Trading Fixed Income and FX in Emerging Markets: A Practitioner's Guide

List of Figures

List of Tables

Introduction

This book will make you a better portfolio manager and risk‐taker. The key to succeeding in markets is twofold. First, a solid methodology is crucial. And second, conviction to press the bets when the stars align may be even more important. The two issues are obviously linked. A solid methodology is, after all, what creates conviction. Such a methodology can come from participating in markets for a long time and internalizing what works along the way. The gut feeling of an experienced portfolio manager may be what gives conviction. But there is a shortcut: data can substitute for hands‐on experience and is likely superior. After all, backtesting trading rules and analysing what works across many countries, instruments, and time periods is more reliable than just using data subconsciously collected during an individual trading career, which is necessarily more limited in terms of instruments traded and timespans covered. This book does the data analysis for our readers to generate a robust trading methodology for emerging markets. The result is a set of empirically validated rules of thumb that we find helpful to generate alpha. The rules are valuable for benchmarked long‐only investment funds as well as for hedge funds. We establish both what works and what does not work (even though many think it does). Often, it is of equal value to understand what does not work, as noise reduction is important to generate conviction.

This book will make you a better policy maker. While the book is written from the perspective of making money in markets, some chapters are also relevant for policy makers. In particular, it is very important for policy makers to understand how markets will react to their various measures, whether they are FX interventions, IMF programmes, or interest rate policies. The actions of policy makers generate many of the opportunities for markets. But at the same time, understanding markets creates opportunities for policy makers.

This book will make you a better academic and quantitative researcher. This book is not written with an academic mindset. And although writing the book involved a significant amount of coding, we also do not do the work of hardcore quants. We are willing to live with small sample sizes and simplifying assumptions in our backtests. In order to bring the ideas across, we typically assume zero transaction costs, and we don't worry about risk‐management overlays. But the book is about systematic ideas and figuring out how markets work. We trust that academics and quantitative researchers will find many of the ideas interesting and worthy of further study. This book will make academics' output more relevant to the real world.

Combined, the authors have more than 40 years of experience in emerging fixed‐income and FX markets. Having interacted with thousands of investors across real money funds, hedge funds, pension funds, sovereign wealth funds, corporates, and policy makers, we have learned a lot from our clients over the years. Dirk and Ken have been ranked the first team in the institutional investor (II) survey for Latin America fixed income for the last four years. The global EM strategy team, headed by Dirk, is ranked the first team for Asia, CEEMEA, and Latam for both FX and interest rates, and the second team for Latam sovereign credit in the first global II survey in 2018. The long‐term performance of Dirk's and Ken's published investment recommendations has been very strong throughout bull and bear markets.¹ As such, the methodology that we are proposing in this book has stood the test of time. One reason for the resilience of our framework is that we care mostly about deep fundamentals of human psychology and behavioural patterns that are unlikely to change, rather than just economic fundamentals. We therefore expect and certainly hope that our framework will add value in the future. But the future is the future. There are no guarantees, and keeping an open mind is the key to succeeding in trading.

So why did we write this book? Either our framework is helpful to make money, and then why tell anyone, given that it may deteriorate if more traders apply it; or our framework is not helpful, and then why waste the time writing a book about it?

The answer is that we do not think that publishing the book will impact our strategies much. After all, we have produced research on the sell side for many years, and this has not led to a noticeable deterioration of our trading strategies. While markets always change, we think they change fairly slowly. Constant research is necessary to keep on top of markets, and we are excited to keep working to constantly update our framework.

On a related topic, we also note that the bulk of this book was written during 2018 and 2019 in a process that was admittedly slow, mostly due to the demands of our day jobs. While it is always tempting to keep updating the chapters, especially in light of the momentous developments in early 2020, we have resisted this temptation. The vast majority of our trading rules would have worked well since the completion of the relevant chapters, and we think not updating gives readers a good sense of a true out‐of‐sample performance of our framework.

The book is organized as follows:

Chapter 1: EMFX and Fixed Income: Where the Opportunities Lie. The chapter illustrates the importance of EMFX and fixed‐income markets, why continued future growth is likely, and why EM are a key source of alpha. For readers who are familiar with the EM universe, the main topic of interest will be our analysis of the strategies the EM investment funds currently employ to outperform and how much herding behaviour this generates.

Chapter 2: Global Macro Rules. EM is 65% global macro and 35% local, at least in EMFX and credit. EM rates have a higher local component. The chapter explains how views on global macro assets can be implemented in EM to outperform the EM benchmarks and trade EM assets. At times, there are important lags between those macro assets and the EM assets, and lags generate opportunities.

Chapter 3: China: The Only Emerging Market That Counts. China is the only EM that deserves its own chapter. We explain how to trade the Chinese fixed‐income and FX markets. We also highlight how China impacts the rest of the emerging world and how to position for that.

Chapter 4: How to Trade EMFX. The meat of the book starts with Chapter 4. Here we investigate which systematic strategies work for EMFX trading and which do not. Many factors have much weaker performance these days: in particular, carry, in its simplest form, has broken down. We propose alternative strategies to earn carry. We also highlight growth as a profitable factor. We introduce some technicals that work well.

Chapter 5: How to Trade EMFX: Event Guide. We explain how to generate alpha from recurring events in the FX market, such as intervention, emergency rate hikes, IMF packages, elections, and certain economic data releases. All event‐related trading strategies are thoroughly backtested.

Chapter 6: How to Trade Emerging Market Rates: The Cycle. We analyse in depth the reaction function of EM central banks and explain how to trade the typical interest rate cycle in both the US and EM. We show how to use valuation measures like term premia to generate alpha.

Chapter 7: Real Rates: Simply Superior. We explain the important market for linkers in EM and propose some backtested rules of thumb on how to add alpha by switching between linkers and nominal bonds.

Chapter 8: How to Trade EM Rates: Event Guide. We investigate and backtest how to trade recurring events in rates space: economic data, curve inversion, index inclusion, and natural disasters.

Chapter 9: How to Trade EM Credit. We explore how to trade the EM credit cycle, and we explain what Warren Buffett and Ray Dalio would do. We also explain how to trade recurring events like IMF packages, defaults, and credit up‐ and downgrades, and we analyse when to overweight external debt versus local debt and vice versa.

Chapter 10: Portfolio Construction. This chapter investigates smart fixed‐income indexes, frontier markets, and portfolio allocation across EM asset classes and explains the importance of derivatives for alpha generation. We also offer a proposal to make ESG more EM‐friendly.

Chapter 11: The (Near) Future: Big Data, Machine Learning, and What If There Are No Emerging Markets Left. We discuss the application of big data to EM, and we propose what to focus on first in terms of implementation. We also suggest some machine learning techniques to use for EMFX trading. Finally, we investigate whether it is plausible that we will run out of EM. We very much doubt it.

Thanks for reading this book. And good luck trading.

New York

March 2020

NOTE

1   Footnote: For performance attribution of the EM local market (paper) model portfolio, see Willer et al. (2020).

Acknowledgements

I owe deep gratitude to my parents, who supported me through thick and thin. My father worked extensively in Russia and China in the 1980s and 1990s and conveyed to me his vision of a successful economic future for both countries. Crucially, my mother imparted to me a deep interest in politics. Thanks, Mom and Dad.

I am indebted to Sir Richard Layard for inviting me to join his team in Moscow in the early 1990s to work with the Russian government during one of the seminal moments in post‐war history. I am also grateful to Professor David Webb for being an inspiring teacher, and for giving an awesome wedding speech. Throughout my life, I have been consistently blessed with great mentors. In particular, I would like to thank Jose Luis Yepez, Thomas Glaessner, Guillermo Mondino, and Rob Rowe for all their support. I owe Rob Rowe and Andrew Pitt a special thank you for wholeheartedly supporting this book project. It is not obvious for a preeminent research organization to share intellectual property with the world, and Andrew's and Rob's leadership is exemplary. I would also like to thank all my clients/friends as well as my research, trading, and sales colleagues/friends at Citi, who with their feedback constantly improve our research effort.

I also want to thank Gemma Valler at Wiley for believing in the project and Elisha Benjamin, Purvi Patel, Gladys Ganaden, and Tiffany Taylor for countless improvements. Jessica James deserves a shout out for the introduction to Wiley. While all mistakes are the sole responsibility of the authors, I want to thank the friends and colleagues who tried hard to minimize them. Special thanks to Tobias Adrian, Amer Bisat, Gaurav Garg, James Keefe, Luis Loera, Ayoti Mittra, Eric Ollom, Ernesto Revilla, Lu Sun and Bruno Vander Cruyssen. I would also like to thank Willem Buiter, Mike Corbat, Pramol Dhawan, Sam Finkelstein, Rob Gibbins, Hari Hariharan, Antti Ilmanen, Paul Tudor Jones, Andrew Lo, Guillermo Ortiz and Nouriel Roubini for looking at early versions of the draft.

Finally, I want to wholeheartedly thank my incredible wife and soul mate for more than 25 years, who has been very supportive of this project, even with four young(ish) children to entertain, while pursuing a very demanding career of her own. Speaking of kids: thank you very much to Charlotte, Caroline, Sophie, and Anna for always reminding me how fascinating life is.

D.W.

I would not have gotten into finance without the Quant Trading and Analysis programme at Citi. Special thanks to Shelli Faber and Andy Feigenberg for running one of the most unique analyst programmes on the street. Special thanks to all my former and current colleagues for their time and counsel. In particular, I would like thank Dirk Willer, Luis Loera, Pere Sole, Gabriel Infante, Vivek Kapoor, Rupak Chatterjee, Raoul Luttik, Vera Kartseva, Sukhjeet Reehal, and Rob Drijkoningen.

Special thanks to my Mom and Dad for being supportive and always going the extra distance for me. My Mom would probably have been happier if I had thanked her in a PhD thesis, but a book is at least a consolation prize. I am grateful for all the support my sister Rohini has given over the years. I hope she will thank me in all the books that she is set to write in the future.

Finally, I am grateful to my wife Swetha for putting up with me in general, and for being supportive and picking up the slack for me regarding everything in life during this book project.

R.B.C.

I would like to thank my colleagues and friends at Citi for their support: in particular, Dirk, who has taught me so much over the years. A grateful thank you to my parents, without whom nothing is possible.

K.L.

Acronyms

ADR American Depository Receipt AMLO López Obrador, President of Mexico AUM Assets under management BOJ Bank of Japan bp Basis point CA(D) current account (deficit) CDS credit default swap CEEMEA Central and Eastern Europe, Middle East, and Africa CEMBI Corporate Emerging Market Bond Index (credit) CGB Chinese Government Bond CIBM Direct China Interbank Bond Market Direct CTA commodity trading advisor CTOT commodities terms of trade DM Developed markets DV01 Dollar variation in a bond's value for a 1 bp change in yield DXY USD index ECB European Central Bank EM Emerging markets EMBI Emerging Market Bond Index (credit) EMFX Emerging markets foreign exchange ETF Exchange‐traded fund FOMC Federal Open Market Committee FX Foreign exchange G10 Group of Ten (developed countries) GBI‐EM Government Bond Index‐Emerging Markets (local currency) HRP Hierarchical risk parity HY High yield IG Investment grade IMF International Monetary Fund ISM Institute for Supply Management PMI IR Information ratio IRS Interest rate swap JGB Japanese Government Bond Latam Latin America LTCM Long Term Capital Management (a hedge fund) MA Moving average MCap Market capitalization Momo Momentum NDF Non‐deliverable forward in FX ND‐IRS Non‐deliverable interest rate swap NFP US nonfarm payrolls PBOC People's Bank of China PCA Principle components analysis PMI Purchasing Manager Index PPP Purchasing power parity QE Quantitative easing QFII Qualified Foreign Institutional Investor R² A statistical measure of fit REER Real effective exchange rate RQFII Renminbi Qualified Foreign Institutional Investor RRR Required reserves ratio SDR Special drawing right SHCOMP Shanghai Composite Equity Index ToT Terms of trade TSF Total social financing US AGG US Aggregate Bond Index US HY US High Yield Corporate Bond Index UST US Treasuries VIX Implied volatility index for the S&P Vol Volatility WGBI World Government Bond Index (local currency) yoy Year over year

CHAPTER 1

EMFX and Fixed Income: Where the Opportunities Lie

1.1 EM DEBT – GROWING TOO FAST TO IGNORE

Two main growth stories in the emerging market fixed‐income space offer major opportunities and lead to increased investor interest and participation: local markets and external debt.

Ever since the emerging markets (EM) crisis of the late 1990s and 2000s, EM countries have tried to unwind the original sin of previously having issued large stocks of USD‐denominated debt.¹ The reason is that it was the USD debt that caused, or at the very least intensified, the EM crisis in the 1990s. Back then, the USD was in a strong bull market, making USD‐denominated debt more expensive to carry and eventually causing mayhem in EM. The main way to reduce this vulnerability stemming from USD debt has been to develop markets for local currency sovereign debt and to substitute external debt for local debt. Many countries have been successful in this undertaking, and as a result, local sovereign debt markets have grown with a 15% compound annual growth rate (CAGR) between 2003 and Q3 2019, compared to about 7% annual growth for USD‐denominated sovereign debt. Amazingly, the 2008–2009 global financial crisis made only a shallow and short‐lived dent in the high growth of local debt, even when translated into USD terms, as can be seen in Figure 1.1. This is surprising, as EM currencies depreciated sharply during the crisis, impacting the USD value of these markets very negatively. This strong growth in adverse circumstances demonstrates that local emerging market debt has become a major investible asset class and is here to stay.

At the end of the third quarter of 2019, EM sovereign local currency debt markets were capitalized at USD 10.5 trillion. Around USD 5.1 trillion in local government bonds sit in China (roughly evenly split between Chinese Government Bonds (CGBs) and policy bank notes).² The share of Chinese local government debt as a percentage of EM local debt continues to grow (Figure 1.2).

FIGURE 1.1 EM Sovereign Debt Grew Even Through the Great Recession.

Source: Bank for International Settlements.

Another USD 1 trillion of local sovereign debt sits in India. Chinese and Indian local fixed‐income markets are not widely owned by foreigners, but this is changing rapidly, partly as China's weight in the global fixed‐income indexes grows. China is clearly too large to be ignored by global debt managers, and so is India. China and India are the single biggest sources of growth potential for emerging market debt trading. Furthermore, China entering various developed market fixed‐income indexes at a time when it is arguably still an emerging market will force global investors to engage more actively with investing in emerging market local currency denominated bond markets. This is why we dedicate a full chapter of this book to China.

FIGURE 1.2 China is 50% of Local Currency Government Debt – and Rising.

Source: Bank for International Settlements.

FIGURE 1.3 EMFX Gaining Market Share From G10 FX.

Source: BIS triennial survey.

To invest in local currency debt, there is also a need to trade emerging market currencies. Rising EMFX trading volumes are therefore logically going hand in hand with the rise in outstanding local currency debt. As of the last data point (2019) from the Bank for International Settlements, the turnover in EMFX reached USD 1.7 trillion per day, or 13% of the total FX volume, rising from close to zero in 1995 (see Figure 1.3).

External debt is also growing quickly. As of Q3 2019, USD 2.3 trillion of bonds are outstanding. But the shift by sovereign issuers to local markets has muted the growth from existing sovereign issuers. Instead, EM corporate debt issuers are growing rapidly, happily filling this gap. The market has welcomed such corporate issues, in particular from exporters that are considered naturally currency hedged given their USD export revenues. While external corporate issuance has moderated from its earlier breakneck pace, we think it will accelerate again whenever global growth, and therefore corporate capital expenditures (capex), pick up. At the end of 2019, corporate external debt stood at around USD 1.1 trillion. But there also is a growth driver for sovereign external debt, a market that has increased from USD 394 billion in 2003 to USD 1.2 trillion at the end of 2019. Here, the growth story is mostly the increasing number of issuers. Figure 1.4 shows the number of effective country members³ included in the EM local currency bond index (JPMorgan Government Bond Index‐Emerging Markets, or GBI‐EM), as well as the EM sovereign bond index (JPMorgan Emerging Market Bond Index, or EMBI). As can be seen in the chart, post crisis, the number of external sovereign issuers in the index has soared, while