About the Book
"China is the second largest economy in the world and is going to overtake the US by 2030. Chinese fixed income markets are worth more than 11trn USD, but only in 2019 will these bonds be added to global fixed income indices. This means that there will be huge demand to understand China and the time is now. India is very similar in that the economy and fixed income market is huge, and access to its fixed income markets for foreigners is starting to become easier. Other emerging markets are following this pattern. Furthermore, the additional yield available in emerging markets remains extremely attractive in a world of still depressed developing market yields (especially in Europe). With respect to existing EM fund managers there is a need to stop the market share gains by passive investment vehicles. Using the strategies in the proposed book helps to improve performance and will help existing managers to fight back. Sell-side professionals will need to update their knowledge base as their clients get smarter. At the same time, existing EM fund managers and their strategists and analysts need to up their game to avoid market share losses to passive investment vehicles. This book is going to lay out the principle drivers for EM fixed income investing and suggests practical rules on how to generate alpha. The impact of China will also be explained in some detail"--
Book Synopsis
A practitioner's guide to finding alpha in fixed income trading in emerging markets
Emerging fixed income markets are both large and fast growing. China, currently the second largest economy in the world, is predicted to overtake the United States by 2030. Chinese fixed income markets are worth more than $11 trillion USD and are being added to global fixed income indices starting in 2019. Access for foreigners to the Indian fixed income market, valued at almost 1trn USD, is also becoming easier - a trend repeated in emerging markets around the world. The move to include large Emerging Market (EM) fixed income markets into non-EM benchmarks requires non-EM specialists to understand EM fixed income. Trading Fixed Income in Emerging Markets examines the principle drivers for EM fixed income investing. This timely guide suggests a more systematic approach to EM fixed income trading with a focus on practical trading rules on how to generate alpha, assisting EM practitioners to limit market-share losses to passive investment vehicles.
The definitive text on trading EM fixed income, this book is heavily data-driven - every trading rule is thoroughly back-tested over the last 10+ years. Case studies help readers identify and benefit from market regularities, while discussions of the business cycle and typical EM events inform and optimise trading strategies. Topics include portfolio construction, how to apply ESG principles to EM and the future of EM investing in the realm of Big Data and machine learning. Written by practitioners for practitioners, this book:
- Provides effective, immediately-accessible tools
- Covers all three fixed income asset classes: EMFX, EM local rates and EM credit
- Thoroughly analyses the impact of the global macro cycle on EM investing
- Examines the influence of the financial rise of China and its fixed income markets
- Includes case studies of trades that illustrate how markets typically behave in certain situations
The first book of its kind, Trading Fixed Income in Emerging Markets: A Practitioner's Guide is an indispensable resource for EM fund managers, analysts and strategists, sell-side professionals in EM and non-EM specialists considering activity in emerging markets.
From the Back Cover
Emerging fixed income markets are both large and fast growing. China, currently the second largest economy in the world, is predicted to overtake the United States by 2030. Chinese fixed income markets are worth more than USD11 trillion and are gradually being added to global fixed income indexes since 2019. Access for foreigners to the Indian fixed income market, valued at almost one trillion USD, is also becoming easier - a trend repeated in emerging markets around the world. The move to include large Emerging Market (EM) fixed income markets into non-EM benchmarks requires non-EM specialists to understand EM fixed income. Trading Fixed Income in Emerging Markets examines the principle drivers for EM fixed income investing. This timely guide suggests a more systematic approach to EM fixed income trading with a focus on practical trading rules on how to generate alpha, assisting EM practitioners to limit market-share losses to passive investment vehicles.
The definitive text on trading EM fixed income, this book is heavily data-driven - every trading rule is thoroughly back-tested over the last 10+ years. Case studies help readers identify and benefit from market regularities, while discussions of the business cycle and typical EM events inform and optimise trading strategies. Topics also include portfolio construction, how to apply ESG principles to EM and the future of EM investing in the realm of Big Data and machine learning. Written by practitioners for practitioners, this book:
- Provides effective, immediately-accessible tools
- Covers all three fixed income asset classes: EMFX, EM local rates and EM credit
- Thoroughly analyses the impact of the global macro cycle on EM investing
- Examines the influence of the financial rise of China and its fixed income markets
- Includes case studies of trades that illustrate how markets typically behave around important events
The first book of its kind, Trading Fixed Income in Emerging Markets: A Practitioner's Guide is an indispensable resource for EM fund managers, analysts and strategists, sell-side professionals in EM and non-EM specialists considering activity in emerging markets. Academics and quants will also find the ideas outlined in the book very valuable.
About the Author
DR. DIRK WILLER is a Managing Director and Global Head of Emerging Market FX and Fixed Income Strategy at Citi Research in NY. His research covers global emerging markets for FX, local rates, and credit. His expertise further extends to the analysis of developments in G3 markets and their impact on global emerging markets. Dirk and his team have been ranked as the top team in the 2019 institutional investor survey for emerging markets strategy in FX and rates for Latam, CEEMEA and Asia. In Latam Dirk has been ranked first for four years in a row. Dirk's credit team has also been ranked among the top teams for Latam in the last years. Dirk is frequently quoted in the financial press, including Bloomberg, Reuters, Financial Times and the WSJ, as well as interviewed on TV. Previously, Dirk worked at Omega Advisors and RHG Capital as a global macro strategist and at Swiss Bank as Russia strategist. Before his work on the buy and sell side Dirk advised the Russian government under Deputy Prime Minister Anatoly Chubais during the successful stabilization period in the early 90ies. Dirk started his studies at the University of St. Gallen, Switzerland, and holds a PhD and a MSc with distinction in Economics from the London School of Economics. Dirk is a member of Atlantik-Bruecke and the Economics Club of New York. He resides in NYC with his wife and four daughters.
RAM BALA CHANDRAN is a Portfolio Manager on the Emerging Markets Debt team responsible for FX and rates management, covering Latin America. Prior to joining Neuberger Berman, Ram held a similar role at ING Investment Management. Before that he worked at Citigroup as an Latin American FX and local markets strategist. Ram holds a Bachelor's degree in Mechanical Engineering from the Indian Institute of Technology, Madras, India and earned a Master of Science in Computation for Design and Optimization from the Massachusetts Institute of Technology (MIT), Cambridge.
KENNETH LAM is a Director in Latam Strategy at Citi Research, with a focus on foreign exchange and local market fixed income. Previously Kenneth worked in US rates and mortgage trading as well as FX Structuring at Citi. Kenneth holds a Bachelor's degree in Systems Design Engineering from University of Waterloo and a Master's degree in Computational Finance from Carnegie Mellon University.
