Developed Countries

Highlights The short-term trade is to overweight the DAX or Euro Stoxx 50… …versus German bunds or the S&P 500. These trades have outperformed since late last year and can continue to do so for a while longer. But moving into the second half of the year, it will be time to take profits in these growth-sensitive trades. The long-term position is to own German real estate equities. The hedged position is long German real estate equities, short Swedish real estate equities. Feature Let’s begin with a trivia question. What do Germany, Finland, and Ireland have in common, that the other EU28 countries do not have? Chart of the WeekEuro Stoxx 50 Vs. S&P500 And EM Vs. DM Have Followed Near Carbon Copy Profiles The answer: Germany, Finland, and Ireland are the only three European countries that have a trade surplus with China.1 Germany Catches A Cold When China Sneezes… Chart 2Slowdown In Germany And Finland, No Slowdown In France And Spain Germany and Finland are the European economies most exposed to China, with 17 percent and 14 percent respectively of their extra-EU28 exports heading to the dominant emerging economy (for Ireland it is only 7 percent). This equates to almost 3 percent of GDP for Germany and around 1.5 percent for Finland. Hence, when China sneezes – as it did last year – Germany and Finland are the European economies most likely to catch a cold. It is not a coincidence that Germany and Finland suffered near identical short-term slowdowns in 2018 with the pain focussed in the third quarter. By contrast, the European economies with much less exposure to China – say, France and Spain – suffered no discernible slowdown (Chart I-2). In fact, Spain seemed completely unaffected, growing at a steady and robust 2 percent clip throughout 2018! The corollary is that when China rebounds – as it has recently – Germany and Finland are the European countries most likely to benefit. Since early January, Germany’s DAX has outperformed the 10-year German bund by 15 percent. For the past three months, the DAX has also outperformed the S&P 500, albeit modestly. The trends can continue for a while, but be warned: these short-term cyclical moves are likely to reverse later in the year, perhaps viciously. More about this later. …But Germany’s Structural Growth Model Has Changed Germany’s gross exports of €1.6 trillion equate to almost half of its €3.4 trillion economy. Inevitably, this makes the German economy highly vulnerable to down-oscillations in global growth as, for example, when China sneezes. But here’s the paradox: while the level of German exports is very high, it has been flat-lining at this elevated level since 2012 (Chart I-3). Hence, Germany is no longer deriving any structural growth from its export sector. All of Germany’s post-2012 structural growth has come from domestic demand. Germany’s structural growth model has changed. Through 1999-2007, Germany’s net export contribution accounted for the vast majority of its structural growth; and in 2008, net exports accounted for two-thirds of Germany’s severe economic contraction. But remarkably, since 2012, net exports have made no contribution to Germany’s structural growth (Chart I-4). Meaning that all of Germany’s post-2012 structural growth has come from domestic demand. Chart 3The Level Of German Exports Is High But Flat-Lining Chart 4Since 2012, Net Exports Have Made No Contribution To Germany's Structural Growth One manifestation of this is the post-2012 recovery in Germany’s real estate market. When Germany was deriving most of its growth from external demand, the domestic real estate market withered. In recent years, when growth has come from domestic demand, Germany’s real estate market has started to flourish (Chart I-5). Chart 5German Real Estate Prices Still Need To Catch Up Chart 6German Real Estate Book Values Have Trebled With Germany’s average house price, in real terms, at the same level as it was in 1995, there is still considerable upside outside the major cities such as Berlin, Frankfurt, and Munich. Especially so, because one of the main enemies of the real estate market – substantially higher bond yields – will be absent for some time.2 The strong performance of German real estate equities – a near trebling since 2012 – is just tracking the strong performance of their book values (Chart I-6), which itself is a leveraged function of real estate prices. On the basis that the real estate sector is benefiting from a structural tailwind, the sector is a long-term hold, but for those who want to hedge their exposure, the recommendation is: long German real estate equities, short Swedish real estate equities. What Is Driving Euro Stoxx Outperformance? In response to this week’s title question, some people will ask: has Euro Stoxx 50 outperformance even started? The answer is a clear yes. Relative to both global equities and the S&P 500, the Euro Stoxx 50 has been in a well-established – though modest – uptrend since last September. Interestingly, emerging markets (EM) versus developed markets (DM) has followed a near carbon copy profile, albeit the outperformance was front-end loaded (Chart of the Week and Chart I-7). Euro Stoxx 50 has been gently outperforming. Can this continue? Recent history is not very encouraging. Since the Global Financial Crisis, no bout of Euro Stoxx 50 outperformance has lasted more than a year (Chart I-8). If this pattern continues to hold, it implies that the current bout of Euro Stoxx 50 outperformance will be exhausted within another four months. Chart 7Euro Stoxx 50 Has Been Gently Outperforming Chart 8Euro Stoxx 50 Vs. S&P500 ##br##Follows…   Chart 9…Euro Area Banks Vs. U.S. Tech Could it be different this time? We think not. Euro Stoxx 50 performance relative to the S&P 500 lines up almost perfectly with the relative performance of euro area banks versus U.S. tech (Chart I-9). Given that this defines the sector skew ‘fingerprint’ of the relative position, this defining relationship is fundamental. Meaning that for the Euro Stoxx 50 to outperform the S&P 500 on a sustained basis, euro area banks have to outperform U.S. tech. Likewise, EM versus DM lines up almost perfectly with the relative performance of global resources versus global healthcare (Chart I-10 and Chart I-11). Again, this is not surprising as this just defines the sector skew fingerprint of EM versus DM. Admittedly, in this case the causality could sometimes run from the EM economy to the sector performance – given China’s role in driving resource demand – rather than from sector relative performance to EM versus DM. Nevertheless, for EM to outperform DM, resources have to outperform healthcare. EM versus DM lines up almost perfectly with the relative performance of global resources versus global healthcare. Since last autumn, Euro Stoxx 50 versus S&P 500 and EM versus DM have followed near carbon copy profiles because growth-sensitive financials and resources have outperformed less growth-sensitive technology and healthcare. Chart 10EM Vs. DM Follows… Chart 11…Basic Resources Vs. Healthcare From Sweet Spot To Weak Spot Nevertheless, there is a puzzle: why have growth-sensitive sectors, the DAX, Euro Stoxx 50, and EM outperformed since late last year when the high-profile hard economic data – such as GDP growth and CPI inflation – have been unambiguously weak? High-profile hard data are a record of what happened in the past. The simple answer is that these high-profile hard data are a record of what happened in the past, sometimes the distant past. Yet they matter because central banks’ increasingly ‘data dependent’ reaction functions have become slaves to this backward-looking data. Here’s the paradox: the ‘sweet spot’ for growth-sensitive sectors and markets is when the high-profile backward-looking data – GDP and inflation – are actually weak, while real-time measures of growth – such as short-term credit impulses – are strengthening. This creates a win-win for markets because the dovish pivot by data-dependent central banks lifts asset valuations and the acceleration in real-time growth lifts profit expectations. Sound familiar? It describes the situation since last autumn, and explains why the DAX, Euro Stoxx 50, and EM have outperformed. Now comes the unfortunate corollary: the ‘weak spot’ for growth-sensitive sectors and markets is when the high-profile backward-looking data are strong, while real-time measures of growth – such as short-term credit impulses – are weakening. This is a lose-lose for markets because the hawkish pivot by central banks weighs on asset valuations and the deceleration in real-time growth depresses profit expectations. Almost certainly, this will be the situation later in the year as the high-profile hard data starts to perk up – removing some of the central bank support for valuations – just as short-term credit impulses inevitably roll over – weighing on profit growth expectations. To sum up, growth-sensitive sectors, the DAX, and Euro Stoxx 50 have outperformed since late last year, especially versus bonds and cash – in line with our house view. These trends can continue for a while longer. But moving into the second half of the year, these growth-sensitive positions will transition from sweet spot to weak spot, and it will be time to take profits. As ever, we will tell you when. Stay tuned.   Dhaval Joshi, Chief European Investment Strategist dhaval@bcaresearch.com Fractal Trading System* This week, we note that that the 65-day fractal dimension for technology versus healthcare is at an all-time low – implying that the recent strong outperformance is highly vulnerable to a technical reversal. Accordingly, this week’s recommended trade is short technology versus healthcare with a profit target of 6.5 percent and a symmetrical stop-loss. In other trades, we are pleased to report that long aluminium versus tin achieved its 6.5 percent profit target at which it was closed. This leaves five open positions. For any investment, excessive trend following and groupthink can reach a natural point of instability, at which point the established trend is highly likely to break down with or without an external catalyst. An early warning sign is the investment’s fractal dimension approaching its natural lower bound. Encouragingly, this trigger has consistently identified countertrend moves of various magnitudes across all asset classes. Chart I-10 The post-June 9, 2016 fractal trading model rules are: When the fractal dimension approaches the lower limit after an investment has been in an established trend it is a potential trigger for a liquidity-triggered trend reversal. Therefore, open a countertrend position. The profit target is a one-third reversal of the preceding 13-week move. Apply a symmetrical stop-loss. Close the position at the profit target or stop-loss. Otherwise close the position after 13 weeks. Use the position size multiple to control risk. The position size will be smaller for more risky positions. * For more details please see the European Investment Strategy Special Report “Fractals, Liquidity & A Trading Model,” dated December 11, 2014, available at eis.bcaresearch.com. Footnotes 1 Based on the EU28 net exports of goods to China in 2018 by Member State. 2 Please see the European Investment Strategy Weekly Report ‘Monetarists, Keynesians, And Modern Monetary Theory’ April 11 2019 available at eis.bcaresearch.com. Recommendations Asset Allocation Equity Regional and Country Allocation Equity Sector Allocation Bond and Interest Rate Allocation Currency and Other Allocation Closed Fractal Trades Trades Closed Trades Asset Performance Currency & Bond Equity Sector Country Equity Indicators Bond Yields Chart II-1Indicators To Watch - Bond Yields Chart II-2Indicators To Watch - Bond Yields Chart II-3Indicators To Watch - Bond Yields Chart II-4Indicators To Watch - Bond Yields Interest Rate Chart II-5Indicators To Watch - Interest Rate Expectations Chart II-6Indicators To Watch - Interest Rate Expectations Chart II-7Indicators To Watch - Interest Rate Expectations Chart II-8Indicators To Watch - Interest Rate Expectations  

Highlights So what? Quantifying geopolitical risk just got easier. Why?   In this report we introduce 10 proprietary, market-based indicators of country-level political and geopolitical risk. Featured countries include France, U.K., Germany, Italy, Spain, Russia, South Korea, Taiwan, Turkey, and Brazil. Other countries, and refinements to these beta-version indicators, will come in due time. We remain committed to qualitative, constraint-based analysis. Our GeoRisk Indicators will help us determine how the market is pricing key risks, so we can decide whether they are understated or overstated. Feature For the past three months we have been tracking a “Witches’ Brew” of political risks that threaten the late-cycle bull market. Some of these risks have abated for the time being: the Fed is on pause, China’s stimulus has surprised to the upside, and Brexit has been delayed. Other risks we have flagged, however, are heating up: Iran And Oil Market Volatility: Surprisingly the Trump administration has chosen not to extend oil sanction waivers on Iran from May 2, putting 1.3 million barrels per day of oil on schedule to be removed from international markets by an unspecified time.  It remains to be seen how rapidly and resolutely the administration will enforce the sanctions on specific allies and partners (Japan, India, Turkey) as well as rivals (China, others). Because the decision coincides with rising production risks from renewed fighting in Libya and regime failure in Venezuela, we expect President Trump to phase in the new enforcement over a period of months, particularly on China and India. But official rhetoric is draconian. Hence the potential for full and immediate enforcement is greater than we thought. In the short term, individual political leaders, and very powerful nations like the United States, can ignore material economic and political constraints. Since the Trump administration’s decision exemplifies this point, geopolitical tail risks will get fatter this year and next. Global oil price volatility and equity market volatility will increase with sanction enforcement actions and retaliation. We would think that Trump’s odds of reelection will marginally suffer, though for now still above 50%, as any full-fledged confrontation with Iran will raise the chances of an oil price-induced recession. U.S.-EU Trade War: Neither the Trump administration nor the U.S. has a compelling interest in imposing Section 232 tariffs on imports of autos and auto parts. Nevertheless the risk of some tariffs remains high – we put it at 35% – because President Trump is legally unconstrained. The decision is technically due by May 18 but Economic Council Director Larry Kudlow has said Trump may adjust the deadline and decide later. Later would make sense given the economic and financial risks of the administration’s decision to ramp up the pressure on Iran.1 But the risk that tariffs will pile onto a weak German and European economy will hang over investors’ heads. U.S.-China Talks Not A Game Changer: The ostensible demand that China cease Iranian oil imports immediately and the stalling of U.S. diplomacy with North Korea are not conducive to concluding a trade deal in May. We have highlighted many times that strategic tensions will persist even if Beijing and Washington quarantine these issues to agree to a short-term trade truce. The June 28-29 G20 meeting in Japan remains the likeliest date for a summit between Presidents Trump and Xi Jinping, but even this timeframe could be too optimistic. Continued uncertainty or a weak deal will fail to satisfy financial markets expecting a very positive outcome.   With a 70% chance that U.S. tariffs on China will not increase this year and, contingent on a U.S.-China deal, only a 35% chance that the U.S. slaps tariffs on German cars, we sound optimistic to some clients. But the Trump administration’s decision on Iran is highly market-relevant and portends greater volatility. We expect to see a geopolitical risk premium creep higher into oil markets as well as a greater risk of “Black Swan” events in strategically critical or oil-producing parts of the Middle East. There is limited research devoted to quantifying geopolitical risk. We are late in the business cycle and President Trump has emphatically decided to increase rather than decrease geopolitical risk. Quantifying Geopolitical Risk Geopolitical analysis has taken a bigger role in investors’ decision-making over the last decade. Surveys show that geopolitical risks rank among global investors’ top concerns overall. In the oft-cited Bank of America Merrill Lynch survey, geopolitical and related issues have dominated the “top tail risk” responses for the past half-decade (Chart 1). In other surveys, the most worrisome short-term risks are mostly political or geopolitical in nature, ranking above socio-economic and environmental risks (Chart 2). Despite this high level of concern, there is limited research devoted to quantifying geopolitical risk. Isolating and measuring the range of risks under this umbrella term remains a challenge. As such, for many investors, geopolitics remains an ad hoc, exogenous factor that is often mentioned but rarely incorporated into portfolio construction. For the past four decades the predominant ways of measuring political or geopolitical risk have been qualitative or semi-qualitative. The Delphi technique, developed on the basis of low-quality data sets in social sciences, relies on pooled expert opinions.2 Independently selected experts are asked to provide risk assessments and their responses are then interpreted by analysts to create a measure of risk. Another semi-qualitative method of measuring geopolitical risk ranks countries according to a set of political and socio-economic variables. These variables – such as governance, political and social stability, corruption, law and order, or formal and informal policies – are extremely important but inherently difficult to quantify.3 These results are useful but suffer from dependency on expert opinion, data quality, and institutional biases. More importantly, these methods are slow to react to breaking events in a rapidly changing world. The same goes for bottom-up assessments using political intelligence. The weakness of these methods is that it is highly unlikely that they will produce statistically significant estimates of risk. The odds of getting a “silver bullet” insight from a “key insider” are decent for simple political systems, but not in the complex jurisdictions that host the vast majority of global, liquid investments. Quantitative approaches to measuring geopolitical risk have since become more widespread. The most prominent method is based on quantifying the occurrence of words related to political and geopolitical tensions that appear in international newspapers. These word-counts typically include terms like “terrorism,” “crisis,” “war,” “military action,” etc. As a result, the indices reflect incidents of physical violence or other “Black Swan” events that may not have direct relevance to financial markets. Moreover, while news-based indices accurately capture dramatic one-time peaks at the time of a crisis, they are largely flat aside from these, as they rely on popular topics rather than underlying structural trends (Chart 3). They fail to capture geopolitical developments associated with electoral cycles, protest movements, paradigm shifts in economic policy, or other policy changes.4 Notice, for instance, that the fall of the Soviet Union in late 1991 and the resulting chaos in Russia and many other parts of the emerging world hardly register in Chart 3. Chart 3News-Based Indices Only Capture Crisis Peaks, Not Geopolitical Developments Introducing BCA’s GeoRisk Indicators The past 70 years have taught BCA Research to listen and respect the market. Why would we suddenly follow the media instead? Most quantitative geopolitical indicators begin with the premise that journalists and the news-reading public have accurately emphasized the most relevant risks and uncertainties. They proceed to quantify the terms of these assessments with increasingly sophisticated methods. This approach solves only part of the puzzle. News-based indices ... fail to capture geopolitical developments associated with underlying policy changes. At BCA Geopolitical Strategy, we aim to generate geopolitical alpha.5 This means identifying where financial media and markets overstate or understate geopolitical risks. We do not primarily aim to predict events or crises. As such, traditional news-based indicators that capture only major events, even those ex post facto, are of little relevance to our analysis. What is needed is a better way to quantify how the market is calculating risks. We start with a simple premise: the market is the greatest machine ever created for gauging the wisdom of the crowd. Furthermore, it puts its money where its predictions are, unlike other methods of geopolitical risk quantification which have no “value at risk.” Chart 4USD/RUB Captures Geopolitical Risk In Russia... To this end, we have introduced market-based indicators over the years that rely on currency movements, which are often the simplest and most immediate means of capturing the process of pricing risk. In 2015, for instance, we introduced an indicator that measures Russia’s geopolitical risk premium (Chart 4). It is constructed using the de-trended residual from a regression of USD/RUB against USD/NOK and Russian CPI relative to U.S. CPI. We can show empirically that it captures geopolitical risk priced into the ruble, as the indicator increases following critical incidents. These include the downing of Malaysian Airlines Flight 17 over eastern Ukraine in 2014; the warnings that Russia aimed to stage a “spring offensive” in Ukraine in 2015; Russian military intervention in the Syrian Civil War later that year; and the poisoning of former intelligence agent Sergei Skripal in the U.K. in 2018 and subsequent tensions. Using similar methods, we created a proxy to capture geopolitical risk in Taiwan, based on USD/JPY and USD/KRW exchange rates and relative Taiwanese/American inflation (Chart 5). The indicator tracks well with previous cross-strait crises. It jumped upon Taiwan’s election of President Tsai Ing-wen and her pro-independence government in January 2016 – and this was well before any tensions actually flared. It even registered a small increase upon her controversial phone call congratulating Donald Trump upon winning the U.S. election. Chart 5...And USD/TWD Captures Geopolitical Risk In Taiwan This year we have expanded on this work, constructing a set of ten standardized GeoRisk Indicators for five developed economies and five emerging economies: U.K., France, Germany, Spain, Italy, Russia, Turkey, Brazil, Korea, and Taiwan. Indicators for the U.S., China, and others will be rolled out in a future report. These indicators attempt to capture risk premiums priced into the various currencies – except for Euro Area countries, where the risk is embedded in equity prices. In each case, we look at whether the relevant assets are decreasing in value at a faster rate than implied by key explanatory variables. The explanatory variables consist of (1) an asset that moves together with the dependent variable while not responding to domestic geopolitical risks, and (2) a variable to capture the state of the economy. This set of indicators differs from our earlier indicators in the following ways: We aim to create a simple methodology that we can apply consistently to all countries, both in the DM and EM universes. We therefore omitted using regression models that can prove to be quite whimsical. Instead, we simply looked at the deviation of the dependent variable from the explanatory variables, all in expanding standardized terms, to create the GeoRisk proxy. We wanted an indicator that would immediately respond to priced-in risks, so we opted for a daily frequency rather than the weekly frequency we used in our initial work. To get as accurate of a signal as possible, we use point-in-time data. Since economic data tends to be released with a one-to-two-month lag, we lagged the economic independent variable to correspond to its release date. All ten indicators are shown in the Appendix. Across all countries, they track well with both short-term events and long-term trends in geopolitical risk. In the case of France, for example, the indicator steadily climbs during the period of domestic tensions and protests in the early 2000s; as the European debt crisis flares up; again during the rise of the anti-establishment Front National and the Russian military intervention in Ukraine; and finally during the U.S. trade tariffs and Yellow Vest protests (Chart 6). Our GeoRisk indicators isolate risks that either originate internally or otherwise affect the country more so than others. Similarly, in Germany, there is a general increase in perceived risk as Chancellor Gerhard Schröder implements structural reforms in the early 2000s; another increase leading up to the leadership change as Angela Merkel is elected Chancellor; another during the global and European financial crises; another during the Ukraine invasion and refugee influx; and finally another with the U.S.-China trade war (Chart 7). Chart 6Our French Indicator Picks Up Domestic And European Unrest Chart 7Greater German Risk Amid The Trade War   We have annotated each country’s GeoRisk indicator heavily in the appendix so that readers can see for themselves the correspondence with political events. The indicators are affected by international developments – like the Great Recession – but we have done our best to isolate risks that either originate internally or otherwise affect the country more than other countries. (As a consequence, the Great Recession is muted in some cases.) What are the indicators telling us now? Most obviously, they highlight the extreme risk we have witnessed in the U.K. over the now-delayed March 29 Brexit deadline. We would bet against this risk as the political reality has demonstrated that a “hard Brexit” is very low probability: the U.K. has the ability to back off unilaterally while the EU is willing to extend for the sake of regional stability. In this sense the pound is a tactical buy, which our foreign exchange strategist Chester Ntonifor has highlighted.6 Our U.K. risk indicator has been fairly well correlated with the GBP/USD since the global financial crisis and it suggests that the pound has more room to rally (Chart 8). Chart 8Betting Against A Hard Brexit, the GBP Is A Tactical Buy Meanwhile, Spanish risks are overstated while Italy’s are understated. As for the emerging world, Turkish risks should be expected to spike yet again, as divisions emerge within the ruling coalition in the wake of critical losses in local elections and a failure to reassure investors over monetary policy and the currency. Brazilian risks will probably not match the crisis points of the impeachment and the 2018 election, at least not until controversial pension reforms reach a period of peak uncertainty over legislative passage. Both our new Russian indicator and its prototype are collapsing (see Chart 4 above). This captures the fact that we stand at a critical juncture in Russian affairs, where President Putin is attempting to shift focus to domestic stability even as the U.S. and the West maintain pressure on the economy to deter Russia from its aggressive foreign policy. Given that both Putin’s and the government’s approval ratings are low amid rising oil prices, the stage is set for Russia to take a provocative foreign policy action meant to distract the populace from its poor living conditions. Venezuela is the obvious candidate, but there are others. Moscow will want to test Ukraine’s newly elected, inexperienced president; it may also make a show of support for Iran. With Russia equities having rallied on a relative basis over the past year and a half, and with the Iranian waiver decision already boosting oil prices as we go to press, the window of opportunity to buy Russian stocks is starting to close. (We remain overweight relative to EM on a tactical horizon; our Emerging Markets Strategy is also overweight.) Going forward, we will update these risk indicators regularly as needed and publish the full appendix at the end of every month along with our long-running Geopolitical Calendar. We will also fine-tune the indicators as new information comes to light. In other words, here we present only the beta version. We hope that these indicators will help inform investors as to the direction, and even magnitude, of political risks as the market prices them. Our GeoRisk indicators are not predictive, as establishing a trend is not a prediction. The main purpose of this exercise is to answer the critical question, “What is already priced in?” How is the market currently calculating geopolitical risk for a country? After that, it is the geopolitical strategist’s job to unpack this question through qualitative, constraint-based analysis. It is when our qualitative assessments disagree with what is priced in that we can generate geopolitical alpha.    Ekaterina Shtrevensky, Research Analyst ekaterinas@bcaresearch.com Matt Gertken, Vice President Geopolitical Strategist mattg@bcaresearch.com Marko Papic Consulting Editor marko@bcaresearch.com Footnotes 1      See Sean Higgins, “Auto tariffs decision could be delayed, Kudlow says,” Washington Examiner, April 3, 2019, www.washingtonexaminer.com. 2      Norman C. Dalkey and Olaf Helmer-Hirschberg, “An Experimental Application of the Delphi Method to the Use of Experts,” Management Science, Vol. 9, Issue: 3 (April 1963) pp. 458- 467. 3      Darryl S. L. Jarvis, “Conceptualizing, Analyzing and Measuring Political Risk: The Evolution of Theory and Method,” Lee Kuan Yew School of Public Policy Research Paper No. LKYSPP08-004 (July 2008).  William D. Coplin and Michael K. O'Leary, "Political Forecast For International Business," Planning Review, Vol. 11 Issue: 3 (1983) pp.14-23. The PRS Group, “Political Risk Services”™ (PRS) or the “Coplin-O’Leary Country Risk Rating System”™ Methodology. Daniel Kaufmann, Aart Kraay, and Massimo Mastruzzi, “The Worldwide Governance Indicators: Methodology and Analytical Issues,” World Bank Policy Research Working Paper No. 5430 (September 2010). 4      Scott R. Baker, Nicholas Bloom, and Steven J. Davis, “Measuring Economic Policy Uncertainty,” The Quarterly Journal of Economics, Volume 131, Issue 4, November 2016 (July 2016) pp.1593–1636. Dario Caldara and Matteo Iacoviello, “Measuring Geopolitical Risk,” Board of Governors of the Federal Reserve Board, Working Paper (January 2018). 5      Please see BCA Research Geopolitical Strategy Special Report, “Five Myths On Geopolitical Forecasting,” dated July 9, 2018, available at gps.bcaresearch.com. 6      Please see BCA Foreign Exchange Strategy Weekly Report, “Not Out Of The Woods Yet,” April 5, 2019, available at www.bcaresearch.com.   Appendix Appendix France Appendix U.K. Appendix Germany Appendix Italy Appendix Spain Appendix Russia Appendix Korea Appendix Taiwan Appendix Turkey Appendix Brazil What’s On The Geopolitical Radar?      Geopolitical Calendar

Overweight We upgraded the S&P oil & gas refining & marketing index last month all the way from underweight to overweight based on the dramatic divergence between improving fundamentals and a zealously pessimistic sell-side. While the index has moved sideways since we made the change, our thesis has been reinforced by industry dynamics. The Wall Street Journal reported yesterday that domestic gasoline prices have been rising uninterrupted for the past 69 days, a 15-year record. This is confirmed by rapidly declining gasoline inventories (inventories shown inverted, second panel) and, in combination with higher prices, are driving a surge in refiner crack spreads (second panel). Refining margins have historically defined the direction of relative profit growth and the current message is positive. However, sell-side estimates continue to point to relative earnings underperformance despite the brightening outlook (bottom panel). Bottom Line: A gap between fundamentals and estimates has opened in the S&P oil & gas refining & marketing index and has created a compelling buying opportunity. Stay overweight. The ticker symbols for the stocks in this index are: BLBG: S5OILR – PSX, MPC, VLO, HFC.

Overweight A number of macro factors have fallen into place that have warmed us to the S&P movies & entertainment index. Consumer confidence remains glued to multi-decade highs and there are high odds that the big gulf that has opened up between confidence and relative share prices will narrow via a rise in the latter (top panel). Moreover, a vibrant labor market with payrolls expanding at a healthy clip (second panel), the unemployment rate and unemployment insurance claims at generational lows, all signal that consumers will keep their purse strings loose, especially given rising wages (third panel). More dollars spent on recreation is synonymous with a margin expansion in the S&P movies & entertainment index (bottom panel). This consumer spending backdrop is also conducive to a rise in relative profitability, the opposite of what the sell-side currently expects. Bottom Line: We lifted the S&P movies & entertainment index to overweight on Monday; please see our Weekly Report for more details. The ticker symbols for the stocks in this index are: BLBG: S5MOVI – DIS, NFLX, VIAb.

Special Report

Highlights Corporate Debt In Theory: Conventional theory holds that high levels of corporate debt pose a risk to the economy because they make the corporate sector more vulnerable to exogenous economic shocks. Corporate Debt In Practice: The conventional theory is contradicted by empirical evidence that links rapid private debt growth to negative economic outcomes, but shows no relationship between high debt levels and slow economic growth. The empirical evidence also links measures of credit market sentiment – such as corporate bond spreads – to future economic outcomes. We present an alternative theory of the corporate credit cycle that better aligns with the observed empirical results. The Current Risk: At present, the corporate debt measures that have historically been linked to weaker economic growth paint a fairly benign picture. We see no immediate risk to the U.S. economy from elevated corporate debt. Feature In our interactions with clients we are often asked whether corporate debt poses a risk to the U.S. economy. It’s easy to see why, U.S. nonfinancial corporate debt as a percent of GDP is higher than at any time since 1936 (Chart 1). Chart 1U.S. Corporate Debt: Highest Since 1936! This Special Report investigates the issue by looking at what recent academic theory and empirical evidence have to say about the relationship between corporate debt and economic growth. We then apply that evidence to today’s corporate debt situation to assess the economy’s current level of risk. We should note that this report focuses on potential risks stemming from the amount of outstanding debt, how quickly it is growing and how it is valued in financial markets. In a follow-up report, we will consider whether the ownership structure of the corporate bond market imparts additional risks to the economy and financial system. The Risk From Corporate Debt In Theory Conventional economic theory tells us that we should be concerned about elevated private sector debt because high debt makes the economy more vulnerable in the face of future shocks. Case in point, here is how the Federal Reserve’s Financial Stability Report describes the mechanism through which private sector debt impacts the economy: Excessive borrowing by businesses and households leaves them more vulnerable to distress if their incomes decline or the assets they own fall in value. In the event of such shocks, businesses and households with high debt burdens may need to cut back spending sharply, affecting the overall level of economic activity.1 This theory raises a few issues that we will consider in the remainder of this report: The theory suggests that the absolute amount of private sector debt matters more than its rate of growth. The theory suggests that elevated debt leads to a more severe economic downturn, but doesn’t necessarily cause the downturn. In other words, high debt simply makes the economy more vulnerable to exogenous shocks. The theory suggests that household debt and corporate debt are equally important. The Empirical Record Level Versus Growth While conventional theory implies that the crucial variable to monitor is the level of private sector debt, recent empirical evidence challenges this view. For example, a 2017 Bank of England paper considered a sample of 130 recessions across 26 countries and found that the rate of private debt growth matters much more.2 Please note that in the remainder of this report we define “debt growth” as the 3-year change in the debt-to-GDP ratio. Specifically, the researchers found a statistically and economically significant link between the severity of the recession – defined as the drawdown in per capita GDP – and the 3-year change in private debt-to-GDP that immediately preceded the downturn. They found no similar relationship using the level of private debt-to-GDP. In fact, the researchers found that the level of private debt to GDP only helped explain the severity of the recession when it was interacted with the rate of private debt growth. To quote from the paper: It appears that the level of credit before a recession matters for the severity of the downturn only when it is accompanied by a credit boom. By contrast, periods of fast credit growth appear to be associated with more severe recessions whether or not the level of credit is elevated.3 These findings suggest that the conventional theory presented above – that high debt levels make the private sector more vulnerable to exogenous shocks – is not the principle mechanism at work. We need an alternative theory to explain why the rate of debt growth is the more important variable to monitor. We discuss a possible alternative theory in the section titled “Toward A Better Theory” below. But for now, let’s consider the current state of the U.S. economy in light of the Bank of England’s findings. Chart 2 shows that the level of U.S. private sector debt-to-GDP is elevated compared to history. In fact, using data beginning in 1955, it was only higher in the run-up to the 2008 financial crisis. However, the second panel of Chart 2 shows that private sector debt growth is only 2.5%, a far cry from what was seen prior to the last three recessions. Chart 2Recession Watch: Private Debt Growth And Inflation We don’t mean to imply that a recession cannot occur with low private debt growth, but the track record of post-WWII U.S. recessions shows that every single one was preceded either by elevated private debt growth – 8% or above – or high inflation. At present, the U.S. economy shows very little risk on either front. Household Debt Versus Corporate Debt So far we’ve looked at private sector debt in total, i.e. we have combined household debt and nonfinancial corporate debt. This arguably masks the true instability in the U.S. economy, which is concentrated in the corporate sector. Chart 3 shows that low overall private sector debt growth of 2.5% is split between relatively quick corporate debt growth of 4.2% and household debt that is contracting at a rate of 1.8%. If we ignore the household sector’s persistent deleveraging, we see that current corporate debt growth of 4.2% is not that far below the peaks of 6.9%, 7.9% and 8% seen prior to each of the last three recessions. Chart 3U.S. Private Debt Growth Is Driven By Corporate Sector This raises two interesting questions. First, are corporate debt and household debt equally de-stabilizing for the economy? And relatedly, when tracking the U.S. economy should we focus on overall private sector debt, or should we monitor household and corporate sector debt individually? The track record of post-WWII U.S. recessions shows that every single one was preceded either by elevated private debt growth or high inflation. On the first question, we can turn back to the Bank of England paper. That paper presented the results from several regressions where the researchers looked at household debt growth and corporate debt growth individually. The results showed that elevated household debt growth and elevated corporate debt growth were both associated with more severe recessions, and with roughly equal coefficients. In the words of the researchers: Rapid credit growth continues to be an important predictor of the severity of a recession whether we look at lending to non-financial companies or to households, suggesting that the role of lending to businesses should not be ignored. Interestingly, this result stands in contrast to some other recent empirical work. Most notably, a 2016 paper by Atif Mian, Amir Sufi and Emil Verner (MSV). That paper looked at a panel of 30 countries between 1960 and 2012 and found that while higher household debt growth is associated with lower subsequent GDP growth, no such correlation is found with corporate debt.4 MSV summarize their basic result as follows: There is a significant negative correlation between changes in private debt and future output growth. Moreover, this negative correlation is entirely driven by the growth in household debt. The magnitude of the negative correlation is large, with a one standard deviation increase in the change in household debt to GDP ratio (6.2 percentage points) associated with a 2.1 percentage point lower growth rate during the subsequent three years. The main difference between the MSV methodology and that used by the Bank of England is that the MSV paper looks at GDP growth unconditional on whether there is a recession. In contrast, the Bank of England paper looks only at recessionary periods. A look back at past U.S. recessions makes us reluctant to ignore corporate debt growth completely. Table 1 lists every post-WWII U.S. recession, showing the peak-to-trough drawdown in GDP as a measure of the recession’s severity along with prior peaks in private debt growth, household debt growth, corporate debt growth and inflation. Table 1A History Of Post-WWII U.S. Recessions Table 1 confirms what we already stated above, that every post-WWII U.S. recession has been preceded by either rapid private sector debt growth or high inflation. If we dig deeper and look at the breakdown between household debt growth and corporate debt growth we find that there have only been two recessions where peak corporate debt growth exceeded peak household debt growth. Current corporate debt growth of 4.2% is not that far below the peaks of 6.9%, 7.9% and 8% seen prior to each of the last three recessions. The first such recession occurred in 1973-75, but that recession was clearly driven by high inflation. Both household and corporate debt growth were quite low during that period. The second example is the 2001 recession. Private debt growth was elevated prior to the 2001 recession, and more heavily concentrated in the corporate sector. However, it’s important to note that the 2001 recession was also the mildest post-WWII U.S. recession. Main Takeaways We draw several conclusions from our review of the empirical research: First, we should pay attention to the rate of growth in private debt-to-GDP and downplay the level of private debt-to-GDP. The latter has very little predictive power on its own. Second, a U.S. recession is unlikely to occur in the absence of elevated private sector debt growth (above ~8%) or high inflation. At the moment, neither factor suggests that the U.S. economy is on the cusp of a downturn. Third, we should not ignore corporate debt growth. However, the MSV research suggests it might be less economically important than household debt growth. Further, the Bank of England paper shows that the severity of any future downturn is equally sensitive to both household and corporate debt, suggesting that it is reasonable to combine the two and use overall private sector debt growth as our key metric when assessing risks to the economy. Finally, the empirical research suggests that the theory of how corporate debt relates to the economy that was presented in the first section of this report is at best incomplete. That theory cannot explain why the rate of debt growth is associated with weaker economic activity, but the level of debt is not. Fortunately, some recent research proposes a few alternative theories that better align with the empirical results. These theories also suggest a few other measures of corporate credit risk that are important for investors to monitor. Looking Beyond Debt Growth So far we have focused on the difference between the level of corporate debt and the rate of corporate debt growth, but recent empirical research has also linked several other measures of ebullient credit market sentiment to future slow-downs in economic activity. Assessing Credit Market Sentiment For example, a 2016 paper by David Lopez-Salido, Jeremy Stein and Egon Zakrajsek (LSZ) shows, using U.S. data from 1929 to 2013, that “when corporate bond spreads are narrow relative to their historical norms and when the share of high-yield bond issuance in total corporate bond issuance is elevated, this forecasts a substantial slowing of growth in real GDP, business investment, and employment over the subsequent few years. Thus buoyant credit-market sentiment today is associated with a significant weakening of real economic outcomes over a medium-term horizon.”5 Before getting into the possible reason for this finding, let’s quickly look at how the U.S. economy stacks up with regard to credit market sentiment. First, the spread between Baa-rated corporate bonds and the 10-year U.S. Treasury yield – the spread measure used in the LSZ paper – is slightly above its historical average, and does not look stretched compared to history (Chart 4). Chart 4U.S. Credit Spreads Aren't Stretched Second, even a more conventional spread measure like the average option-adjusted spread from the Bloomberg Barclays Investment Grade Corporate Bond index remains fairly wide (Chart 5). Chart 5Junk Share Of New Issuance Is Falling Third, the high-yield share of new corporate bond issuance was elevated early in the recovery, especially compared to last cycle, but has declined in recent years (Chart 5, panel 2). Relatedly, the par value of outstanding junk debt as a proportion of the total par value of corporate debt has been falling since 2015 (Chart 5, bottom panel). Does Elevated Credit Market Sentiment Cause Slower Economic Growth? Of course, the empirical finding that tight credit spreads predict slower economic growth could simply reflect the fact that credit spreads respond to swings in the economic data. If our goal is to forecast economic growth, then this would suggest that we don’t need to pay much attention to credit spreads, because they are simply reflecting swings in the economy rather than causing them. However, the empirical evidence increasingly suggests that there is a causal mechanism at play. To test this, the LSZ paper employs a two-step regression procedure. In the first step, researchers model the future change in credit spreads based on the lagged level of credit spreads and the junk share of new issuance. In the second step, they use the fitted value from the first regression to predict changes in economic activity. The fact that the fitted value is significantly related to changes in economic activity implies that there is some predictable mean reversion in credit market sentiment, unrelated to economic fundamentals, that actually exerts an influence on future economic growth. LSZ suggest the following causal mechanism: Heightened levels of sentiment in credit markets today portend bad news for future economic activity. This is because mean reversion implies that when sentiment is unusually positive today, it is likely to deteriorate in the future. Moreover, a sentiment-driven widening of credit spreads amounts to a reduction in the supply of credit, especially to lower credit-quality firms. It is this reduction in credit supply that exerts a negative influence on economic activity. It follows from this analysis that if we could show that corporate bond spreads are tight relative to their “economic fair value”, then the economy would be at even greater risk from a mean reversion in credit market sentiment. While it’s difficult to identify a true “fair value” for credit spreads, Simon Gilchrist and Egon Zakrajsek (GZ) have calculated an Excess Bond Premium that measures the excess spread available in a sample of corporate bonds after removing a bottom-up estimate of expected default losses.6 Expected default losses are estimated using the Merton model and each firm’s market value of equity and face value of debt.7 Using this new measure, GZ find that “over the past four decades, the predictive power of credit spreads for economic downturns is due entirely to the Excess Bond Premium”. This stunning result is the most compelling evidence yet that swings in credit market sentiment actually cause shifts in economic activity, rather than simply reflect them. Looking at the GZ Excess Bond Premium today, we see that while it had been negative for most of the current cycle, it recently ticked above zero and has yet to recover (Chart 6). For the time being, there is no evidence of excessively optimistic credit market sentiment. Chart 6U.S. Credit Spreads Are High Relative To Fundamentals Toward A Better Theory So far we’ve seen that rapid debt growth is a better predictor of future economic weakness than high debt levels. We’ve also seen evidence that optimistic credit market sentiment (tight credit spreads, especially relative to fundamentals, and an elevated junk share of new issuance) forecasts, and likely causes, future economic weakness. Clearly, we need a better theory for why corporate debt matters for the economy than the one provided by the Federal Reserve in the first section of this report. In our view, the theory that most closely aligns with the empirical data is Nicola Gennaioli and Andrei Shleifer’s theory of Diagnostic Expectations, as detailed in their 2018 book A Crisis Of Beliefs.8 In the book, the author’s demonstrate how investors systematically overreact to new economic information. A tendency that makes forecast errors highly predictable. For example, Chart 7 shows that forecasts for what the Baa/Treasury spread will be in one year’s time are tightly linked with today’s actual spread. This means that investors inevitably expect too much future spread widening when spreads are high, and too much future tightening when spreads are low. Chart 7Forecast Errors Are Predictable Gennaioli and Shleifer integrate this systematic behavioral bias into a model that, from our perspective, better aligns with the empirical data on the relationship between corporate debt and the real economy. According to Gennaioli and Shleifer: Good economic news […] makes right-tail outcomes representative. This leads investors to both overestimate average future conditions and to neglect the unrepresentative downside risk, causing overexpansion of both leverage and real investment. When good news stops coming, investors revise their expectations down, even without adverse shocks. These revisions cause credit spreads to revert, the lenders to perform poorly, and economic and financial conditions to deteriorate, leading to deleveraging and cuts in real investment. A severe crisis occurs if arriving news is sufficiently bad as to render left-tail outcomes representative and hence overstated. This theory would seem to explain all of the key empirical findings. Investors form their expectations based on an overreaction to recent news. During an economic recovery this causes credit spreads to tighten and debt to grow rapidly. Eventually, investors realize that expectations have become unrealistically optimistic, credit spreads mean-revert and debt growth plunges. Crucially, in this model a severe economic shock is not required for credit spreads to mean-revert, only a lack of further good news to confirm investor over-optimism. Based on this theory, if we are concerned about the impact of corporate debt on the real economy we should predominantly track measures of credit market sentiment and the rate of debt growth. The theory helps reveal why the level of corporate debt has little informational value. Concluding Thoughts Conventional theory tells us that high corporate debt levels could pose a risk to the economy because they make the corporate sector more vulnerable in the face of exogenous economic shocks. However, empirical evidence suggests that this theory is of little practical value. A better theory is one where investors and corporate managers overreact to positive economic news, leading to overvaluation in credit markets and rapid debt growth. Then, when sentiment is revealed to be overly optimistic, it leads to a mean-reversion in credit spreads and a tightening of credit supply that actually causes a period of weaker economic growth. Investors inevitably expect too much future spread widening when spreads are high, and too much future tightening when spreads are low. It follows from this theory that if we are concerned about the impact of corporate debt on the real economy we should predominantly track debt growth and measures of credit market sentiment such as credit spreads and the junk share of new issuance. The U.S. economy currently looks quite stable by these measures. Overall private sector debt growth is only 2.5%. Historically, it has been above 8% prior to recessions that weren’t caused by high inflation. The GZ Excess Bond Premium also shows that credit market sentiment is not currently stretched relative to fundamentals. Ryan Swift, U.S. Bond Strategist rswift@bcaresearch.com   Footnotes 1      https://www.federalreserve.gov/publications/files/financial-stability-report-201811.pdf 2      https://www.bankofengland.co.uk/working-paper/2017/down-in-the-slumps-t… 3      Please note that the Bank of England paper uses the term “credit” in place of “debt”. In this report we use both terms interchangeably. 4      https://chicagounbound.uchicago.edu/cgi/viewcontent.cgi?article=1050&co… 5      https://www.nber.org/papers/w21879 6      https://www.federalreserve.gov/econresdata/notes/feds-notes/2016/recession-risk-and-the-excess-bond-premium-20160408.html 7      Merton, Robert C., “On The Pricing Of Corporate Debt: The Risk Structure of Interest Rates”, The Journal of Finance, Vol. 29, No. 2, May 1974. 8      Nicola Gennaioli and Andrei Shleifer, A Crisis Of Beliefs: Investor Psychology And Financial Fragility, Princeton University Press, 2018.

Highlights Portfolio Strategy Disney’s recent streaming pricing disclosure and a favorable macro backdrop for recreation PCE argue that more gains are in store for the S&P movies & entertainment index. The price of credit, credit quality and credit growth along with equity buybacks all suggest that bank profits will continue to overwhelm. Recent Changes Upgrade the S&P movies & entertainment index to overweight today. Table 1   Feature Equities continued to defy gravity last week as the earnings season warmed up and did not reveal any “skeletons in the closet”. Lower interest rates single-handedly explain the recent stock market exuberance (Treasury yield shown inverted, Chart 1). In more detail, the Fed’s complete pivot has suppressed the 10-year Treasury yield and last year’s forward multiple drubbing – to the tune of a 30% drawdown – has reversed. Chart 1Lower Yield = Higher Multiple Chart 2 shows that, year-to-date, the forward multiple has done all the heavy lifting in the SPX and then some, as EPS have actually subtracted from the broad market’s return. In theory, a lower discount rate should boost the multiple and vice versa. Nevertheless, there are good odds that the 10-year Treasury yield has troughed, and BCA’s fixed income strategists continue to expect a selloff in the bond market for the rest of the year. The implication is that equities are becoming fully priced and if profits fail to pick up the baton from the multiple expansion phase, the risk/reward tradeoff is to the downside on a tactical horizon. Meanwhile, there are a number of indicators we track that are still firing warning shots for the overall equity market. Margin debt has stalled and remains 13% below the all-time peak hit last year. Historically, this has been a coincident equity market indicator and a lack of confirmation is troublesome for the overall equity market (bottom panel, Chart 3). Chart 2SPX Return Explained Chart 3M&A Lull... M&A activity has taken a step back, with the total number of deals down 25% from the 2018 zenith (top panel, Chart 3). Similar to margin debt uptake, this is a coincident indicator and the latest weak reading is cause for concern, as it signals that animal spirits are low. With regard to frail sentiment, CEO confidence has taken a beating of late on all fronts. The most recent Business Roundtable and Conference Board CEO surveys reveal that chief executives are a worried bunch. Their views on the overall economic outlook, all industries (including services manufacturing, durable and non-durable), capital outlays, employment, and revenues all remain downbeat, and likely explain the recent M&A lull (Chart 4). On the profit front, last year’s once in a lifetime equity retirement will not repeat this year, warning that artificial EPS growth will weigh on overall profit growth in 2019. Beyond this grim reading on “soft data”, select financial market leading indicators are also not corroborating the euphoric equity market. J.P. Morgan’s EM FX index has petered out recently and both EM and Chinese investable stocks (in U.S. dollar terms) remain well below their early-2018 peaks. Similarly, China-levered U.S. semi equipment stocks are a far cry from their cyclical highs set last year and suggest that some caution is still warranted in the broad equity market (Chart 5). Chart 4...Drop In CEO Confidence... Chart 5...And Financial Indicators Still Flashing Red Finally, on the profit front, last year’s once in a lifetime equity retirement will not repeat this year, warning that artificial EPS growth will weigh on overall profit growth in 2019. In addition, Charts 6A & 6B show that buybacks are already concentrated in a few sectors. Our sense is that this concentration theme will continue this year and likely center around financials as banks will flex their equity retirement muscle.   This week we delve deeper into banks and upgrade a communication services subsector. “A Kind Of Magic” Factors have fallen into place to boost the recently rejigged S&P movies & entertainment index to an above benchmark allocation today. DIS and NFLX dominate this index now comprising roughly 97% of the market cap weight and VIAb is merely the third wheel. The dust has settled from the global media industry M&A frenzy of the past two years, but the push to the cloud via online streaming services suggests that it is only a temporary break. We would not rule out another round of inter- and intra-industry M&A, as content is king once again (Chart 7). Chart 7Rejigged Recent pricing news of Disney’s streaming service, expected later this year, sent reverberations across the media space as Disney priced it at such a low point in order to grab market share and likely pave the way for future price hikes. While streaming services have been mushrooming, there is space for a number of competitors, signaling that Netflix’s global streaming domination will not come crumbling down all of a sudden. While the index’s 12-month forward EPS took a hit with the NFLX addition in October, 2018 and the forward P/E jumped to the historical mean, this niche communication services subgroup is now clearly a growth index and will continue to command a premium valuation to the broad market (bottom panel, Chart 8). From a macro perspective there are also compelling reasons to warm up to the S&P movies & entertainment index. Consumer confidence remains glued to multi-decade highs and there are high odds that the big gulf that has opened up between confidence and relative share prices will narrow via a rise in the latter (top panel, Chart 8). Moreover, a vibrant labor market with payrolls expanding at a healthy clip (top panel, Chart 9), the unemployment rate and unemployment insurance claims at generational lows, all signal that consumers will keep their purse strings loose, especially given rising wages (third panel, Chart 9). Chart 8Positive Macro... Chart 9...Drivers... Tack on the confidence consumers have in residential real estate with house prices expanding both on a year-over-year and on a shorter-term basis (second panel, Chart 9), and the ingredients are in place for an increase in consumer recreation outlays. Disney’s streaming pricing disclosure, a favorable macro backdrop on recreation PCE and sell-side analyst extreme profit pessimism argue that more gains are in store for the S&P movies & entertainment index. Lift to overweight today. One final macro variable that is also on the side of the S&P movies & entertainment index is the ISM non-manufacturing index. Historically, real outlays on recreation activities has moved in lockstep with the ISM services survey and the current message is positive for PCE on recreation (bottom panel, Chart 9). More dollars spent on recreation is synonymous with a margin expansion in the S&P movies & entertainment index (third panel, Chart 8). This consumer spending backdrop is also conducive to a rise in relative profitability, the opposite of what the sell-side currently expects (middle panel, Chart 10). Chart 10...But Analysts Are Not Buying It Not only are industry EPS slated to trail the SPX by 300bps in the coming year, but also analysts have been vigorously downgrading their EPS estimates weighing on the sector’s net earnings revisions ratio (bottom panel, Chart 10). This is contrarily positive and we would lean against such analyst pessimism. Netting it all out, Disney’s streaming pricing disclosure, a favorable macro backdrop for recreation PCE and sell-side analyst extreme profit pessimism argue that more gains are in store for the S&P movies & entertainment index. Bottom Line: Lift the S&P movies & entertainment index to overweight today. The ticker symbols for the stocks in this index are: BLBG: S5MOVI – DIS, NFLX, VIAb. Bank Update: Primed For A Re-rating By the end of last week most banks reported profits that exceeded expectations and investors breathed a sigh of relief, despite the early-December yield curve inversion and the more recent broadening of the inversion from the 5/3 all the way out to the 10/fed funds rate slope. What partially explains the sector’s EPS resilience is net interest margins (NIMs) that just entered their fifth straight year of widening. While this may seem counterintuitive given the inverted/flattening yield curve, banks are repressing depositors by not passing on higher interest rates on deposits, thus guaranteeing extremely cheap funding. The bottom panel of Chart 11 shows that the 2-year Treasury yield/1-year CD rate slope is steep and it has historically moved in lockstep with bank NIMs. As a reminder, BCA’s bond strategists expect a selloff in the bond market and remain short duration, signaling that bank NIMs will not suffer a setback for the remainder of the year. Beyond the prospects for a further increase in the price of credit, another key source of bank EPS support is equity retirement. Citi explicitly mentioned it this earnings season, and the S&P financials sector buybacks, largely driven by banks, corroborate this anecdote (Chart 12). Chart 11Deciphering Bank Profit Resilience Chart 12New Buyback Kings In fact, there is a wide gap between this artificial EPS lift and relative share prices that will likely narrow in the coming months via a catch up phase in the latter, particularly if banks pass the Fed’s stringent stress test anew as we expect later this summer. On the credit quality front, bank NPLs remain anchored near cycle lows and tight labor markets suggest that a flare up in delinquencies is a low probability event in the coming year, especially given BCA’s view of no recession (bottom panel, Chart 13). Chargeoffs and souring loans are almost non-existent in all the categories that the Federal Reserve tracks, with the slight exception of credit card loans that are ticking higher, but from an extremely low base (we provide more details below in the risk section, second & third panels, Chart 13). Finally, loan growth has held up very well despite the stock market collapse in Q4/2018 and the massive tightening in financial conditions. While our overall loans & leases and C&I loan models are decelerating, they remain squarely in expansion mode and should continue to underpin bank profitability (second and bottom panel, Chart 14). Chart 13Pristine Credit Quality Chart 14Credit Growth Rests On A Solid Foundation  Consumer confidence remains sky-high and house prices are also rising at a healthy pace, signaling that mortgage (top panel, Chart 11) and consumer loan origination will remain upbeat (third panel, Chart 14). The price of credit, credit quality, credit growth along with buybacks all suggest that bank profits will continue to overwhelm. Stay overweight the S&P banks index. All of this positive news is already reflected in banks’ return on equity that vaulted higher recently signaling that a re-rating in still-extremely depressed valuations is looming in the coming quarters (Chart 15). Nevertheless, there are two risks to our sanguine S&P banks view that we are closely monitoring. First, our Economic Impulse Indicator remains near the zero line and, coupled with the still downbeat Citi Economic Surprise Index, warn that demand for loans may start softening at the margin (top panel, Chart 16). Chart 15Follow The ROE Chart 16Two Risks To Monitor Second, while the top 100 largest commercial banks are not showing a deterioration on the credit card delinquency front, the rest of the banks are waving a red flag as delinquencies are already at recessionary levels. This explains why the overall credit card delinquency rate is ticking higher (bottom panel, Chart 16). Netting it all out, the price of credit, credit quality, credit growth along with buybacks all suggest that bank profits will continue to overwhelm. Bottom Line: Stay overweight the S&P banks index. The ticker symbols for the stocks in this index are: BLBG: S5BANKX – JPM, BAC, WFC, C, USB, PNC, BBT, STI, MTB, FITB, FRC, KEY, CFG, RF, HBAN, SIVB, CMA, ZION, PBCT.   Anastasios Avgeriou, U.S. Equity Strategist anastasios@bcaresearch.com   Current Recommendations Current Trades Size And Style Views Favor value over growth Favor large over small caps