stock market correction and a widening in credit spreads. This led to an overall tightening in financial conditions, which further hurt growth (Chart I-3). The critical point is that all of these negative forces are behind us: Financial conditions have eased significantly over the past two months; oil prices have rebounded, but are still well below their 2018 highs; and as we explain later on, Chinese growth is likely to bottom by the middle of this year. This means that global growth should start to improve over the coming months. The United States: Better News Ahead The latest U.S. economic data has been weak, with this morning’s disappointing ISM manufacturing print being the latest example. The New York Fed’s GDP Nowcast is pointing to annualized growth of 0.9% in the first quarter. While there is no doubt that underlying growth has decelerated, data distortions have probably also contributed to the perceived slowdown. For instance, the dismal December retail sales report reduced the base for consumer spending going into 2019, thus shaving about 0.4 percentage points off Q1 growth. The drop in real personal consumption expenditures (PCE) cut the New York Fed’s Q1 growth estimate by a further 0.15 percentage points. We suspect that much of the weakness in December retail sales and PCE was linked to the government shutdown. The closure caused some of the surveys used to compile these reports to be postponed until January, which is historically the weakest month for retail sales. The Johnson Redbook Index – which covers 80% of the retail sales surveyed by the Department of Commerce – as well as the sales figures from Amazon and Walmart all point to strong spending during the holiday season (Chart I-4). Fundamentally, U.S. consumers are in good shape (Chart I-5). As a share of disposable income, household debt is over 30 percentage points lower than it was in 2007. The savings rate stands at an elevated level, which gives households the wherewithal to increase spending. Job openings hit another record high, while wage growth continues to trend upwards. The housing market should improve. Rising mortgage rates weighed on housing last year. However, rates have been declining for several months now, which augurs well for home sales and construction over the next six months (Chart I-6). While capex intention surveys have come off their highs, they still point to reasonably solid expansion plans (Chart I-7). Rising labor costs and high levels of capacity utilization will induce firms to invest in more capital equipment, which should support business spending. Government expenditures should also recover. By most estimates, the shutdown shaved one percentage point from Q1 growth. This is likely to be completely reversed in the second quarter. The End Of The Chinese Deleveraging Campaign? The popular narrative about weaker Chinese growth has focused on the trade war. While trade uncertainty undoubtedly hurt growth last year – and has continued to weigh on growth so far this year – most of the weakness in the Chinese economy can be traced to the deleveraging campaign which started in 2017, long before the surge in trade flow angst. Fixed investment spending in China is generally financed through credit markets. Chart I-8 shows that the contribution of investment spending to GDP growth has declined in tandem with decelerating credit growth.   Chinese credit growth has typically reaccelerated whenever it has dipped towards trend nominal GDP growth. We may have already reached this point (Chart I-9). New credit formation came in well above expectations in January. Given possible distortions caused by the timing of the Chinese lunar new year, investors should wait until the February data is released in mid-March before drawing any firm conclusions. Nevertheless, it is starting to look increasingly likely that credit growth has bottomed. The 6-month credit impulse has already surged (Chart I-10). The 12-month impulse should also begin moving up provided that month-over-month credit growth simply maintains its recent trend (Chart I-11). On the trade front, President Trump’s decision to delay the implementation of tariffs on $200 billion in Chinese imports is a step in the right direction. Nevertheless, gauging whether the trade war will continue to de-escalate is extraordinarily difficult. There is no major constituency within the Republican Party campaigning for protectionism. It ultimately boils down to what one man – Trump – wants. Our best guess is that President Trump will try to score a few political points by “declaring victory” – deservedly or not – in his battle with China in order to pivot to more pressing domestic issues such as immigration. However, there can be no assurance of this, which is why China’s leaders are likely to prioritize growth over deleveraging, at least for the time being. They know full well that the only way they can credibly threaten to walk away from the negotiating table is if their economy is humming along. Europe: From Headwinds To Tailwinds? Slower global growth, higher oil prices, and a spike in Italian bonds yields all contributed to the poor performance of the European economy last year. Economic activity was further hampered by a decline in German automobile production following the introduction of more stringent emission standards. The good news is that these headwinds are set to reverse course. Italian bond yields are well off their highs, as are oil prices (Chart I-12). German automobile production is recovering (Chart I-13). In addition, the European Commission expects the euro area fiscal thrust to reach 0.40% of GDP this year, up from 0.05% of GDP last year (Chart I-14). This should add about half a percentage point to growth. Finally, if our expectation that Chinese growth will bottom out by mid-year proves correct, European exports should benefit. Brexit still remains a risk, but a receding one. The political establishment on both sides of the British channel will not accept anything resembling a hard Brexit. As was the case with the EU treaty referendums involving Denmark and Ireland in the 1990s, the European political elites will insist on a “No fair! Let’s play again! Best two-out-of-three?” do-overs until they get the result they want. Theresa May’s efforts to cobble together a parliamentary majority that precludes a hard Brexit, along with the Labor Party’s increasing willingness to pursue a second vote, is consistent with our thesis. Fortunately for the “remain” side, public opinion is shifting in favor of staying in the EU (Chart I-15). Focusing on the minutiae of various timetables, rules, and regulations is largely a waste of time. If neither the political establishment nor the general public favor Brexit, it will not happen. Investment Conclusions Global growth is still slowing. Having rallied since the start of the year, global stocks will likely enter a “dead zone” for the next six-to-eight weeks as investors nervously await the proverbial green shoots to sprout. We think they will appear in the second quarter, setting the scene for a reacceleration in global growth in the second half of the year, and an accompanying rally in global risk assets. The dollar is a countercyclical currency, meaning that it moves in the opposite direction of the global business cycle (Chart I-16). The greenback will strengthen a bit over the next few months, but should start to weaken in the summer as the global economy catches fire. We do not have a strong view on EM versus DM equities at the moment, but expect to shift EM to overweight once we see more confirmatory evidence that Chinese growth is stabilizing. In conjunction with our expected upgrade on EM assets, we will move European equities to overweight. Stronger global growth will benefit European multinational exporters, while brisker domestic growth should allow the market to price in a few more ECB rate hikes starting in 2020. The latter will lead to a somewhat steeper yield curve which, along with rising demand for credit, should boost financial sector earnings (Chart I-17). This will give European bank stocks a welcome boost. Japanese equities will also benefit from faster global growth, but domestic demand will suffer from the government’s ill-advised plan to raise the sales tax in October. As such, we do not anticipate upgrading Japanese stocks. We also expect the yen to come under some pressure as the BoJ is forced to maintain its ultra-accommodative monetary policy stance, while bond yields elsewhere move modestly higher. Peter Berezin    Chief Global Investment Strategist March 1, 2019 Next Report: March 28, 2019 II. Troubling Implications Of Global Demographic Trends Developed economies are challenged by two powerful and related demographic trends: declining growth in working-age populations, and a rapidly-aging population structure. Working-age populations are in absolute decline in Japan and much of Europe and growth is slowing sharply in the U.S. An offsetting acceleration in productivity growth is unlikely, implying a marked deceleration in economic growth potential. The combination of slower growth in the number of taxpayers and rising numbers of retirees is toxic for government finances. Future generations face sharply rising debt burdens and increased taxes to pay for entitlements. The correlation between aging and asset prices is inconclusive but common sense suggests it is more likely to be bearish than bullish. Population growth remains rapid throughout most of the developing world, China being a notable exception. It is especially strong in Africa, a region that has historically faced economic mismanagement and thus poor economic prospects for most of its inhabitants. Migration from the emerging to developed world is a logical solution to global demographic trends, but faces a backlash in many countries for both economic and cultural reasons. These tensions are likely to increase. Making accurate economic and market forecasts is daunting because there are so many moving parts and unanticipated events are inevitable. Quantitative models are destined to fail because of the unpredictability of human behavior and random shocks. Demographic forecasts are a lot easier, at least over the short-to-medium term. If you want to know how many 70-year olds there will be in 10 years’ time, then count how many 60-year olds there are today and adjust by the mortality rate for that age group. Demographic trends are very incremental from year to year and their impact is swamped by economic, political and financial events. Thus, it rarely makes sense to blame demographics for cyclical swings in the economy or markets. In some respects, demographics can be likened to glaciers. You will quickly get bored standing by a glacier to watch it move. But, over long time periods, glaciers cover enormous distances and can completely reshape the landscape. Similarly, over the timespan of one or more generations, demographics can have powerful effects on economies and societies. Some important demographic trends have been going on for long enough that their effects are visible. The most common concern about global demographics has tended to be overpopulation and pressure on resources and the environment. And this is hardly new. In 1798, Thomas Malthus published his “Essay on The Principles of Population” in which he argued that population growth would outstrip food supply, leading to a very miserable outcome. Of course, what he missed was the revolution in agricultural techniques that meant food supply kept up with population growth. In 1972, a group of experts calling themselves The Club of Rome published a report titled “The Limits to Growth” which argued that a rising world population would outstrip the supply of natural resources, putting a limit to economic growth. Again, that report underestimated the ability of technology to solve the problem of scarcity, although many still believe the essence of the report has yet to be proved wrong. Phenomena such as climate change and rising numbers of animal species facing extinction are seen as supporting the thesis that the world’s population is putting unsustainable demands on the planet. Rather than get into that debate, this report will focus on three particular big-picture problems associated with demographic trends: Declining working-age populations in most major industrialized economies during the next several decades. Population aging throughout the developed world. Continued rapid population growth in many of the world’s poorest and most troubled countries. According to the UN’s latest projections, the world’s population will increase from around 7.5 billion today to almost 10 billion by 2050.1 The population growth rate peaked in the 1970s and is expected to slow sharply over the next several decades (Chart II-1). Despite slower percentage growth rates, the population keeps going up steadily because one percent of the 1970 global population was about 3.7 million, while one percent of the current population is about 7.5 million. But here is an important point: virtually all future growth in the global population will come from the developing world (Chart II-2). The population of the developed world is expected to be broadly flat over the period to 2050, and this has some significant economic implications. Let’s first look at why population growth has stagnated in the developed world. Population growth is a function of three things: the birth rate, the death rate and net migration. Obviously, if there are more births than deaths then there will be a natural increase in the population and net migration will either add or subtract to that. Over time, there have been major changes in some of these drivers. In the developed world, a stable population requires that, on average, there are 2.1 children born for every woman. The fact that it is not exactly 2 accounts for infant mortality and because there are slightly more males than females born. The replacement-level fertility rate needs to be higher than 2.1 in the developing world because of higher infant mortality rates. After WWII, the fertility rate throughout most of the developed world was well above 2.1 as soldiers returned home and the baby boom generation was born. But, by the end of the 1970s, the rate had dropped below the replacement level in most countries and currently is a lowly 1.5 in Japan, Germany and Italy (Table II-1). It has stayed higher in the U.S. but even there it has dipped below the critical 2.1 level. This trend has reflected lot of factors including more widespread use of birth control and more women entering the labor force. In the developed world, the birth rate is expected to drop below the death rate in the next ten years (Chart II-3). That means there will be a natural decrease in the population. In the case of Japan, Germany, Italy and Portugal that change already occurred between 2005 and 2010. In the U.S., the UN expects birth rates to stay just above death rates in the period to 2050, but the gap narrows sharply. Births exceed deaths throughout most of the developing world meaning that populations continue to grow. Notable exceptions to this are Eastern Europe where populations are already in sharp decline and China, where deaths begin to exceed births in the 2030s. Although life expectancy is rising, death rates in the developed world will rise simply because the rapidly growing number of old people more than offsets the impact of longer lifespans. Of course, the population of a country can also be boosted by immigration, and that has been true for much of the developed world. In Canada and most of Europe, net migration already is the dominant source of overall population growth and it will become so in the U.S. in the coming decades, based on current trends (Chart II-4). This is the background to the first key issue addressed in this report: the declining trend in the growth of the working-age population in the developed world. Slowing Growth In Working-Age Populations An economy’s growth potential depends on only two things: the number of people working and their productivity. If the labor force grows at 1% a year and productivity also increases by 1%, then the economy’s trend growth rate is 2%. In the short-run, the economy may grow faster or slower than that, depending on issues like fiscal and monetary policy, oil prices etc. Over the long run, growth is constrained by people and productivity. The potential labor force is generally regarded to be the people aged 15 to 64. The growth trend in this age segment has slowed sharply in recent years in the major economies and is set to weaken further in the years ahead (Chart II-5). The problem is most severe in Japan and Europe where the working-age population is already declining. In the case of the U.S., growth in this age cohort slows from an average 1.5% a year in the 1960s and 1970s to a projected pace of less than 0.5% in the coming decades. While this generally is not a problem faced by the developing world, a notable exception is China, now reaping the consequences of its one-child policy. Its working-age population is set to decline steadily in the years ahead. Thus, it is inevitable that Chinese growth also will slow in the absence of an acceleration of productivity growth The slowing trend in the working-age population could be offset if we could get more 15-64 year olds to join the labor force, or get more older people to stay working. In the U.S., almost 85% of male 15-64 year olds were either employed or were wanting a job in the mid-1990s. This has since dropped to below 80% - a marked divergence from the trend in most other countries (Chart II-6). And the female participation rate in the U.S. also is below that of other countries. The reason for the decline in U.S. labor participation rates for prime-aged adults is unclear. Explanations include increased levels of people in full-time education, in prison, or claiming disability. A breakdown of male participation rates by age shows particularly sharp drops in the 15-19 and 20-24 age groups, though the key 20-54 age category also is far below earlier peaks (Chart II-7). The U.S. participation rate has recently picked up but it seems doubtful that it will return to earlier highs. Other solutions to the problem would be getting more people aged 65 and above to stay in the labor force, and/or faster growth in productivity. The former probably will require changes to the retirement age and we will return to that issue shortly. There always are hopes for faster productivity growth, but recent data have remained disappointing for most developed economies (Chart II-8). New technologies hold out some hope but this is a contentious topic. On a positive note, the shrinking growth of the working-age population may be easier to live with in a world of robotization and artificial intelligence where machines are expected to take over many jobs. That would support a more optimistic view of productivity but it remains to be seen how powerful the impact will be. Another important problem related to the slowing growth of the working-age population relates to fiscal burdens. In 1980, the level of government debt per taxpayer (ages 20-64) was around $58,000 in the U.S. in today’s money and this is on track for $104,000 by 2020 (Chart II-9). But this pales in comparison to Japan where it rises from $9,000 to $170,000 over the same period. Canada looks more favorable, rising from $23,000 in 1980 to $68,000 in 2020. These burdens will keep rising beyond 2020 until governments start running budget surpluses. Our children and grandchildren will bear the burden of this and won’t thank us for allowing the debt to build up in the first place. There will be a large transfer of privately-held assets from the baby boomers to the next generation, but the ownership of this wealth is heavily skewed. According to one study, the top 1% owned 40% of U.S. wealth in 2016, while the bottom 90% owned 20%.2 And it seems likely that this pool of wealth will erode over time, providing a smaller cushion to the following generation. This leads in to the next topic – aging populations. Aging Populations In The Developed World The inevitable result of the combination of increased life expectancy and declining birth rates has been a marked aging of populations throughout the developed world. Between 2000 and 2050, the developed world will see the number of those aged 65 and over more than double while the numbers in other age groups are projected to show little change (Chart II-10). As long as the growing numbers of those aged 65 and above are in decent health, then life is quite good. Fifty years ago in the U.S., poverty rates were very high for those of retirement age compared to the young (i.e. under 18). But that has changed as the baby boomer generation made sure that they voted for increased entitlement programs. Now poverty rates for the 65+ group are far below those of the young (Chart II-11). At the same time, real incomes for those 65 and older have significantly outperformed those of younger age groups. A major problem is that aging baby boomers are expensive because of the cost of pensions and medical care. As would be expected, health care costs rise dramatically with age. For those aged 44 and under, health care costs in the U.S. averaged around $2,000 per person in 2015. For those 65 and over, it was more than $11,000 per person. And per capita spending doubles between the ages of 70 and 90. So here we have the problem: a growing number of expensive older people supported by a shrinking number of taxpayers. This is illustrated by the ratio of the number of people between 20 and 64 divided by those 65 and older. In other words, the number of taxpayers supporting each retiree (Chart II-12). In 1980, there were five taxpayers for every retiree in the U.S., four in W. Europe and seven in Japan. These ratios have since dropped sharply, and in the next few decades will be down to 2.5 in the U.S., 1.8 in Europe and 1.3 in Japan. For each young Japanese taxpayer, it will be like having the cost of a retiree deducted from their paycheck. Throughout the developed world, the baby boomers’ children and grandchildren face a growing burden of entitlements. Some of the statistics related to Japan’s demographics are dramatic. In the first half of the 1980s there were more than twice as many births as deaths (Chart II-13). They become equal around ten years ago and in another ten years deaths are projected to exceed births by around three million a year. In 1990, the number of people aged four and under was more than double the number aged 80 and above. Now the situation is reversed with those aged 80 years and above more than double those four and under. That is why sales of adult diapers reportedly exceed those of baby diapers – very depressing!3 What’s the solution to aging populations? An obvious one is for people to retire later. When pension systems were set up, life expectancy at birth was below the age pensions were granted - typically around 65. In other words, not many people were expected to live long enough to get a government pension. And the lucky ones who did live long enough were not expected to be around to receive a pension for more than a few years. By 1950, those males who had reached the age of 65 were expected, on average, to live another 11 to 13 years in the major developed countries (Table II-2). This rose to 16-18 years by 2000 and is expected to reach 22-23 years by 2050. Governments have made a huge error in failing to raise the retirement age as life expectancy increased. Pension systems were never designed to allow people to receive government pensions for more than 20 years. Some countries have raised the retirement age for pensions, but progress on this front is painfully slow. Other solutions would be to raise pension contributions or to means-test benefits. Not surprisingly, governments are reluctant to take such unpopular actions. At some point, they will have no choice, but that awaits pressures from the financial markets. Currently, not many people aged over 65 remain in the workforce. The participation rate for men is less than 10% in Europe and less than 25% in the U.S. And it is a lot lower for women (Chart II-14). The rate in Japan is much higher reflecting the fact that it is at the leading edge of aging. Participation rates are moving higher in Europe and the U.S. and further increases are likely in the years ahead if Japan’s experience is anything to go by. Having people staying in the workforce for longer will help offset the decline in prime-age workers, but there is a downside. While it is a contentious topic, many studies point to a negative correlation between age and productivity after the age of 50. As we age, there is some decline in cognitive abilities and older people may be less willing or able to adapt to new technologies and working practices. These would only be partly offset by the benefits of experience that comes with age. Therefore, an aging workforce is not one where one would expect productivity growth to accelerate, other things being equal. An IMF study concluded that a 1% increase in the labor force share of the 55-64 age cohort in Europe could reduce the growth in total factor productivity by 0.2% a year over the next 20 years.4 Another study published by the NBER paper estimated that aging will reduce the U.S. economic growth rate by 1.2% a year this decade and 0.6% a year next decade.5 Other studies are less gloomy but it would be hard to argue that aging is actually good for productivity. Another aging-related issue is the implications for asset prices. It is generally believed that aging will be bad for asset prices as people move from their high-saving years to a period where they will be liquidating assets to supplement their incomes. This is supported by a loose correlation between the percentage of the labor force between 35 and 64 (the higher-saving years) and stock market capitalization as a percent of GDP (Chart II-15). However, other studies cast doubts on this relationship.6 One might think real estate is even more vulnerable than stocks to aging. However, in late 1988, two high-profile economists (Greg Mankiw and David Weil) published a report arguing that real house prices would fall substantially over the next two decades as the baby boom generation aged.7 That forecast was catastrophically wrong. Of course, that does not mean that the more dramatic aging occurring over the next couple of decades will not have a major negative impact on home prices. Numerous studies have been carried out on the relationship between demographics and asset prices and the conclusions are all over the place.8 Time and space constraints prevent a more in-depth discussion of this topic. Nonetheless, common sense would suggest that aging is more likely to be bearish than bullish for asset prices. Thus far, we have addressed two demographic challenges facing the developed world: slowing growth in the number of working-age people and a marked aging of the population. Much of the developing world has the opposite issue: continued rapid population growth and large numbers of young people. This is my third topic. Rapid Population Growth In The Developing World We already noted that nearly all future growth in global population will occur in the developing world, China being a notable exception. With birth rates remaining far above death rates, emerging countries will not have the aging problem of the developed world and this has some positives and negatives. On the positive side, a rapidly-growing young population creates the potential for strong economic growth – the opposite of the situation in advanced economies. But this assumes that the institutional and political framework is conducive to growth. Unfortunately, the history of many developing countries is that corrupt and incompetent governments prevent economies from ever reaching their potential. This means there will be a growing pool of young people likely facing a dim economic future. In some cases, these young people could be an excellent recruiting ground for extremist groups. It is unfortunate that there is particularly rapid population growth in some of the most troubled countries in the world. The Institute for Economics and Peace ranks countries by whether they are safe or dangerous.9 According to their ranking, the eight most dangerous countries in the world will see their population grow at a much faster pace than the developing world as a whole (Chart II-16). Some individual country comparisons are striking. The UN’s projections show that Nigeria’s population will exceed that of the U.S. by 2050, The Democratic Republic of Congo’s population will match that of Japan by 2030 and by 2050 will be 80% larger (Chart II-17A and B). Similarly, Afghanistan will overtake Italy in the 2040s. Most incredibly, Africa’s overall population surpassed that of the whole of Europe in the second half of the 1990s and is projected to be 3.5 times larger by 2050. That suggests that the numbers seeking to migrate from Africa to Europe will increase dramatically in the next couple of decades. Controlling these flows will become an increasing challenge for countries in Southern Europe. Migration is the logical solution to declining working-age populations in the developed world and expanding young populations in the developing world. However, there currently is a backlash against immigration in many developed countries. Anti-immigration political parties are gaining strength in many European countries and immigration was a major factor influencing the Brexit vote in the U.K. And it is a hot-button political issue in the U.S. Concerns about immigration are twofold: competition for employment and potential cultural change. Employment fears have coincided with a long period of severely depressed wages for low-skill workers in many developed economies and immigration is an easy target for blame. Meanwhile, the cultural challenge of absorbing large numbers of immigrants clearly has fueled increased nationalist sentiment in a number of countries. In the U.S., projections by the Bureau of the Census show that the non-Hispanic white population will fall below 50% of the total by 2045. That has implications for voting patterns and lies behind some of the concerns about high levels of immigration. There is no simple solution to this controversial issue and an in-depth discussion is beyond the scope of this article. Conclusions We have only touched on some aspects of demographic trends. It is a huge topic and has many other implications. For example, the political and cultural views of each generation are shaped by the environment they grow up in and this changes over time. This year, the number of millennials (those born from the early 1980s to the mid-1990s) in the U.S. is expected to surpass those of baby boomers and that will have important political and social implications. Again, that is beyond the scope of this report. The demographic trends we have discussed will pose serious challenges to policymakers. In the developed world, the baby boom generation has accumulated huge amounts of government debt, partly to fund generous entitlement programs and did not have enough children to ease the burdens on future generations. The young have good reason to feel frustrated by the actions of their elders (see cartoon). In the developing world, the challenge will be to provide economic opportunities for a growing pool of young people. The biggest problems will be in Africa, a continent where economic success stories have been few and far between in the past. Failure to deal with this will have troubling implications for geopolitical stability. Martin H. Barnes Senior Vice President Economic Advisor III. Indicators And Reference Charts Our tactical equity upgrade is beginning to pay off, and an increasing proportion of our proprietary indicators is confirming that stocks have more upside over the next few quarters. Our Willingness-to-Pay (WTP) indicator for the U.S. has stopped falling. This pattern is also evident in both Europe and Japan. The WTP indicators track flows, and thus provide information on what investors are actually doing, as opposed to sentiment indexes that track how investors are feeling. After clearly pulling funds out of the equity markets, investors are beginning to tip their toes back in. Our Revealed Preference Indicator (RPI) has clearly shifted back into stocks. The RPI combines the idea of market momentum with valuation and policy measures. It provides a powerful bullish signal if positive market momentum lines up with constructive signals from the policy and valuation measures. Conversely, if constructive market momentum is not supported by valuation and policy, investors should lean against the market trend. According to BCA’s composite valuation indicator, the U.S. stock market remains overvalued from a long-term perspective, despite the dip in multiples since last fall. It is a composite of 11 different valuation measures. Moreover, our Monetary Indicator has shifted out of negative territory for stocks, and is now decisively in stimulative territory. The Fed pause, along with some dovish-sounding commentaries have improved the monetary backdrop by removing expected rate hikes from the money market curve. Our Composite Technical indicator for stocks broke down in December, providing a clear ‘sell’ signal, and has not yet delivered a ‘buy’. However, if the recent improvement in this indicator can continue, the S&P 500 will likely be able to punch above the 2800 level. The 10-year Treasury yield is in the neutral range according to our valuation model. Bonds are not overbought, but they have now fully worked out their previously deeply-oversold conditions. The Adrian, Crump & Moench formulation of the 10-year term premium remains close to its 2016 nadir, suggesting that yields are unsustainably low. Our bond-bearish bias is consistent with the view that the Fed rate hike cycle is not over. The U.S. dollar is still very expensive on a PPP basis. Our Composite Technical Indicator is not as overbought as it once was, but it is far from having reached oversold levels either. This combination suggests that the greenback could experience further downside over the coming month. It remains to be seen if this wave of depreciation will mark the beginning of the cyclical bear market required to correct the dollar’s overvaluation. EQUITIES: FIXED INCOME:     CURRENCIES:   COMMODITIES:   ECONOMY: Mark McClellan Senior Vice President The Bank Credit Analyst   Footnotes 1       Most of the data referred to in this report comes from the medium variant projections from the United Nation’s World Population Prospects report, 2017 revision. There is an excellent online database tool that allows users to access numerous demographic series for every country and region in the world. This can be found at https://population.un.org/wpp/DataQuery/ 2       Edward N. Wolff, Household Wealth Trends in the United States, 1962 to 2016. NBER Working Paper 24085, November 2017. Available at: https://www.nber.org/papers/w24085. 3       This is not a joke: https://www.businessinsider.com/signs-japan-demographic-time-bomb-2017-3 4       The Impact of Workforce Aging on European Productivity. IMF Working Paper, December 2016. Available at: https://www.imf.org/en/Publications/WP/Issues/2016/12/31/The-Impact-of-Workforce-Aging-on-European-Productivity-44450 5       The Effect of Population Aging on Economic Growth, the Labor Force and Productivity. NBER Working Paper 22452, July 2016. Available at https://www.nber.org/papers/w22452.pdf 6              For example, see “Will Grandpa Sink The Stock Market?”, The Bank Credit Analyst, September 2014. 7       The Baby Boom, The Bay Bust, and the Housing Market. NBER Working Paper 2794. Available at: https://www.nber.org/papers/w2794 8       For those interested in this topic, we recommend the following paper: Demographics and Asset Markets: A Survey of the Literature. Available at: https://pdfs.semanticscholar.org/912a/5d6d196c3405e37b3a50d797cbf65a27ba44.pdf 9       Global Peace Index, 2018. Available at: http://visionofhumanity.org/app/uploads/2018/06/Global-Peace-Index-2018-2.pdf. According to this index, the eight least-safe countries are (starting with the most dangerous): Syria, Afghanistan, South Sudan, Iraq, Somalia, Yemen, Libya, and Democratic Republic of the Congo. EQUITIES:FIXED INCOME:CURRENCIES:COMMODITIES:ECONOMY:

Highlights The global shipping-fuels market will tighten as UN-mandated fuel standards kick in next year. This will keep ship fuels, known as bunkers, and other distillate prices – e.g., diesel and jet fuel – elevated relative to other refined products like gasoline. In turn, this will boost demand for lighter, sweeter crudes – particularly Brent and similar grades – that allow refiners to raise distillate yields, as they scramble to meet higher demand for low-sulfur ship-fuel next year. After pipeline expansions in the Permian Basin come on line later this year, WTI exports should provide the marginal light-sweet barrel refiners will need to raise distillate output next year. Light-sweet exports from the U.S. will find a ready home in the Atlantic Basin and Asia, as demand for shipping fuels – along with other distillates– rises. Still, the ramp in WTI exports from the U.S. will be hampered by a lack of deep-water ports that can accommodate very large crude carriers (VLCCs) used to ship crude oil globally. As a result, we expect the light-sweet crude market ex-U.S. to tighten. Given this expectation, we are extending our long July 2019 Brent vs. short July 2020 Brent recommendation – up 240.2% since inception January 3 – to long 2H19 Brent vs. short 2H20 Brent. Highlights Energy: Overweight. In line with our expectation, OPEC is showing no sign of agreeing to raise production less than two months after initiating output cuts to drain inventories. Separately, Muhammadu Buhari was re-elected for a second four-year term as Nigeria’s president. The main opposition party rejected the results, following record-low voter turnout, after elections were unexpectedly delayed by one week, according to the BBC. Base Metals/Bulks: Neutral. The prompt March copper contract on the CME’s COMEX is attempting to fill a gap just above $2.95/lb, which opened in July 2018 as U.S. – China trade tensions rose. Positive signals from Sino – U.S. trade talks are supporting prices. Precious Metals: Neutral. Palladium traded to a record high of $1,536.50/oz Monday, pushing it more than $200/oz over gold. Platinum prices also rallied, as South African miners were notified by labor unions of intended strikes next week. Russia’s leading producer, Norilsk Nickel, which accounts for 40% of global palladium production, expects an 800k-ounce physical deficit in 2019, according to Reuters. Ags/Softs: Underweight. U.S. President Donald Trump said he would delay increasing U.S. tariffs on Chinese imports. Trump also said he expects to meet China’s President Xi Jinping to conclude the trade deal they’ve been negotiating if both sides continue to make progress. Feature Maritime shipping represents ~ 80% of international trade, and is responsible for roughly 90% of the total sulfur emissions from the transportation sector. In 2008, the UN’s International Maritime Organization (IMO) adopted a new regulation to reduce the cap for sulfur content of ships’ fuel oil – known as bunker fuel – to 3.5% from 4.5% in 2012, and to 0.5% from 3.5% in 2020 (Chart 1).1 Chart of the WeekReducing Marine Sulfur Pollution Requires Higher-Priced Low-Sulfur Fuels Around 50% of the cost of shipping is fuel costs. This amounts to more than 4mm b/d of bunker fuel (~ 3.5mm b/d of High-Sulfur Fuel Oil, or HSFO, and ~ 0.8mm b/d of marine gasoil, known as MGO). Hence, the IMO 2020 regs threaten demand of ~ 3.5mm b/d of HSFO. As the January 1, 2020, IMO deadline approaches, uncertainty surrounding the new regs remains elevated. On the demand side, shippers have the option to install abatement technology (i.e., scrubbers); burn IMO 2020-compliant fuels like MGO; use liquefied natural gas (LNG) as a fuel on ships; or do nothing, i.e., not comply with the regulation. Refiners on the supply side have to adjust via a combination of increasing MGO and Low-Sulfur Fuel Oil (LSFO) production; modifying their crude slates, which will favor lighter, sweeter crudes like Brent and WTI; building additional refining capacity; or running their units harder – i.e., increase refinery utilization rates – to produce more fuel. Demand for bunkers is the only part of the HSFO market that is growing. IMO 2020 removes the all-important shipping consumer of residual fuel oil, which will have a major impact on simple refineries, and will force a dramatic reconfiguration of the shipping and refining industries. To date, shippers and refiners have been slow to implement required changes as market participants have an incentive to move last.2 We agree with a recent McKinsey analysis, which notes the simplest solution for shippers is to switch to MGO.3 We also could see an uptick in demand for LSFO with sulfur content below the 0.5% limit for blending purposes. This would push demand for the lower-sulfur fuels and prices up. It also would pressure HSFO prices lower over the short term, to the point where this fuel can compete in the utility sector as a fuel, or in the refining sector as a charging stock for complex refiners. The IEA expects MGO consumption to rise from 0.8mm b/d to 1.7mm b/d in 2020.4 Complex Refiners, Light-Sweet Crude Producers Benefit Moving to LSFO and MGO shifts the burden of IMO 2020 to the refining market. According to the IEA, around 80% of the sulfur content in crude is removed from the final product. Once IMO 2020 is implemented, this will rise to 90%. In the lead-up to the IMO 2020 deadline, refiners are adjusting their crude slates to minimize residual fuel and maximize distillate output. As a result, demand for light-sweet crudes like Brent and WTI – the crude being produced in ever-rising quantities in the U.S. shales – will increase. At the same time, heavier crudes exported by Venezuela and GCC states will see demand fall, which means the spread between these crudes will favor the lighter, sweeter barrel, all else equal.5 Simple refineries incapable of cracking the complex heavy-sour crudes favored by U.S. Gulf Coast refiners will either have to upgrade, close, or use low-sulfur crude as a charging-stock input. According to McKinsey, the switch to marine gasoil will lead to an increase of 1.5mm b/d of distillate demand. This represents ~ 2.2 to 2.7mm b/d of increased demand for light-sweet oil. The IEA estimates diesel prices could rise by 20 – 30%, as a result.6 This increased demand for low-sulfur bunkers – MGO in particular –will keep prices for distillates generally well supported over the next year or so at the expense of HSFO. S&P Global Platts reported this week the first physical trade for U.S. Gulf Coast 0.5% MGO was done in its official trading window at $67.70/bbl, a $3.75/bbl premium to HSFO.7 IMO 2020 will keep distillates the star performers for refiners. Distillate crack spreads – most visible in the ultra-low-sulfur diesel (ULSD) cracks employing the CME’s NY Harbor ULSD futures vs. WTI and Brent – recently were trading $16/bbl over gasoline cracks using the Exchange’s RBOB futures (Charts 2A and 2B). We expect these cracks to remain wide, to incentivize more distillate-production capacity. Chart 2ABrent Diesel And Gasoline Cracks Likely Trade > $14/bbl Wide Chart 2BBrent Diesel Cracks Will Remain Elevated Following IMO 2020 Prices for other distillates also will be supported by IMO 2020 – e.g., jet fuel – over the coming year, given the high correlation of products within this cut of the barrel. These distillate prices also are highly correlated with Brent and WTI prices, as can be seen in Chart 3, and in Tables 1 and 2. These high correlations likely will persist as IMO 2020 is implemented, and hedgers seek out liquid markets in which to shed their price risk.8 Chart 3Global Distillate Prices Will Be Supported by IMO 2020Table 1Distillate Fuels’ Correlations Remain High Around The WorldTable 2Percent Changes In Distillates Also Are Highly Correlated Baker & O’Brien, an energy consultancy based in Dallas, Texas, expects a number of factors – ranging from non-compliance with IMO 2020; increased use of scrubbers to capture sulfur-oxide emissions; blending to make IMO 2020-compliant marine fuel; upgrades by refiners and changes in their crude slates – will lead to lower prices once the market adjusts to the new regs.9 We do not disagree, but the timing on this likely hinges on how quickly U.S. light-sweet crude oil exports ramp up. Investment Implications WTI exports – actually LTO exports from U.S. shales – will provide the marginal light-sweet barrel refiners will need to raise distillate output next year. As a result, LTO exports from the U.S. will find a ready home in the Atlantic Basin and Asia, as demand for low-sulfur shipping fuels increases. However, this will not happen overnight. At present WTI exports from the U.S. are hampered by a lack of deep-water ports that can accommodate the VLCCs used to ship crude oil. The 2mm b/d of expanded pipeline capacity out of the Permian by the end of this year will move the U.S. crude-oil bottleneck from the Permian to the U.S. Gulf.10 So, as refiners prepare this year for the IMO 2020 regs effective January 1, 2020, the light-sweet crude market ex-U.S. – particularly Brent– will tighten. This already is visible in the backwardation we were expecting at the beginning of this year, when we recommended getting long July 2019 Brent vs. short July 2020 Brent, which is up 240.2% since inception on January 3. Given our expectation for a tighter light-sweet crude market ex-U.S., we are liquidating our existing Brent 2019 long position vs. a short position in July 2020 at tonight’s close, and replacing it with a long 2H19 Brent vs. a short 2H20 Brent position.11 Bottom Line: The implementation of IMO 2020 will tighten marine fuels markets globally, as refiners increase their demand for light-sweet crude oil and shippers most likely increase their demand for MGO and lower-sulfur fuels generally.     Robert P. Ryan, Senior Vice President Commodity & Energy Strategy rryan@bcaresearch.com Hugo Bélanger, Senior Analyst Commodity & Energy Strategy HugoB@bcaresearch.com   Footnotes 1      The regulation is part of Annex VI to the International Convention for the Prevention of Pollution from Ships (MARPOL). Following the adoption of the regulation in 2008, a provision was kept in order to review the compliant fuel availability and possibly push the implementation to 2025. In October 2016, the IMO’s Marine Environment Protection Committee confirmed the final implementation date (January 1, 2020) following a positive assessment of the availability for shippers of compliant fuels. Any amendment to MARPOL needs to be circulated for a minimum of six months, and can only be implemented 16 months after adoption, therefore, no legal amendment to the current January 2020 date are possible. Please see https://www.iea.org/etp/tracking2017/internationalshipping/ 2      The slow response by refiners can be explained by: (1) the fact that a switch to LSFO or MGO prior to the actual deadline would lead to a financial loss due to the current high price of LSFO and MGO vs. HSFO; (2) abatement technology requires large upfront investments (i.e. capital cost of new processing units, storage tanks, loss of revenue from laying ships in dry dock while they are retrofitted, and a permanent loss of deck space and loading capacity to the new equipment); and (3) the unpredictability of fuel prices and the endogenous relationship between other shippers and the behavior of prices. In other words, trying to get out in front of the official implementation of IMO 2020 leads to unnecessary financial burdens and to competitive disadvantage. Please see Halff, Antoine, Lara Younes, Tim Boersma (2019), “The Likely Implications of the new IMO standards on the shipping industry.”  Energy Policy, 126: 277 - 286. 3      Please see “IMO 2020 and the outlook for marine fuels,” published by McKinsey & Company, September 2018.  S&P Global Platts reaches a similar conclusion in a report entitled “Turning tides, the future of fuel oil after IMO 2020,” which was released this month.  Platts notes, “The IMO’s lower sulphur cap is set to take away the bulk of marine fuel oil demand from the start of next year.  Most ship owners and operators will switch to burning new low-sulfur bunker blends, translating into an almost overnight shift of 3 million b/d of demand.” 4      The IEA expects 30% of the current HSFO bunker demand will switch to marine gasoil (MGO), 30% of the HSFO bunker demand will switch to the new ultra low 0.5% sulphur fuel (ULSFO), and 40% of HSFO bunker demand will remain.)  In the IEA’s modeling, this could push prices up by as much as 30%.  Please see “Oil 2018: Analysis and forecasts to 2023” published by the IEA. It is available at iea.org 5      Please see “IMO 2020 and the Brent – Dubai Spread,” published by The Oxford Institute For Energy Studies in September 2018.  Of course, reducing the export of heavy-sour crudes, as has been done by the Gulf Arab members of OPEC will keep the Brent – Dubai spread tighter than pure economics would dictate. 6      Please see sources in footnotes 3 and 4. 7      This trade was done in the Platts Market on Close assessment.  Please see “USGC Marine Fuel 0.5% has first physical trade in Platts MOC process,” published by S&P Global Platts February 26, 2019. 8      These are short-term correlations, which use daily data from 2017 to now. We present correlations in levels and in percent-changes, given these are cointegrated variables. Please see section 3.3 of “Correlation, regression, and cointegration of nonstationary economic time series,” by Soren Johansen, published November 6, 2007, by the Center for Research in Econometric Analysis of Time Series at the University of Aarhus. 9      Please see “The Thunder Rolls – IMO 2020 And The Need For Increased Global Oil Refinery Runs (Part 3)” published by Baker & O’Brien, December 11, 2018. 10     An additional 1mm b/d of new takeaway is scheduled for 1H21, following a final investment decision from an Exxon-led group that will move Permian Basin LTO to the U.S. Gulf.  This came one day after Exxon FID’d a 250k b/d buildout of its Beaumont refinery in Houston, which will increase capacity by more than 65%, Natural Gas Intelligence reported January 30. 11     Please see EIA’s This Week in Petroleum report titled “Upcoming changes in marine fuel sulfur limits will affect crude oil and petroleum product markets,” published January 16, 2019. Investment Views and Themes Recommendations Strategic Recommendations Tactical Trades Commodity Prices and Plays Reference Table   Trades Closed in Summary of Closed Trades

Highlights It may seem self-evident that most governments are overly indebted, but both theory and evidence suggest otherwise. Higher debt today does not require higher taxes tomorrow if the growth rate of the economy exceeds the interest rate on government bonds. Not only is that currently the case, but it has been the norm for most of history. Unlike private firms or households, governments can choose the interest rate at which they borrow, provided that they issue debt in their own currencies. Ultimately, inflation is the only constraint to how large fiscal deficits can get. Today, most governments would welcome higher inflation. There are increasing signs China is abandoning its deleveraging campaign. Fiscal policy will remain highly accommodative in the U.S. and will turn somewhat more stimulative in Europe. Remain overweight global equities/underweight bonds. We do not have a strong regional equity preference at the moment, but expect to turn more bullish on EM versus DM by the middle of this year. Feature A Fiscal Non-Problem? Debt levels in advanced economies are higher today than they were on the eve of the Global Financial Crisis. Rising private debt accounts for some of this increase, but the lion’s share has occurred in government debt (Chart 1). Chart 1Global Debt Levels Have Risen, Especially In The Public Sector Not surprisingly, rising public debt levels have elicited plenty of consternation. While there has been a lively debate about how fast governments should tighten their belts, few have disputed the seemingly self-evident opinion that some degree of “fiscal consolidation” is warranted. Given this consensus view, one would think that the economic case for public debt levels being too high is airtight. It’s not. Far from it. Debt Sustainability, Quantified Start with the classic condition for debt sustainability, which specifies the primary fiscal balance (i.e., the overall balance excluding interest payments) necessary to maintain a constant debt-to-GDP ratio (See Box 1 for a derivation of this equation).   An increase in the economy’s growth rate (g), or a decrease in real interest rates (r), would allow the government to loosen the primary fiscal balance without causing the debt-to-GDP ratio to increase (Chart 2).1 If the government were to ease fiscal policy beyond that point, debt would rise in relation to GDP. But by how much? It is tempting to assume that the debt-to-GDP ratio would then begin to increase exponentially. However, that is only true if the interest rate is higher than the growth rate of the economy. If the opposite were true, the debt-to-GDP ratio would rise initially but then flatten out at a higher level.2 A Fiscal Free Lunch The last point is worth emphasizing. As long as the interest rate is below the economic growth rate, then any primary fiscal balance – even a permanent deficit of 20%, or even 30% of GDP – would be consistent with a stable long-term debt-to-GDP ratio. In such a setting, the government could just indefinitely rollover the existing stock of debt, while issuing enough new debt to cover interest payments. No additional taxes would be necessary. In fact, stabilizing the debt-to-GDP ratio becomes easier the higher it rises. Chart 3 shows this point analytically.    Ah, one might say: If the government issues a lot of debt, then interest rates would rise, and before we know it, we are back in a world where the borrowing rate is above the economy’s growth rate, at which point the debt dynamics go haywire. Now, that sounds like a sensible statement, but it is actually quite misleading. As long as a government is able to issue its own currency, it can always create money to pay for whatever it purchases. If people want to turn around and use that money to buy bonds, they are welcome to do so, but the government is under no obligation to pay them the interest rate that they want. If they do not wish to hold cash, they can always use the cash to buy goods and services or exchange it for foreign currency. As long as a government is able to issue its own currency, it can always create money to pay for whatever it purchases. Wouldn’t that cause inflation and currency devaluation? Yes, it might, and that’s the real constraint: What limits the ability of governments with printing presses to run large deficits is not the inability to finance them. Rather, it is the risk that their citizens will treat their currencies as hot potatoes, rushing to exchange them for goods and services out of fear that rising prices will erode the purchasing power of their cash holdings. When Is Saving Desirable? The reason governments pay interest on bonds is because they want people to save more. However, more savings is not necessarily a good thing. This is obviously the case when an economy is depressed, but it may even be true when an economy is at full employment. Just like someone can work so much that they have no time left over for leisure, or buy a house so big that they spend all their time maintaining it, it is possible for an economy to save too much, leading to an excess of capital accumulation. Under such circumstances, steady-state consumption will be permanently depressed because so much of the economy’s resources are going towards replenishing the depreciation of the economy’s capital stock.  Economists have a name for this condition: “dynamic inefficiency.” What determines whether an economy is dynamically inefficient? As it turns out, the answer is the same as the one that determines whether debt ratios are on an explosive path or not: The difference between the interest rate and the economy’s growth rate. Economies where interest rates are below the growth rate will tend to suffer from excess savings. In that case, government deficits, to the extent that they soak up national savings, may increase national welfare.   r < g Has Been The Norm Today, the U.S. 10-year Treasury yield stands at 2.69%, compared to the OECD’s projection of nominal GDP growth of 3.8% over the next decade. The gap between projected growth and bond yields is even greater in other major economies (Chart 4). Granted, equilibrium real rates are likely to rise over the next few years as spare capacity is absorbed. Structural factors might also push up real rates over time. Most notably, the retirement of baby boomers could significantly curb income growth, leading to a decline in national savings. Chart 5 shows that the ratio of workers-to-consumers globally is in the process of peaking after a three-decade long ascent. Economic growth could also fall if cognitive abilities continue to deteriorate, a worrying trend we discussed in a recent Special Report.3 Chart 5The Global Worker-To-Consumer Ratio Has Peaked It may take a while before real rates rise above GDP growth. Still, it may take a while before real rates rise above GDP growth. As Olivier Blanchard, the former chief economist at the IMF, noted in his Presidential Address to the American Economics Association earlier this year, periods in U.S. history where GDP growth exceeds interest rates have been the rule rather than the exception (Chart 6).4 The same has been true for most other economies.5 Chart 6GDP Growth Above Interest Rates: Historically, The Rule, Not The Exception What’s Next For Fiscal Policy? Austerity fatigue has set in. In the U.S., fiscally conservative Republicans, if they ever really existed, are a dying breed. Trump’s big budget deficits and his “I love debt” mantra are the waves of the future. For their part, the Democrats are shifting to the left, with the “Green New Deal” proposal being the latest manifestation. The case for fiscal stimulus is stronger in the euro area than for the United States. The European Commission expects the euro area to see a positive fiscal thrust of 0.40% of GDP this year, up from a thrust of 0.05% of GDP last year (Chart 7). This should help support growth. Chart 7The Euro Area Will Benefit From A Modest Amount Of Fiscal Easing This Year Additional fiscal easing would be feasible. This is clearly true in Germany, but even in Italy, the cyclically-adjusted government primary surplus is larger than what is necessary to stabilize the debt ratio.6 Unfortunately, the situation in southern Europe is greatly complicated by the ECB’s inability to act as an unconditional lender of last resort to individual sovereign borrowers. When a government cannot print its own currency, its debt markets can be subject to multiple equilibria. Under such circumstances, a vicious spiral can develop where rising bond yields lead investors to assign a higher default risk, thus leading to even higher yields (Chart 8).   Mario Draghi’s now-famous “whatever it takes” pledge has gone a long way towards reassuring bond investors. Nevertheless, given the political constraints the ECB faces, it is doubtful that Italy or other indebted economies in the euro area will be able to pursue large-scale stimulus. Instead, the ECB will keep interest rates at exceptionally low levels. A new round of TLTROs is also looking increasingly likely, which should protect against a rise in bank funding costs and a potential credit crunch. Our European team believes that a TLTRO extension would be particularly helpful to Italian banks.  Even in Italy, the cyclically-adjusted government primary surplus is larger than what is necessary to stabilize the debt ratio. Despite having one of the highest sovereign debt ratios in the world, Japan faces no pressing need to tighten fiscal policy. Instead of raising the sales tax this October, the government should be cutting it. A loosening of fiscal policy would actually improve debt sustainability if, as is likely, a larger budget deficit leads to somewhat higher inflation (and thus, lower real borrowing rates) and, at least temporarily, faster GDP growth. We expect the Abe government to counteract at least part of the sales tax increase with new fiscal measures, and ultimately to abandon plans for further fiscal tightening over the next few years. In the EM space, Brazil, Turkey, and South Africa are among a handful of economies with vulnerable fiscal positions. They all have borrowing rates that exceed the growth rate of the economy, cyclically-adjusted primary budget deficits, and above-average levels of sovereign debt (Chart 9).   In contrast, China stands out as having the biggest positive gap between projected GDP growth and sovereign borrowing rates of any major economy. The problem is that the main borrowers have been state-owned companies and local governments, neither of which are backstopped by the state. Not officially, anyway. Unofficially, the government has been extremely reluctant to allow large-scale defaults anywhere in the economy. Despite all the rhetoric about market-based reforms, they are unlikely to start now. Historically, the Chinese government has allowed credit growth to reaccelerate whenever it has fallen towards nominal GDP growth. As we recently argued in a report entitled “China’s Savings Problem,” China needs more debt to sustain aggregate demand.7 Historically, the government has allowed credit growth to reaccelerate whenever it has fallen towards nominal GDP growth (Chart 10). The stronger-than-expected jump in credit origination in January suggests that we are approaching such an inflection point. Chart 10Historically, China Has Scaled Back On Deleveraging When Credit Growth Has Fallen Close To Nominal GDP Growth Investment Conclusions The consensus economic view is that deflation is a much harder problem to overcome than inflation. When dealing with inflation, all you have to do is raise interest rates and eventually the economy will cool down. With deflation, however, a central bank could very quickly find itself up against the zero lower bound constraint on interest rates, unable to ease policy any further via conventional means. While this standard argument is correct, it takes a very monetary policy-centric view of macroeconomic policy. When interest rates are low, fiscal policy becomes very potent. Indeed, the whole notion that deflation is a bigger problem than inflation is rather peculiar. Just as it is easier to consume resources than to produce them, it should be easier to get people to spend than to save. People like to spend. And even if they didn’t, governments could go out and buy goods and services directly. Looking out, our bet is that policymakers will increasingly lean towards the ever-more fiscal stimulus. If structural trends end up causing the so-called neutral rate of interest to rise – the rate of interest that is necessary to avoid overheating – policymakers will have no choice but to eventually raise rates and tighten fiscal policy (Box 2). However, they will only do so begrudgingly. The result, at least temporarily, will be higher inflation. Fixed-income investors should maintain below benchmark duration exposure over both a cyclical and structural horizon. Reflationary policies that increase nominal GDP growth will help support equities, at least over the next 12 months. Chart 11 shows that corporate earnings tend to accelerate whenever nominal GDP growth rises. We upgraded global equities to overweight following the December FOMC meeting selloff. While our enthusiasm for stocks has waned with the year-to-date rally, we are sticking with our bullish bias. Chart 11Earnings And Nominal GDP Growth Tend To Move In Lock-Step A reacceleration in Chinese credit growth will put a bottom under both Chinese and global growth by the middle of this year. As a countercyclical currency, the dollar will likely come under pressure in the second half of this year. Until then, we expect the greenback to be flat-to-modestly stronger. The combination of faster global growth and a weaker dollar later this year will be manna from heaven for emerging markets. We closed our put on the EEM ETF for a gain of 104% on Jan 3rd, and are now outright long EM equities. I do not have a strong view on the relative performance of EM versus DM at the moment, but expect to shift EM equities to overweight by this summer.8 Peter Berezin, Chief Global Strategist Global Investment Strategy peterb@bcaresearch.com   Box 1 The Arithmetic Of Debt Sustainability   Box 2 Debt Sustainability And Full Employment: The Role Of Fiscal And Monetary Policy Policymakers should strive to stabilize the ratio of debt-to-GDP over the long haul, while also ensuring that the economy stays near full employment. The accompanying chart shows the tradeoffs involved. The DD schedule depicts the combination of the primary fiscal balance and the gap between the borrowing rate and GDP growth (r minus g) that is consistent with a stable debt-to-GDP ratio. In line with the debt sustainability equation derived in Box 1, the slope of the DD schedule is simply equal to the debt/GDP ratio. Any point below the DD schedule is one where the debt-to-GDP ratio is rising, while any point above is one where the ratio is falling. The EE schedule depicts the combination of the primary fiscal balance and r - g that keeps the economy at full employment. The schedule is downward-sloping because an increase in the primary fiscal balance implies a tightening of fiscal policy, and hence requires an offsetting decline in interest rates. Any point above the EE schedule is one where the economy is operating at less than full employment. Any point below the EE schedule is one where the economy is operating beyond full employment and hence overheating. Suppose there is a structural shift in the economy that causes the neutral rate of interest – the rate of interest consistent with full employment and stable inflation – to increase. In that case, the EE schedule would shift to the right: For any level of the fiscal primary balance, the economy would need a higher interest rate to avoid overheating. The arrows show three possible “transition paths” to a new equilibrium. Scenario #1 is one where policymakers raise rates quickly but are slow to tighten fiscal policy. This results in a higher debt-to-GDP ratio. Scenario #2 is one where policymakers tighten fiscal policy quickly but are slow to raise rates. This results in a lower debt-to-GDP ratio. Scenario #3 is one where the government drags its feet in both raising rates and tightening fiscal policy. As the economy overheats, real rates actually decline, sending the arrow initially to the left. This effectively allows policymakers to inflate away the debt, leading to a lower debt-to-GDP ratio. Note: In Scenario #2, and especially in Scenario #3, the DD line will become flatter (not shown on the chart to avoid clutter). Consequently, the final equilibrium will be one where real rates are somewhat higher, but the primary fiscal balance is somewhat lower, than in Scenario #1.   Footnotes 1          One can equally define the interest rate and GDP growth rate in nominal terms (see Box 1 for details).  2       Japan is a good example of this point. The primary budget deficit averaged 5% of GDP between 1993 and 2010, a period when government net debt rose from 20% of GDP to 142% of GDP. Since then, Japan’s primary deficit has averaged 5.1% of GDP, but net debt has risen to only 156% of GDP (and has been largely stable for the past two years). 3      Please see Global Investment Strategy Special Report, “The Most Important Trend In The World Has Reversed And Nobody Knows Why,” dated February 1, 2019. 4      Olivier Blanchard, “Public Debt And Low Interest Rates,” Peterson Institute for International Economics and MIT American Economic Association (AEA) Presidential Address, (January 2019). 5      Paolo Mauro, Rafael Romeu, Ariel Binder, and Asad Zaman, “A Modern History Of Fiscal Prudence And Profligacy,” IMF Working Paper, (January 2013). 6      The Italian 10-year bond yield is 2.83% while nominal GDP growth is 2.64%. Multiplying the difference by net debt of 118% of GDP results in a required primary surplus of .22% of GDP that is necessary to stabilize the debt-to-GDP ratio. This is lower than the IMF’s 2018 estimate of cyclically-adjusted government primary surplus of 2.14%. 7      Please see Global Investment Strategy Weekly Report, “China’s Savings Problem,” dated January 25, 2019. 8      Please note that my colleague, Arthur Budaghyan, BCA’s Chief EM strategist, remains bearish on both EM and DM equities and expects EM to underperform DM over the coming months. Strategy & Market Trends MacroQuant Model And Current Subjective Scores Tactical Trades Strategic Recommendations Closed Trades        

Special Report

When we first set out to create ETS, we leveraged the vast amount of research on stock market anomalies and started with factors that had a proven track-record. We also wanted to minimize the risk of data mining, and as a result, we decided to keep things simple. We stuck with established metrics, and avoided venturing down the long, windy path of custom metrics and adjustments: the more parameters that are included, the easier it is to find spurious results. We also opted for simple, linear mappings – lower is better, or higher is better. When deviating from this approach, it is easy to lose sight of the big picture and spend time optimizing minute details that will not have a large impact on the overall performance of the model. Fast-forward to 2019. We have a stable model that has performed well out of sample, and we are now comfortable taking a second pass over our factors. We can now analyze each model input in detail to see if we can make any improvements. The first factor under the microscope is the Altman Z-Score. This metric was first developed by Edward I. Altman in 1968 to estimate the probability of bankruptcy over a two-year horizon. It uses various items from a firm’s income statements and balance sheet and combines them using a set of weights to yield the so-called Altman Z-Score.1 Since this metric relies on estimated coefficients for a specific set of data, and given that these coefficients date back to the 60s, we wanted to investigate the possibility of using a more modern model of distress in place of the original Altman-Z score.  Our research process led us to review the academic literature, replicate the most promising results internally, and finally, to implement our own variation of the Altman-Z score given our unique dataset.   A Proxy For Bankruptcy In order to assess the ability of a distress model to predict insolvency, it is necessary to have a historical dataset of failure events. If not, it is impossible to measure the success of a given model. Failure can be defined in several ways, the most obvious of which is a Chapter 7 or Chapter 11 bankruptcy filing, at least in the U.S. To ensure that we captured the maximum possible failure events for our global set of stocks, we avoided the Chapter 7/11 definition and developed a simple market-cap based proxy for bankruptcy. We define the failure event of a firm as the point in time where the market-cap drops to 1% of its historical maximum. We also enforce that this event must occur after the maximum to prevent false failures at the beginning of a firm’s trading history. We found that this definition signals failure at the appropriate time for a selection of large-cap firms known to have experienced distress; a notable example is Enron Corp. (Chart 1). In general, we deem this a reasonable proxy for bankruptcy since the price of shares will drop substantially upon news of insolvency. Ultimately, even though it may, in some cases, flag firms that are technically not bankrupt, for our purposes, we are happy to avoid buying firms that plunge below 1% of their previous valuation peak. Academia To The Rescue? A review of the modern finance literature suggested that the Altman Z-Score, while methodologically sound, still had room for improvement as a distress measure. We anticipated that using a more refined distress model, we could amplify the effect of the existing Altman-Z Factor in ETS. In light of this, our first attempt at replacing the Altman-Z score involved running a logistic regression (logit) model presented in Campbell et al. (2010)2 on the ETS universe of stocks and constructing a new factor based on the output from this model. Following the authors’ methodology, we constructed a set of eight variables (three accounting ratios, and five market-based variables) and computed the probability of failure on our entire historical dataset. The probabilities were then percentile-ranked to construct a score from 0-100%, where firms with a score of 0% correspond to those with the highest probability of failure. This ranking system is consistent with the other ETS factors where lower scores are bad and higher scores are good. Although the model by Campbell et al. worked well for predicting subsequent failure (as judged by our bankruptcy proxy measure), the metric fell short performance-wise when tested within our universe of stocks. In brief, our decile-spread metric3 yielded a negative number, indicating poor separation of returns between deciles. Based on the above, we sought to construct our own distress model using similar methods, but applied to the universe of valid ETS firms. There are several advantages to this approach: First, it prevents errors in the construction of the explanatory variables. For instance, when replicating models found in academic literature, we cannot be sure that we are constructing our variables in the exact same way as reported, and hence we cannot have complete confidence in the accuracy of the computed probabilities of failure. Second, it frees us from the shackles of a complicated model, and we can seek to reduce our own model down to something more computationally tractable, and avoid overfitting the data.  Finally, it allows us to base our model on global stock data, as opposed to the U.S.-centric CRSP/COMPUSTAT dataset used by many academic institutions. Bringing It “In-House” The construction of our own distress model began with an analysis of the variables defined in Campbell et al. First, we wanted to determine which variables showed the strongest deviation between success and failure groups. From the calculation of summary statistics and histograms, the variables that showed the most prominent separations between success and failure groups were Net Income to Market Total Assets (NIMTA), Total Debt to Market Total Assets (TDMTA), monthly excess return (EXRET), and the 3-month standard deviation of daily returns (SIGMA) (Chart 2). Detailed descriptions of the variables are provided in the Appendix. We computed NIMTA, TDMTA, EXRET, and SIGMA at monthly frequencies with the goal of constructing a logit model that would predict failure 12 months into the future. The logit model implies that at time t, the probability of firm i failing in the next 12 months is given by:   where y represents the sequence of success (0) and failure (1) events for each firm at each point in time, x represents the four explanatory variables, and α, β are the parameters to fit. The parameters were fit on a rolling basis to avoid look-ahead bias when constructing a trading strategy based on the outcome of the model. Therefore, at each year-end, we used the trailing success/failure data up to that point to estimate parameters. The fitting yielded intuitive results, suggesting that higher TDMTA, SIGMA and lower NIMTA, EXRET indicate a higher probability of failure (see parameter list in Appendix Table 1). Another positive characteristic of these parameters is that they remain relatively stable throughout time, alluding to the robustness of the model. From visual inspection of the parameters, we see that EXRET has the strongest effect on failure probability, followed by SIGMA, TDMTA, and NIMTA. It is not surprising that EXRET has the strongest effect since it is based on a 12-month trailing weighted average. Therefore, we can expect this variable to capture the prolonged period of descent that firms typically undergo before reaching a bankruptcy event. Indeed, firms in our failure group experienced, on average, a failure event 5 years after reaching peak market cap. As for the remaining variables, it is natural to expect increased volatility and subpar financial statements to signal imminent failure. Model accuracy was tested by looking at its predictions on an individual and aggregate basis. Reassuringly, we found individual examples of large firms with known failure events showing the expected behavior (Chart 3). However, the more significant result is that on average, the model predicts a high probability of failure for the group of true failure firms (N=3213) relative to a random sample of true success firms (Chart 4). Armed with a successful distress model, we then translated the predictions into an ETS factor, giving it a score from 0-100%. Using a relative change condition in the parameters as a guide,4 we chose the factor inception date to be year-end 2004. Since our stock data begins in 1995, this allows for a sufficient “burn-in” time for the distress model to stabilize. The latter is important given the spike in U.S. Chapter 11 filings starting in 2001, which is also captured by our bankruptcy proxy (Chart 5).  With the factor constructed, we replaced the existing Altman-Z factor in the full model, keeping the same initial weight.  As expected, this replacement led to an improvement in the overall model according to our standard performance metrics, which are described in a previous report.5 Specifically, we observed a 6% improvement in the decile ordering metric (DECORD) and a small (<1%) reduction in mean absolute difference in BCA Score (MAD), leading to a 7% increase in our overall risk-reward ratio (DECORD / MAD). The new factor, simply named Distress on the platform, also performs well when examined in isolation. To test this, we ran the equivalent of an equal-weighted, daily-rebalanced backtest on ten deciles separated by the Distress score. Calculating the Sharpe ratio on the decile returns, we observe an increasing trend in the performance of the factor as a function of decile (Chart 6). Therefore, with this factor we obtain the desired separation in performance between deciles on a risk-adjusted basis.  What About Machine Learning? Disclaimer: This section involves a small digression on machine learning One statistical challenge with our success/failure classification problem is that the number of “success” events (i.e. no indication of bankruptcy) greatly outnumbers the failure events. Indeed, with our bankruptcy proxy, approximately 1% of the 3.5 million firm-month observations in our dataset are marked as failures. Despite the small failure rate, classic logistic regression can still provide good results; however, we wished to explore the effectiveness of machine learning techniques in tackling this type of classification problem. The use of machine learning (ML) was motivated by an analogous problem outside the world of stocks, namely the detection of credit card fraud. One can imagine that out of the massive number of credit card transactions registered daily, only a small fraction is actually fraudulent. Now, suppose that for a given period we obtained transaction data that includes characteristics such as dollar amount, time of day, and whether or not the transaction was normal or fraudulent. We could then use this prior data to train an ML model to recognize fraudulent transactions when presented with new, out-of-sample data. A specific class of ML models known as “autoencoders” have been shown to be effective in handling this task (See Box 1 for more details). Given that the credit-card problem is directly analogous to our distress problem, we set up a simple autoencoder to test whether it could detect firm failure with a higher degree of accuracy than the logit model. As inputs to the model, we used the same eight variables from Campbell et al. Perhaps surprisingly, we found that the best version of our autoencoder model did not surpass the accuracy of the logit model, at least in terms of maximizing precision and recall simultaneously.6 Furthermore, the predictions of the autoencoder were less effective at separating winners from losers after being transformed into a factor score between 0-100%. This, of course, does not mean that ML techniques are hopeless. It simply means that, for this particular set of parameters and model structure, the autoencoder was not able to provide additional predictive value over the simpler, more computationally efficient logit model.     Box 1 Autoencoders The rise of machine learning has brought with it a slew of jargon that seems intimidating at first, but can actually be understood without extensive training in mathematics or computer science. The term “autoencoder” may very well fall into this category. To get right into it, an autoencoder is a type of neural network tasked with learning a compressed representation of the original input or “training” data. The flow of data through an autoencoder is shown below (Box Diagram 1). The goal of the autoencoder is to optimize the weights connecting nodes in the network so that the difference between the input and output is minimized. However, due to the action of the “reduction” or “encoding” phase of the autoencoder, the output, i.e., the “reconstructed” or “decoded” data, will always be a compressed approximation of the original input. The latter is important for classification problems because it means that post-training, any data presented to the network that does not resemble the original training data will likely be poorly reconstructed, and flagged as anomalous.  Going back to our problem of identifying distressed firms, let’s step through how we use an autoencoder to distinguish between “success” and “failure” groups. Separate the data (i.e., the observations for all accounting and market-based variables) into success and failure groups according to the bankruptcy proxy measure. Train the autoencoder to reconstruct the success group. Each variable of interest corresponds to a node in the “input” layer of the network. Feed the autoencoder the failure group data and record the error in reconstructing this data. Set an error threshold (a number) for determining when a firm should be marked a failure vs. success. Generate predictions based on this threshold. Analyze the accuracy of these predictions using metrics such as precision and recall. Future Work A key priority of the ETS team is to use modern techniques in computing to uncover new sources of alpha for our clients. With the recent explosion of advancements in data science and machine learning, we are excited about leveraging the knowledge from these fields to improve the ETS model. We believe that this report provides a glimpse into the style of factor analysis we expect to conduct in the near future. As for the distress model developed here, we are content with the performance of the simple logistic regression for now, but we will continue to examine whether modern classification techniques can help improve accuracy.  One method in particular that piques our interest is so-called “Gradient Boosting”, which has made big waves in the data science community for its use in winning competitions on Kaggle.com.7 Overall, we will continue to monitor the model’s ability to exploit stock-market anomalies and adjust accordingly, whether that means adjustments to existing factors, or the development of new ones. In addition, we will strive to keep ETS an integral part of your asset management workflow via new features on the web platform. As always, we hope you find the recent additions valuable, and please do not hesitate to reach out with any comments or questions.   Spencer Moran, Senior Analyst Equity Trading Strategy spencerm@bcaresearch.com   Appendix Variable Definitions Here we provide the definitions of the variables used in the distress model. The denominator in NIMTA and TDMTA represents “Market Total Assets” and is given by Market Cap. plus Total Debt.  The formulas are as follows: EWM is a 12-month exponential weighted moving average used to incorporate more history into the variable but provide greater weight to more recent observations. STD is an annualized, trailing three-month standard deviation. The symbols R, Rm, and r represent monthly returns, monthly market returns, and daily returns, respectively. Parameters Here we provide the parameters (aka a and b’s) obtained from the rolling fit of the distress model. Recall that parameters are estimated at the end of each year, and then these parameters are used to compute predictions for the following year to avoid look-ahead bias. Footnotes 1      The original Z-score formula was as follows: Z =   1.2X1 + 1.4X2 + 3.3X3 + 0.6X4 + 1.0X5, where: X1 : working capital / total assets X2 : retained earnings / total assets X3 : earnings before interest and taxes / total assets  X4 : market value of equity / book value of total liabilities X5 : sales / total assets 2  Campbell, John Y., Jens Dietrich Hilscher, and Jan Szilagyi. 2011. Predicting financial distress and the performance of distressed stocks. Journal of Investment Management 9(2): 14-34. 3   The decile-spread is a metric we use to evaluate the performance of a trading system. Essentially, it looks at the sum of the differences between the annual compounded growth rates of each score decile. Ideally, the deciles should be in order, and the upper deciles should outperform the lower deciles. This metric captures both these aspects, and summarizes them in a single number. 4       The factor inception date was chosen to be the date when the relative change in the magnitude of the parameter set (treated as a vector) fell below 1%. 5      Please see Equity Trading Strategy, “ETS Goes Global,” dated October 31, 2016, available at ets.bcaresearch.com 6      Precision is defined as the ratio of actual failures to all failures predicted by the model. Meanwhile, recall is the ratio of actual failures to the sum of actual failures plus false successes predicted by the model. 7      Kaggle is a popular online community (recently acquired by Google) where members compete to solve open problems in data science and machine learning.

Highlights Global Growth: Early leading indicators (credit impulses, our global LEI diffusion index) are signaling that the worst of the global economic downturn should soon end. Okun’s Law: In the developed economies, the observed relationships between economic growth and changes in unemployment suggest that the current pullback in global growth will not be severe enough to create slack in labor markets and reduce inflation pressures. Global Bond Allocation: Within dedicated global government bond portfolios, stay underweight the U.S. and Canada, neutral core Europe, and overweight the U.K., Japan and Australia. Remain tactically overweight global credit versus government bonds, at least until mid-year, with policymakers likely to stay cautiously dovish until global uncertainties recede. Feature Is This Risk Rally Too Good To Last? The mood of financial markets has improved significantly over the past few weeks, led by the dovish shift from central bankers that has revived investor risk appetite. Some positive headlines on U.S.-China trade negotiations have also generated hope over prospects for a deal, further fueling the bullish sentiment. The global economic picture remains muddled, though. Non-U.S. growth continues to languish, while the actual near-term state of the U.S. economy is proving difficult to determine given the data issues surrounding the 35-day U.S. government shutdown. Given lingering uncertainties, both political and economic, policymakers do not want to rock the boat by saying anything that might be interpreted as hawkish. With monetary policy no longer a near-term headwind, there is a window for continued outperformance of global risk assets in the next few months. That means higher global equity prices and stable-to-tighter global corporate credit spreads. Yet the seeds for the next wave of market turbulence may already be sewn. There are signs that the global growth downturn may soon end. Credit impulses are starting to pick up in several major economies, while our diffusion index of global leading economic indicators – itself a longer leading indicator – has clearly bottomed (Chart of the Week). The epicenter of global economic weakness, China, continues to deploy monetary and fiscal stimulus measures aimed at stabilizing growth. Meanwhile, the U.S. economy still appears to be in good shape, underpinned by solid consumer fundamentals. Chart of the WeekSunnier Days Ahead? A combination of easier financial conditions and faster economic growth will eventually prove to be incompatible with stable monetary policy, especially with surprisingly firm inflation in the major developed economies. Central bankers will respond by moving away from their current dovish bias, led by the U.S. Federal Reserve. With government bond markets now discounting both stable monetary policy and too-low inflation expectations, the path for global bond yields is eventually higher. While headline inflation rates are cooling in response to the lagged impact of weaker oil prices, the pullback has been far more muted so far compared to similar sharp oil-driven moves in the past (Chart 2). This is because domestically-driven inflation rates for services and wages are much sturdier today in many countries. If BCA’s bullish oil view for 2019 comes to fruition, then the current decline in headline/goods inflation rates may prove to be very short-lived and with little pass-through into core/services inflation. Chart 2Sticky Global Inflation, Despite Lower Oil Prices This dynamic is not the same in every country, however. When looking at the individual trends of goods inflation and services/wage inflation in the major developed economies, the largest gaps between the two exist in the U.S. and Canada (Chart 3). There, wage growth is accelerating and services inflation rates remain sturdy, despite sharp drops in goods inflation. Chart 3Domestic Inflation Pressures Most Acute In The U.S. & Canada Our recommended government bond allocation at the country level reflects these underlying inflation trends. We are more bearish on bond markets with the most intense domestic inflation pressures – and where future interest rate hikes are most likely – and vice versa. We remain underweight the U.S. and Canada, where wage growth and services inflation are both above the inflation targets of the Fed and Bank of Canada, and where market-based measures of inflation expectations like CPI swap rates have already bottomed (Chart 4). We remain neutral on core Europe (Germany, France) where wage growth has perked up, core/services inflation remains closer to 1% than the 2% target of the ECB, and inflation expectations continue to drift lower. Finally, we remain overweight the U.K., Japan and Australia, all of which have an underlying inflation picture that is muted enough to keep policymakers on hold for at least the next 6-9 months. Chart 4Favor Bond Markets Where Domestic Inflation Pressures Are Weakest Bottom Line: Early leading indicators (credit impulses, our global LEI diffusion index) are signaling that the worst of the global economic downturn should soon end. Central bankers will remain cautious and dovish in the near-term, however, implying that the current outperformance of global equity and credit markets has more room to run – but also setting up the next upleg for bond yields later this year. Okun’s Law Revisited Central bankers remain wedded to the idea that there is an “exploitable” relationship between unemployment and inflation, a.k.a. the Phillips Curve. A logical extension is that unless policymakers can credibly forecast a reduction in labor demand that pushes unemployment rates beyond levels associated with full employment, inflation will not be expected to decline. Policymakers will have a difficult time staying dovish without believing that inflation pressures are diminishing. One way to measure the relationship between economic growth and changes in economic slack is by using a concept that you may remember from an old macroeconomics class – Okun’s Law. More an empirically observable rule of thumb than any rule based in actual economic theory, Okun’s Law simply measures how much unemployment rates change relative to swings in real GDP growth. Past estimations for the U.S. economy have shown that the long-run coefficient in the Okun’s Law regression is around 2, which means that a 2% fall in real GDP growth should be associated with a 1% increase in the unemployment rate (and vice versa). That coefficient is not the same over shorter time horizons, though, as the unemployment/GDP growth relationship can be impacted by other cyclical factors like changes in hours worked or labor productivity. Charts 5 and 6 show annual real GDP growth (the percentage change over four quarters) versus the change in the unemployment rate over twelve months for the major developed economies (the U.S., U.K., euro area, Japan, Canada, Australia, New Zealand and Sweden) dating back to 1980. There is a reasonably strong relationship between the two series in the charts, although the “fit” does vary from country to country. Chart 5The Okun’s Law Relationship … Chart 6… Still Holds For Most Countries That can be seen in the individual country scatterplots shown in Charts 7 to 14, which plot each quarterly data point of the change in unemployment and real GDP growth. The darker dots represent the period from 1980-2010, while the lighter dots are the post-2010 era. The actual estimated regression, and its R-squared, are also shown in the charts (the equation can be defined as “the estimated change in the unemployment rate for a given pace of real GDP growth”). For most countries shown, the R-squareds are reasonably good (between 0.55 and 0.70) for a single-factor model like this. The coefficients on the change in real GDP are all between -0.35 and -0.45, which means that a fall in real GDP growth of 3.5 to 4.5 percentage points is consistent with a rise in the unemployment rate of 1 percentage point. The lone country where the Okun’s Law relationship has a relatively poor historical fit is in Japan, which is due to the lack of GDP variability relative to swings in the unemployment rate, especially over the past decade. We can use these estimates of the Okun’s Law coefficient to conduct a “back of the envelope” thought experiment that answers the following question that relates to the current economic and financial market backdrop: how much of a decline in GDP growth is necessary to raise unemployment rates back to full-employment (NAIRU) levels? As we have consistently noted in recent Weekly Reports, global central bankers can only turn so dovish, even after the severe market turbulence seen at the end of last year and with elevated political uncertainty in many locations. Why? Because unemployment rates remain below levels that are consistent with stable inflation. Without a meaningful weakening of labor markets that pushes unemployment rates back above “full employment” levels, policymakers will not be able to lower their inflation forecasts and signal a need for easier monetary policy. In Table 1, we present the estimated Okun’s Law regressions from 1980, along with the real GDP growth rate that falls out of those equations if we assume the employment gaps are closed.1 We also show the consensus 2019 real GDP growth forecasts taken from Bloomberg, as well as the expected change in central bank policy rates over the next year taken from our Central Bank Discounters. The conclusion from the Table is that it would take significant declines in real GDP growth to raise unemployment rates enough for policymakers to become less worried about inflation pressures. Table 12019 Consensus Growth Forecasts Are Well Above Levels That Would Eliminate The Unemployment Gap In the U.K., where the unemployment rate is furthest below the OECD’s estimate of the full-employment NAIRU rate, a whopping -3.3 percentage point cut to real GDP growth is needed to raise unemployment back to 5.6%. The required GDP fall is lower in the U.S., with only a -1.6 percentage point decline in real GDP growth need to push the unemployment rate back to the OECD NAIRU estimate of 4.3%. Falls in real GDP growth of between -1.5 and 2.0 percentage points are necessary in most of the other countries to close the “unemployment gap”, except for Japan. Given the weak estimated Okun’s Law relationship in Japan, we are reluctant to put much weight on the results of this thought experiment for Japan. Those “required” declines in real GDP growth are nowhere close to the 2019 consensus Bloomberg forecasts for each country. This is even true in the U.S., where the consensus expects real GDP growth to decline by -0.9 percentage points in 2019. Unsurprisingly, markets are discounting very little change in monetary policy over the next year according to our Central Bank Discounters, with modest odds of a rate cut now discounted in Australia (-19bps), New Zealand (-11bps) and the U.S. (-8bps) and a full 25bp hike now priced in Sweden. Summing it all up, our simple Okun’s Law thought experiment shows that it would take a significantly larger decline in global growth than the consensus, or BCA, expects for central banks to shift even more dovishly in the direction of interest rate cuts. This puts a cyclical floor underneath global bond yields, given that relatively stable policy rates are now discounted. Bottom Line: The observed relationships between economic growth and changes in unemployment suggest that the current pullback in global growth will not be severe enough to create slack in labor markets and an easing of inflation pressures in the developed economies.   Robert Robis, CFA, Senior Vice President Global Fixed Income Strategy rrobis@bcaresearch.com   Footnotes 1 Given the declining productivity trend seen in all countries over the past 20 years, we have made a downward adjustment to those Okun’s Law estimated coefficients. In other words, we do not think that it will take the same magnitude of GDP loss to generate the same increase in unemployment when labor productivity is low. Recommendations The GFIS Recommended Portfolio Vs. The Custom Benchmark Index Duration Regional Allocation Spread Product Tactical Trades Yields & Returns Global Bond Yields Historical Returns