Global

Special Report

  Dear Client, In lieu of our regular report this week, we are sending you a Special Report from my colleague Jonathan LaBerge. Jonathan examines the global effectiveness of recent pandemic containment measures to judge both the odds of a second infection wave and what policy responses are likely to be effective in countering one were it to occur. In addition, I will take part in a discussion on the longer-term outlook for inflation alongside my colleagues Robert Robis and Robert Ryan in a live webcast this Friday, June 5 at 8:00 AM EDT (1:00 PM BST, 2:00 PM CEST, 8:00 PM HKT). Best regards, Peter Berezin, Chief Global Strategist   Highlights In this report we examine the effectiveness of COVID-19 containment measures across 30 of the largest global economies to determine which measures best explain cross-country “success” at fighting the pandemic. Our findings are generally consistent with the recommendations of health experts today and the historical experience of the Spanish flu. The speed at which measures were deployed appears to have been a very important factor contributing to success, and the most economically-damaging measures seem to have been among the most effective in combating the spread of the disease. This underscores that fighting a secondary infection wave, were one to occur, would be enormously costly even if more effective and less blunt containment measures succeeded at preventing uncontrolled spread. Equity investors are thus making a risky bet in extrapolating early reopening. We recommend a tactically neutral allocation towards equities versus bonds, within the context of a cyclically-overweight stance. Feature Global equities have rallied 38% from their March 23 low, and remain only 9% below this year’s high. The rally in stocks reflects, in part, the very aggressive response that has occurred from both fiscal and monetary authorities. But it also reflects the view that pandemic containment measures have succeeded in controlling the spread of the disease in the western world, and that developed countries will be able to continue to progressively roll back containment measures and restart their stalled economies. In this report we investigate the effectiveness of recent pandemic containment measures across 30 of the largest economies in the world, based on data sourced from the Oxford COVID-19 Government Response Tracker. The goal of the report is to determine which of the measures best explain cross-country “success” at fighting the pandemic, in order to judge both the likelihood of a second wave of COVID-19 infections and what policy responses are likely to be effective in countering one were it to occur. Our findings are generally consistent with the recommendations of health experts today and the historical experience of the Spanish flu. The speed at which authorities responded to COVID-19 appears to be among the most important factors contributing to the relative success among countries in combating the pandemic, and the most economically-damaging containment measures (school and workplace closures, event cancellation, and travel restrictions) appear to have been among the most effective in combating the pandemic, depending on the measure of success in question. For investors, this underscores that fighting a secondary infection wave, were one to occur, would be enormously costly even if more effective and less blunt containment measures succeeded at preventing uncontrolled spread. In this regard, it appears that equity investors are making a risky bet in extrapolating early reopening, arguing for a tactically neutral allocation towards equities versus bonds within the context of a cyclically-overweight stance. Measuring Government Responses To COVID-19 Chart 1The Forcefulness Of Government Responses To COVID-19 Over Time The COVID-19 Government Response Tracker (OxCGRT) was launched by the University of Oxford’s Blavatnik School of Government in late-March as a tool to track and compare policy responses of governments tackling the coronavirus outbreak. The tracker originally included 11 indicators of how governments were responding: 7 measures of closures & containment, 2 measures tracking the economic response, and 2 measures of investment in health care and vaccine research. The original 7 measures of closures & containment were combined into an aggregate measure dubbed the Government Response Stringency Index (Chart 1), which has been widely cited over the past two months. OxCGRT was updated in late-April, and the changes included both new indicators (bringing the total to 18) and amendments to the way in which some of the original indicators were defined. Table 1 provides a list of the closure/containment and health indicators as well as their definitions, along with the codes or scores used to denote the different levels of stringency in each indicator. In the charts shown in this report, indicator values are shown rescaled to be between 0 – 100; as an example, a score of 2 out of 4 for international travel would show up as a rescaled value of 50. Table 1Description Of The Oxford Government Response Stringency Index Components Pertaining To Closures & Containment And Health Among the measures shown in Table 1, we test the power of 11 indicators (all 8 closure/containment and 3 public health measures) to explain the cross-country “success” of 30 countries in fighting the COVID-19 pandemic. “Success” is defined in three ways: limiting the magnitude of the virus’ spread (peak per capita cases and fatalities), limiting the time to the peak in new cases and fatalities, and the speed at which new cases and fatalities decline following a peak. Finally, we make our own adjustment to OxCGRT’s indicators by penalizing targeted measures rather than providing a bonus to general measures (as is done when calculating the official Stringency Index). We then combine these adjusted measures into our own index using the same equally-weighted methodology as employed when calculating the official Stringency Index. Our adjusted index has a somewhat stronger relationship with our three measures of success than OxCGRT’s Stringency Index, validating our approach to reducing the score of any given indicator by half when the measure is targeted rather than general in nature. Explaining The Magnitude Of The Cross-Country Spread For the 30 countries included in our analysis, Chart 2 illustrates the relationship between the degree of the virus’ spread (both in terms of current per capita confirmed cases and fatalities) and the average level of our adjusted stringency index in the early phase of each country’s outbreak. Chart 2At First Blush, Stringency Does Not Appear To Predict The Ultimate Magnitude Of The Spread… Given the persistent findings from epidemiological models that efforts to contain pandemics must occur quickly, we define this early phase as the first six weeks following the day in which a country reached five confirmed cases. This point was reached in late-January in most Asian countries, Australia, the US, and some parts of Europe, and in February for almost all of the remaining developed economies that we examined. Emerging market economies reached this point in the first half of March. The chart makes it clear that the average stringency of containment measures during this early phase has little power to predict the ultimate magnitude of the spread when considering all 30 countries. However, the charts also highlight that several European countries – Belgium, Italy, the Netherlands, Spain, and Switzerland – are significant outliers, especially in terms of per capita fatalities. Chart 3 removes these outlying nations, and underscores that the degree to which the virus ultimately spread across countries is better explained for the remaining countries by the early stringency of their response. The higher the stringency of the measures, the lower the current (or peak) number of per capita cases and deaths. Chart 3…But The Relationship Is Stronger After Excluding Outlying European Nations Table 2 shows the R-squared values for each of the individual measures, including and excluding the five outlying countries noted above. The first noteworthy point from Table 2 is that the indicators appear to have a better ability to predict fatalities than confirmed cases, which is true for nearly all of the indicators across all three measures of success that we examine in this report. To us, this emphasizes a point that has become apparent over the past two months, namely that the meaningfulness of confirmed case data varies significantly across countries due to differences in testing practices and availability. To use the parlance of global macro analysts, confirmed cases are “soft data,” whereas fatalities (and hospitalizations) represent “hard data.” Of course, as is also the case in global macro analysis, the soft data tends to lead the hard data, which helps explain why confirmed cases of the disease will remain an important leading indicator for the US economy until they largely capture asymptomatic and mild cases that are not likely to lead to hospitalization or death. Table 2School Closures, Canceling Public Events, And International Travel Restrictions Seem To Explain Lower Fatalities The second noteworthy point is that while none of the measures have particularly strong predictive power for all countries, several do when the outliers are removed. Importantly, strong restrictions on international travel during the early outbreak phase show up as being the most important predictor of reduced fatalities per capita, followed closely by school closures. The cancellation of public events, public information campaigns, and domestic travel restrictions also appear to be relatively important predictors. Notably, cross-country differences in testing policies and the comprehensiveness of contact tracing do not seem to explain the variation in per capita cases and fatalities. As a final point on the magnitude of the spread of COVID-19, it is not immediately clear why the five European countries that we highlighted have been such sizeable outliers in the direction of higher per capita cases and fatalities despite seemingly stringent measures. At present, we have two theories: Given the importance of early and strong restrictions on travel highlighted in Table 2, it is possible that the efficacy of these restrictions has somehow been lower in these countries. It is possible that higher cases and fatalities in these countries can be explained by differences in the management of nursing homes and other elder care facilities, a factor that is not directly measured in the OxCGRT data. On the latter point, data from the Canadian province of Quebec underscores the impact of managing (or mismanaging) long-term care facilities. While Chart 3 highlights that Canada’s experience as a whole appears to be reasonably well-explained by the fairly low stringency of its response during the early phase of its outbreak, the province of Quebec has incurred a particularly high per capita fatality rate that is on par with the outlying European countries that we noted. Chart 3…But The Relationship Is Stronger After Excluding Outlying European Nations Chart 4Mismanaging Elder Care Facilities Significantly Affects The Fatality Rate Chart 4 presents a breakdown of cumulative Quebec COVID-19 fatalities by place of residence, which clearly demonstrates the impact of public and private nursing homes on the overall fatality rate. The death toll in publicly-funded homes has been particularly high, which even after accounting for the higher proportion of elderly residents in these types of facilities points to mismanagement and/or inadequate funding as key drivers of the disease’s spread (and thus fatalities given that nursing home residents face high risk from the disease). Similar dynamics may exist in the European countries that we cited, which could help explain their outlier status. Evidence On Hastening A Peak, And Post-Peak Decline, In New Cases & Fatalities Chart 5 presents the relationship between the amount of time needed to reach a peak in new cases and fatalities and the measure we used to predict the virus’ spread: the average level of our adjusted stringency index in the early phase of each country’s outbreak. Chart 5Stringent Early Measures Shorten The Time To A Peak In New Cases And Fatalities Table 3School Closures, Workplace Closures, And Canceling Public Events Seem To Explain Lower Days To Peak Cases And Fatalities The charts support the argument that stringent early measures shorten the number of days to a peak in new cases and fatalities. Table 3 presents the predictive power of the individual measures, which highlights some differences in the effectiveness of the measures to hasten the time to peak compared with their ability to predict the ultimate magnitude of the spread of the disease: Workplace closures appear to be somewhat better, and school closures somewhat worse, at predicting the speed at which countries reached a peak in new cases and fatalities than they were at predicting the ultimate magnitude of the spread. Closing public transport and restricting domestic travel were modestly successful at predicting the degree of spread but have essentially no power to predict the variation in the time to peak. Finally, restricting international travel was the strongest predictor of the degree of spread but also had essentially no power to predict the amount of time needed to reach a peak in new cases. As noted above, we use the average level of our adjusted stringency index as a predictor for both the prevalence of the disease and the time needed to reach a peak in new cases and deaths. Since it is an average of a given period of time, this variable measures a combination of the stringency of the restrictions as well as how early they were deployed. To test the relative importance of the severity of the measures versus the speed at which they occur, we apply the same approach as in Chart 5 but we replace OxCGRT’s score of each measure’s value for each country with a dummy variable (0 for no measures or 1 for any measures, again rescaled to be between 0 - 100) while retaining the penalty for targeted measures described above. In simple terms, we abstract from whether the severity of the measures is low or high and instead focus simply on whether any measures were applied and when. Chart 6 and Table 4 present the results. With the exception of a country’s testing policy’s ability to predict confirmed cases, the charts and table show that there is little difference between the full indicators and the dummy versions. This suggests that where general (rather than targeted) measures to reduce the spread of the virus have been effective, they have been so because of the speed of their deployment rather than their strictness. Chart 6The Deployment Speed Of Containment Measures Seems More Important Than Their Strictness Table 4Small Differences Between The Full Measures And Those Focused Only On The Existence Of Any Response Finally, Chart 7 and Table 5 present the ability of the various (full) indicators to predict how successful various countries have been at reducing new cases and fatalities following a peak. The chart and table underscore that the measures have not been particularly successful at explaining the degree to which countries have reduced new cases and deaths, with the exception of two measures: the cancellation of public events and contact tracing. And in the case of the latter, the prevalence of contact tracing appears to help explain greater reductions in new cases, but only weakly explains reduced fatalities. Chart 7Overall, Stringency Does Not Predict Success At Reducing New Cases And Fatalities Following A Peak Table 5Canceling Public Events And Contact Tracing Appear To Have Some Success At Hastening A Post-Peak Decline Key Takeaways Correlation does not necessarily imply causation, and thus the ability of a particular containment measure to predict differences in COVID-19 outcomes across countries may not always reflect the effectiveness of the measure. Nonetheless, there are several important takeaways from the evidence provided above: The speed at which authorities responded to COVID-19 appears to be among the most important factors contributing to the relative success among countries in combating the pandemic. Implementing general rather than targeted measures does seem to be important, but beyond that stringency does not appear to be the key driver differentiating outcomes across countries. Worryingly, the most economically-damaging containment measures (school and workplace closures, event cancellation, stay-at-home orders, and travel restrictions) appear to have been among the most effective measures in combating the pandemic, depending on the measure of success in question. While containment measures appear to have succeeded in bringing about a peak in new cases and fatalities in most developed economies, the evidence shown above highlights how long painful measures need to be in place in order to have an impact. For example, Chart 8 illustrates the relationship between workplace closure and the time to peak in new fatalities; with the exception of Hong Kong, even in the countries that acted quickly and forcefully to close workplaces it took over a month to reach a peak. To the extent that global policymakers are aware of the relative importance of restrictions on international travel in limiting the ultimate spread of the disease in the countries we examined, that may suggest that international borders will remain closed or severely restricted for some time or will reoccur very quickly if evidence of a secondary infection wave were to emerge later this year. Chart 8Reaching A Peak In Fatalities Is Costly Even For Countries That Act Quickly There is another important insight for investors that is not immediately apparent from our work, but emerges when we examine two surprising findings. Looking closely, investors can infer that the public’s awareness and fear of the disease has contributed to successes in combating COVID-19, in ways that are not readily captured by the OxCGRT’s data. To us, the key observation is that both closures of public transportation and the forcefulness of stay-at-home orders showed themselves to be mediocre-to-poor predictors, when it seems straightforward to see that reduced crowding on buses and subways and physical distancing have very likely helped reduce the spread of the virus. This seeming discrepancy is likely resolved by the fact that the public acted themselves to take these measures out of fear of getting sick, meaning that cross-country differences in rules pertaining to these measures have not been especially relevant in predicting outcomes. Chart 9 supports this point by highlighting that subway ridership in New York city fell well before the city issued a mandatory stay at home order, as did the median year-over-year growth rate in US seated restaurant diners before the first stay at home order was issued in the US (Chart 10). Chart 9New York City Subway Ridership Fell Well Before The Stay-At-Home Order Was Issued Chart 10Diners Started Avoiding Restaurants Before Any Stay-At-Home Orders Were Issued Chart 11Sweden Is A Very Big Outlier In Terms Of Where The Stringency Of Its Measures Peaked The importance of public behavior in altering the spread of COVID-19 is also evident from Sweden’s experience, albeit in a different way than has been commonly discussed. The charts above highlighted that Sweden has indeed been somewhat of an outlier in terms of its experience with COVID-19 relative to the stringency of its early response, but there have been a few other countries with similar experiences. Where Sweden has been a very significant outlier is the level at which its Stringency Index peaked, at least compared with other advanced economies (Chart 11). And yet, Sweden appears to have achieved a peak in new fatalities based on the data available today. Swedish policymakers have cited the country’s high levels of social trust and cohesion as part of the reason why more strict measures were not absolutely necessary to prevent an uncontrollable/exponential spread of the disease, and we see no reason to doubt that this has been an important, if not crucial, factor – Scandinavian countries have long ranked highly on these types of characteristics. Investment Conclusions The first important point for investors is that our findings are generally consistent with the recommendations of health experts today and the historical experience of the Spanish flu. One of the key lessons of the Spanish flu is that removing or relaxing measures too early can lead to a renewed rise in mortality rates,1 and it thus seems clear that the reopening of economies before the first wave of infections has fully dissipated increases the odds of a second wave. In this regard, it appears that US equity investors are making a risky bet in extrapolating early reopening. Second, the fact that the public's behavior can significantly alter COVID-19 outcomes across countries has both potentially positive and negative implications for the odds of a secondary infection wave and for near-term economic growth. For the economy, it implies the possibility of sustainable economic reopening alongside a controllable risk of renewed spread if the public can be convinced to treat the ongoing risk of the disease very seriously without fearing it. This outcome may be more likely if mask wearing in public – a variable not captured in OxCGRT’s data – becomes and remains widespread in advanced, western economies. At the same time, it may also suggest that the “Swedish approach” of accepting higher fatalities in exchange for lighter containment measures within the context of a “controlled” spread of the disease may not be possible in other countries, if Sweden does indeed enjoy higher levels of social trust and cohesion compared with other countries and if these factors have been key in preventing the disease from spreading there at an exponential rate. Finally, our analysis has underscored that fighting a secondary infection wave, were one to occur, would be enormously costly even if more effective and less blunt containment measures succeeded at preventing uncontrolled spread. Given this, and the higher risk of increased infections introduced by economic reopening and the recent widespread protests in the US, we recommend that investors remain tactically neutral equities versus bonds within the context of a cyclically-overweight stance.   Jonathan LaBerge, CFA, Vice President Special Reports jonathanl@bcaresearch.com   Footnotes 1    Please see Global Asset Allocation Special Report, “Lessons From The Spanish Flu,” dated May 20, 2020. Global Investment Strategy View Matrix Current MacroQuant Model Scores  

The GAA DM Equity Country Allocation model is updated as of May 29, 2020.  The model has not made any significant change this month.  It has kept the same order for the top four overweight countries (Spain, Australia, Sweden, and the US) as well as the four large underweight countries (Japan, the UK, France, and Switzerland), as shown in Table 1.  Table 1Model Allocation Vs. Benchmark Weights As shown in Table 2 and Charts 1, 2 and 3, the overall model outperformed the MSCI World benchmark in May by 29 bps. The Level 1 model outperformed 2 bps because of the overweight in the US. The Level 2 model outperformed by 85 bps thanks to the overweight of Sweden, Germany and the Netherlands, as well as the underweight in the UK and Switzerland. Since going live, the overall model has outperformed its MSCI World benchmark by 180 bps, with 246 bps of outperformance from the Level 2 model, and 33 bps of outperformance from the Level 1 model. Table 2Performance (Total Returns In USD %) Chart 1GAA DM Model Vs. MSCI World Chart 2GAA US Vs. Non US Model (Level 1)     Chart 3GAA Non US Model (Level 2) For more on historical performance, please refer to our website https://www.bcaresearch.com/site/trades/allocation_performance/latest/G…. For more details on the models, please see Special Report, “Global Equity Allocation: Introducing The Developed Markets Country Allocation Model,” dated January 29, 2016, available at https://gaa.bcaresearch.com. Please note that the overall country and sector recommendations published in our Monthly Portfolio Update and Quarterly Portfolio Outlook use the results of these quantitative models as one input, but do not stick slavishly to them. We believe that models are a useful check, but structural changes and unquantifiable factors need to be considered as well when making overall recommendations.   GAA Equity Sector Selection Model Chart 4Overall Model Performance The GAA Equity Sector Model (Chart 4) is updated as of May 29, 2020. The model’s relative tilts between cyclicals and defensives have changed compared to last month. The model reversed its defensive stance implemented throughout March and April and is now tilted towards cyclical sectors. However, the semi-defensive tilt led the model to outperform its benchmark by 21 basis points during May. Year-to-date, the model has outperformed its benchmark by 88 basis points, and 86 basis points since inception. The model’s global growth proxy improved – mostly driven by EM currencies and commodity prices, and therefore turned positive on various cyclical sectors and reversed its defensive stance implemented in March. Global monetary easing and low rates should keep the liquidity component favouring a mixed bag of cyclical and defensive sectors. The valuation component remains muted across all sectors except Energy. However, multiple sectors are approaching expensive and cheap territories – mainly Info Tech (expensive), and Real Estate (cheap). The model awaits confirming momentum signals to change recommendations for that component. The model is now overweight five sectors in total, four cyclical sectors versus one defensive sectors. These are Information Technology, Consumer Discretionary, Communication Services, Materials and Health Care.  Table 3Overall Model Performance For more details on the model, please see the Special Report “Introducing the GAA Equity Sector Selection Model”, dated July 27, 2016, as well as the Sector Selection Model section in the Special Alert “GAA Quant Model Updates,” dated March 1, 2019 available at https://gaa.bcaresearch.com. Table 4Current Model Allocations Xiaoli Tang Associate Vice President xiaoliT@bcaresearch.com Amr Hanafy Senior Analyst amrh@bcaresearch.com  

Feature The key to how markets will move over the coming 12 months is whether the coronavirus pandemic turns out to be a short-term (albeit severe) disruption to the world economy, or something more fundamentally damaging. Markets currently – with global equities up by 34% since March 23 – are clearly pricing in the former. They seem to be saying that the sudden stop to the economy – with US employment, for example, rising to a post-war high in just two months (Chart 1) – is not a problem, since most of the unemployed are furloughed and will quickly return to work once businesses reopen. Enormous stimulus (direct fiscal spending in G20 countries of 4.6% of GDP, even if loans and guarantees are excluded – Chart 2) and aggressive monetary policy (major central banks’ balance sheets have ballooned by $4.7trn since March – Chart 3) will tide us over until normality returns, and then provide a big boost to risk assets. Unprecedented efforts by drugs companies will soon produce a vaccine against COVID-19. Recommended Allocation   Chart 1Can Unemployment Come Down As Quickly? Chart 2Unprecedented Fiscal… Chart 3...And Monetary Stimulus All this is possible. Certainly, the amount of excess liquidity being pumped into the economy by central banks (Chart 4) could dramatically boost economic activity and asset prices once the world returns to normal. The newsflow over coming months may largely be positive, with a gradual easing of lockdowns, a rebound in economic data (it cannot mathematically get any worse), and an abatement of the pandemic during the northern hemisphere summer. Many investors remain pessimistic (Chart 5) and so may be pulled into markets if stocks continue to rise. In this environment – and with the alternatives so unattractive (10-year US Treasurys at 0.6% anyone?) – we wouldn’t want to take a bet against equities. Chart 4Liquidity Will Boost Assets - Eventually But is the market ignoring the risks? Easing of lockdown could lead to a flare-up of new COVID-19 cases: China has already had to reintroduce some containment measures when this happened (Chart 6). Chart 5Retail Investors Remain Bearish   Chart 6What Happens When Lockdowns Are Eased? While COVID-19 cases have peaked in Asia, Europe, and North America, there is a new wave in Emerging Markets, particularly those such as Brazil which were lax in implementing containment measures (Chart 7). Even where the pandemic has waned, consumers seem highly reluctant to go to restaurants (Chart 8) or fly on airplanes (Chart 9). Chart 7The Pandemic Is Shifting To Emerging Economies Consumer-facing companies may no longer see revenues down by 70% or 80% over the next few months, but they could still be 10% or 20% below normal levels. How many business models are robust enough to survive that? As for a vaccine, it is worth remembering that no vaccine has ever been developed for a coronavirus in humans. We may have to learn to live with the disease. Chart 8Consumers Are Not Yet Going To Restaurants... Chart 9…Or On Planes The longer the pandemic lasts, the more damaging will be its second-round effects. Already banks are turning more cautious about lending (Chart 10), and rating agencies are rapidly downgrading companies (Chart 11). We are likely to see a wave of corporate defaults, Emerging Market borrowers struggling to service their foreign-currency debts, and banks getting into trouble as a result – though monetary and fiscal bridging programs may defer these problems for a while. Chart 10Banks Are Turning More Cautious... Chart 11...And Companies Are Being Downgraded The US/China relationship is also a concern in the run-up to November’s US presidential election. It will be tempting for President Trump to turn tough on China, a policy that could be popular with the US electorate, which has become more anti-China in recent months (Chart 12). Problems over Hong Kong, China failing to hit the import targets it promised in January’s trade agreement, and action against Huawei (whose license expires in mid-August) mean that the conflict could escalate quickly. China would also much prefer Joe Biden as US president, and will do nothing to help President Trump get reelected. Chart 12Being Tough On China Is Popular In The US Chart 13The Dollar Has Not Reacted To The Risk-On Rally In this environment of unusual uncertainty, we continue to leaven our benchmark-weight position in global equities with relatively cautious tilts: overweight the lower-beta US market and structural-growth sectors such as Healthcare and Tech. We maintain our large position in cash, and would continue to hold gold as a hedge against tail risks. The risk to this view is that over coming months – if the environment continues to stabilize – there is a vicious rotation into pure cyclical plays, perhaps driven by a fall in the US dollar (which has until recently been surprisingly stable during the past two months’ risk-on rally – Chart 13), a rise in commodity prices, and higher long-term interest rates. This scenario would trigger outperformance by Emerging Markets and eurozone stocks, and value-oriented sectors such as Materials and Financials. This might be possible for a short period but, given the risks highlighted above, we would not recommend long-term investors to shift their portfolios in this direction.   Equities: Our “minimum volatility” approach has worked well: US equities and structural growth sectors such as Healthcare and Tech continued to outperform both during the sell-off in February and March and in the subsequent rebound (Chart 14). For now, we prefer to stick to this cautious stance on a 12-month investment horizon. It is possible, though, that there could be some short-term rotation into value and small cap stocks if the environment improves further over the next couple of months (Chart 15). We are partially hedged against this sort of upside surprise through our overweight in Industrials (which would benefit from a ramp-up in Chinese infrastructure spending, in particular) and neutral on Emerging Markets and Australia. Chart 14"Min Vol" Equities Have Outperformed Chart 15Could There Be A Shift To Value And Small Caps? Fixed Income: Government bond yields have not risen despite the risk-on rally, and we expect this to remain the case. Continuing uncertainty, central bank insistence that easy monetary policies will stay in place for a long time, and deflationary pressures over coming months warrant a neutral stance on duration – though returns from high-quality government bonds will be around zero. In the longer-run, however, the pandemic is likely to prove inflationary: like in a post-war environment, excess liquidity, supply constraints, and pent-up demand could push up consumer prices in 12 months’ time. Consumers are already noticing that the goods they are actually buying now (as opposed to the weightings in the consumption basket used to measure inflation) are rising in price (Chart 16). We recommend TIPS as a hedge, particularly given how cheap they are (with the 10-year breakeven at only 1.2%). Corporate credits that are supported by central bank buying remain attractive, although with spreads having already contracted the easy money has been made (Chart 17). BCA Research’s fixed-income strategists prefer US and UK investment-grade and BB-rated corporate bonds in the Media, Financials and Energy sectors.1 Chart 16Consumers Are Sniffing Out Inflation Chart 17The Easy Money Has Been Made In Credit Currencies: It will pay to watch the US dollar. It is overvalued and no longer supported by interest rate differentials, but as a safe haven currency has seen inflows given global economic uncertainty. For now, we remain neutral. Emerging Market currencies are likely to remain under pressure, particularly since EM central banks have followed the example of their Developed Market counterparts and for the first time embarked on QE to boost their economies (Chart 18). This could lead to rising inflation in some EMs, as central banks essentially monetize government debt. Chart 18EM Central Banks Are Starting QE Too Commodities: China has quietly been ramping up its credit growth, and this will eventually have a positive impact on industrial metals prices, which have showed tentative signs of bottoming (Chart 19). The rebound in oil prices has further to run. OPEC oil production is likely to fall by around 4 million barrels/day from its Q4 2019 level, with further output drops from capital-constrained North American shale producers (Chart 20).   Chart 19Industrial Commodities Bottoming? Harder to predict is how quickly demand – currently down around 15% year-on-year – will recover. BCA Research’s oil strategists, based on an assumption of a strong demand revival in H2, forecast Brent crude to rise above $50 a barrel by end-2020. Chart 20Oil Supply Has Fallen Significantly Garry Evans, Senior Vice President Global Asset Allocation garry@bcaresearch.com Footnotes 1  Please see Global Fixed Income Strategy, "Hunting For Alpha In The Global Corporate Bond Jungle," dated May 27, 2020, available at gfis.bcaresearch.com. Recommended Asset Allocation

Dear Client, In lieu of our regular report next week, we will be sending you a Special Report from my colleague Jonathan LaBerge. Jonathan will be examining the global effectiveness of recent pandemic containment measures to judge both the odds of a second infection wave and what policy responses are likely to be effective in countering one were it to occur. I hope you find the report insightful. Best regards, Peter Berezin, Chief Global Strategist Highlights Fiscal deficits have soared in the wake of the pandemic, putting government debt-to-GDP ratios on a trajectory to reach post-WWII highs in many countries. Contrary to popular belief, there is little reason to think that fiscal relief will make it more difficult for governments to repay their obligations down the road. Larger budget deficits tend to increase overall national savings when the economy is depressed because private savings rise more than enough to compensate for the decline in government savings. The end result is a higher level of national wealth that governments can tax in the future. That said, there is more than one way to tax national wealth. For political reasons, higher inflation coupled with financial repression may prove to be more feasible than other forms of taxation. While inflation is not an imminent risk, it could become a formidable problem in two-to-three years. Investors should maintain below-benchmark levels of duration in fixed-income portfolios and favor inflation-linked securities over nominal bonds. Gold prices will rise over the long haul. The yellow metal should perform well even in the near term if the dollar weakens during the remainder of this year, as we anticipate. Real estate investors should reallocate capital away from densely populated urban areas towards suburbs and farmland. Stay Cyclically Overweight Equities Global equities continued to climb higher this week, as more countries reopened their economies. As we discussed three weeks ago in our report entitled “Risks To The U,” the main downside risk facing stocks is a second wave of the disease.1 While the number of new COVID-19 cases has declined in many countries, it continues to rise in others. As a result, the global tally of new cases remains broadly flat. The daily number of deaths seems to be trending lower, but that could easily reverse if social distancing measures are abandoned too quickly (Chart 1). Chart 1COVID-19: Global New Cases Remain Broadly Flat, While Deaths Seem To Be Trending Slightly Lower Chart 2Joined At The Hip Given this risk, we do not have a strong near-term (3-month) view on the direction of equities. Google searches for the “coronavirus” have closely correlated with equity prices and credit spreads (Chart 2). If fears of a new outbreak were to escalate, risk assets would suffer. Looking at a cyclical (12-month) horizon, we still recommend a modest overweight to stocks. Even if a vaccine does not become available later this year, increased testing should allow for a more economically palatable approach to containment strategies. Ample fiscal support will also help. As we provocatively asked in a report entitled “Could The Pandemic Lead To Higher Stock Prices?”,2 one can easily imagine a scenario where central banks keep rates near zero for the foreseeable future, while ongoing fiscal stimulus enables the labor market to reach full employment. Such an outcome could allow corporate profits to return to pre-pandemic levels, but leave the discount rate lower than before. The end result would be a higher fair value for the stock market. Although we would not counsel investors to bank on such a fortuitous outcome, the probability of it occurring is reasonably high – probably in the range of 30%-to-40%. This makes us inclined to favor stocks over a cyclical horizon. Will Indebted Governments Spoil The Party? One potential flaw in this bullish thesis is that massive government deficits could push up interest rates, crowding out private-sector investment in the process. As we argue below, such worries are misplaced for now. For the time being, bigger budget deficits will likely lead to an increase in overall savings, thus raising investment relative to what would have happened in the absence of any stimulus. That said, as we conclude towards the end of this report, there will come a time – probably in two-to-three years – when most economies are back to full employment. If budget deficits are still high at that point, inflation and long-term bond yields could end up rising substantially. Keynes To The Rescue The IMF expects budget deficits in advanced economies to exceed 10% of GDP in 2020, significantly higher than during the financial crisis. The sea of red ink is projected to push government debt-to-GDP ratios to fresh highs in many economies (Chart 3). Chart 3AGovernment Debt Levels Have Surged In The Wake Of The Pandemic Chart 3BGovernment Debt Levels Have Surged In The Wake Of The Pandemic Chart 4The Paradox Of Thrift: Not Just A Theory Should bond investors be worried? Not for now. One of John Maynard Keynes’ great insights was that an individual’s attempt to increase savings could lead to a collective decline in savings, a phenomenon he called the paradox of thrift. Keynes argued that if everyone tried to save more, the resulting contraction in spending would cause total employment to fall by so much that overall income would decline by more than spending. As a result, aggregate savings would fall. This is precisely what happened during the Great Depression and in the aftermath of the Global Financial Crisis (Chart 4). The paradox of thrift implies that bigger budget deficits in a depressed economy will lead to an increase in overall savings, as private savings rise more than one dollar for every dollar decline in government savings. S-I=CA One can see this point using the familiar macroeconomic accounting identity which says that the difference between what a country saves and invests should equal its current account balance.3 In the absence of a change in the current account balance, any increase in investment will translate into an increase in savings. If the government stimulates aggregate demand by increasing spending, cutting taxes, or boosting transfer payments, companies are likely to respond by investing more (or at least not cutting capital expenditures as much as they would otherwise). Thus, if fiscal stimulus raises investment, it will also raise aggregate savings. Chart 5Huge Spike In The US Personal Savings Rate This conclusion has important implications for bond yields. If bigger budget deficits lead to an increase in overall savings, there is no reason to expect real bond yields to rise very much, at least in the short term. The failure of bond yields to rise since March, when governments began to trot out one fiscal stimulus package after another, is a testament to this fact. So too is the stimulus-induced surge in the US personal saving rate, which reached a record high of 33% in April (Chart 5). All That Money Printing If bigger government budget deficits are, in some sense, self-financing, why are so many people convinced that the Fed and other central banks are effectively “monetizing” deficits by buying up bonds? Part of the answer has to do with how one defines monetization. Governments create money whenever they purchase goods or services or make transfers to the public by running down their deposits at the central bank. In theory, the public could use that money to buy government bonds, which would allow the government to replenish its account at the central bank. In practice, it is usually a bit more circuitous than that. Chart 6Commercial Banks Deposits, Bank Reserve Held At The Fed, And Fed Holdings Of Treasuries Have All Expanded This Year What normally happens is that the public places the money in a commercial bank deposit and the commercial bank then transfers the money to its account at the central bank. Next, the central bank buys the bonds from the government, crediting the government’s deposit account at the central bank in the process. Chart 6 shows that this is precisely what has happened this year: Commercial bank deposits, bank reserves held at the Fed, and the Fed’s holdings of Treasuries have all risen by roughly the same amount. Granted, there is a bit more to the story. If the central bank buys bonds, it will push down bond yields at the margin, allowing the government to finance itself more cheaply than it could otherwise. However, this is a far cry from the sort of “money printing” that many people have in mind. True debt monetization occurs when governments lose all access to outside financing, forcing the central bank to pick up the tab. Such situations invariably involve accelerating inflation and a collapsing currency, which often culminates in hyperinflation. This is clearly not the case today. Back To Full Employment The idea that bigger budget deficits can generate enough private savings to more than fully compensate for any loss in government savings is applicable only for economies with spare capacity. Once the economy reaches full employment, fiscal stimulus will not lead to more income or production since everyone who wants a job already has one. At that point, bigger budget deficits will cause the economy to overheat and inflation to rise, potentially forcing the central bank to raise rates. Higher interest rates will reduce investment. Higher rates will also put upward pressure on the currency, leading to a reduction in net exports and a corresponding deterioration in the current account balance. If investment and the current account balance both decline, then savings, which is just the sum of the two, must also fall. Strategies For Alleviating A Debt Burden Once the free lunch from fiscal stimulus disappears, the question of how to address the government debt accumulated during the downturn becomes paramount. There are four ways to reduce the ratio of government debt-to-GDP: 1) outgrow the debt burden; 2) tighten fiscal policy; 3) default; and 4) inflate away the debt. Outgrowing It At the end of the Second World War, many governments found themselves saddled with high levels of debt. In the US, the government debt-to-GDP ratio stood at 121% in 1945. In the UK, it hit 270%. In Canada, it reached 155%. For the most part, these governments did not repay the debt they incurred during the war. As Chart 7 shows, the nominal value of debt outstanding either rose or remained broadly constant following the war. What happened was that rapid GDP growth led to a shrinkage in debt-to-GDP ratios. Compared with the post-war period, the two drivers of an economy’s growth potential, labor force and productivity growth, are both weaker now. Thus, outgrowing the debt by raising the denominator of the debt-to-GDP ratio will be more difficult than in the past. It’s About g-r That said, the trajectory of the debt-to-GDP ratio does not depend solely on GDP growth; it also depends on the interest rate that the government pays to service its debt. Conceptually, it is the difference between the two that determines whether the level of any given budget deficit is sustainable or not. While trend GDP growth in advanced economies has declined since the 1950s, equilibrium interest rates have also fallen. As a consequence, the spread between growth rates and interest rates is only somewhat smaller in advanced economies today than it was in the 1950s and 60s and notably higher than it was in the 1980s and 90s (Chart 8). Indeed, as Chart 9 shows, g-r has been trending higher for hundreds of years! Chart 7The Case Of Outgrowing The Debt Burden Post-WWII Chart 8The Rate Of Economic Growth Has Been Higher Than Interest Rates   Chart 9A Multi-Century Trend In The Spread Between Growth And Interest Rates Today, government borrowing rates in most economies are well below trend growth rates. No matter the size of the budget deficit, the ratio of debt-to-GDP will converge to a stable level as long as the interest rate the government pays on the debt is below the growth rate of the economy.4  A Gordian Fiscal Knot Of course, there is no guarantee that real rates will remain below the rate of trend growth. As we have discussed before, the exodus of baby boomers from the labor force, a peak in globalization, and rising political populism could all curtail aggregate supply, leading to a depletion of national savings.5 What would happen if governments allowed debt levels to reach very high levels only to find that the neutral rate of interest — the interest rate consistent with full employment and stable inflation — has risen above the growth rate of the economy? Raising the policy rate would be very painful in a high-debt environment because even a small increase in interest rates would lead to a large rise in interest payments. Faced with this reality, some governments might elect to tighten fiscal policy. An increase in taxes or a decline in government spending would not only create some resources to pay back debt, but it would also reduce aggregate demand, pushing down the neutral rate of interest in the process. Don’t Blame The Stimulus Ironically, all the fiscal relief efforts that governments have carried out over the past few months have probably left them better placed to pay back debt than if no stimulus had been undertaken in the first place. Box 1 illustrates this point with a numerical example, but the intuition for this claim can be seen easily enough. As noted earlier, fiscal stimulus in a depressed economy will raise overall savings. This means that after the pandemic is over, governments will have a larger tax base available to them than they would have had in the absence of any stimulus (although, obviously, the tax base would be even larger if the pandemic had never occurred). The Inflation Solution Chart 10Long-Term Inflation Expectations Remain Very Depressed Still, any decision to tighten fiscal policy down the road is going to be an inherently political one. What if governments do not have the political will to tighten fiscal policy even if the economy begins to overheat? Defaulting on the debt is always an option in that case, but not one that any sensible government would choose given the devastating impact this would have on the financial system and broader economy. Rather, it is conceivable that governments will lean on central banks to keep rates low and let inflation accelerate. While higher inflation will not boost real GDP, it will raise nominal GDP, allowing the ratio of government debt-to-GDP to decline. Investors currently assign very low odds to such an outcome. Long-term market-based inflation expectations remain very depressed (Chart 10). Yet, we think such an eventuality is more plausible than widely believed. As long as inflation does not spiral out of control, central banks are likely to welcome rising prices. A higher inflation rate would make monetary policy more effective by allowing central banks to bring real rates deeper into negative territory whenever the economy falls into recession. Higher inflation would also result in steeper yield curves, reoxygenating commercial banks’ profitability. Profiting From Higher Inflation The path to higher interest rates is paved with lower rates. In order to generate inflation, central banks will need to keep rates at very low levels even once the economy has returned to full employment. Given that unemployment is quite high today, inflation is not an imminent risk. However, it could become a formidable problem in two-to-three years. Investors should maintain below-benchmark levels of duration in fixed-income portfolios and favor inflation-linked securities over nominal bonds. While gold is no longer super cheap, it remains a good hedge against inflation. The yellow metal should also do well if the dollar weakens during the remainder of this year, as we anticipate. As a countercyclical currency, the dollar tends to fall whenever global growth picks up (Chart 11). Chart 11Gold Will Do Well When The Dollar Weakens As Global Growth Picks Up Chart 12Farmland Would Benefit From High Inflation Lastly, land will gain from low interest rates in the near term and higher inflation in the long term. Farmland and suburban land are particularly appealing. The pandemic has made remote working more commonplace. It has also highlighted the potential dangers of living in densely populated cities. Since most suburbs are built on top of land that was previously zoned for agriculture, farmland should benefit from the retreat from urban living, much like it did during the inflationary period of the 1970s (Chart 12). Box 1Saving More By Spending More   Peter Berezin Chief Global Strategist peterb@bcaresearch.com   Footnotes 1  Please see Global Investment Strategy Weekly Report, “Risks To The U,” dated May 7, 2020. 2  Please see Global Investment Strategy Weekly Report, “Could The Pandemic Lead To Higher Stock Prices?” dated April 23, 2020. 3  Gross Domestic Product (GDP) can be computed as the sum of consumption (C), investment (I), government spending (G), and net exports (X-M). Gross National Product (GNP) is equal to GDP except that the former includes net income from abroad (which is included in the current account balance). Thus, GNP=C+I+G+CA, or GNP-C-G=I+CA. Savings (S) is equal to GNP-C-G. Taken together, the two expressions imply S-I=CA, or S=I+CA. 4  Please see Global Investment Strategy Weekly Report, ”Is There Really Too Much Government Debt In The World?” dated February 22, 2019. 5  Please see Global Investment Strategy Weekly Report, “A Structural Bear Market In Bonds,” dated February 16, 2018. Global Investment Strategy View Matrix Current MacroQuant Model Scores