Systematic Fixed Income

Understand the role and potential of fixed income as an asset class Systematic Fixed Income: An Investor’s Guide offers readers a powerful, practical, and robust framework for investors and asset managers to preserve the diversifying properties of a fixed income allocation, and add to that unique sources of excess returns via systematic security selection. In other words, this framework allows for efficient capture of fixed income beta and fixed income alpha. Celebrated finance professional Dr. Scott Richardson presents concrete strategies for identifying the relevant sources of risk and return in public fixed income markets and explains the tactical and strategic roles played by fixed income in typical portfolios. In the book, readers will explore: The implementation challenges associated with a systematic fixed income portfolio, including liquidity and risk The systematic return sources for rate and credit sensitive fixed income assets in both developed and emerging markets An essential read for asset managers and institutional investors with a professional interest in fixed income markets, Systematic Fixed Income: An Investor’s Guide deserves a place in the libraries of advanced degree students of finance, business, and investment, as well as other investment professionals seeking to refine their understanding of the full potential of this foundational asset class.

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.

Praise for SYSTEMATIC INVESTING in CREDIT "Lev and QPS continue to shed light on the most important questions facing credit investors. This book focuses on their latest cutting-edge research into the appropriate role of credit as an asset class, the dynamics of credit benchmarks, and potential ways to benefit from equity information to construct effective credit portfolios. It is must-read material for all serious credit investors." —Richard Donick, President and Chief Risk Officer, DCI, LLC, USA "Lev Dynkin and his team continue to spoil us; this book is yet another example of intuitive, insightful, and pertinent research, which builds on the team's previous research. As such, the relationship with this team is one of the best lifetime learning experiences I have had." —Eduard van Gelderen, Chief Investment Officer, Public Sector Pension Investment Board, Canada "The rise of a systematic approach in credit is a logical extension of the market's evolution and long overdue. Barclays QPS team does a great job of presenting its latest research in a practical manner." —David Horowitz, Chief Executive Officer and Chief Investment Officer, Agilon Capital, USA "Systematization reduces human biases and wasteful reinventing of past solutions. It improves the chances of investing success. This book, by a team of experts, shows you the way. You will gain insights into the advanced methodologies of combining fundamental and market data. I recommend this book for all credit investors." —Lim Chow Kiat, Chief Executive Officer, GIC Asset Management, Singapore "For nearly two decades, QPS conducted extensive and sound research to help investors meet industry challenges. The proprietary research in this volume gives a global overview of cutting-edge developments in alpha generation for credit investors, from signal extraction and ESG considerations to portfolio implementation. The book blazes a trail for enhanced risk adjusted returns by exploring the cross-asset relation between stocks and bonds and adding relevant information for credit portfolio construction. Our core belief at Ostrum AM, is that a robust quantamental approach, yields superior investment outcomes. Indeed, this book is a valuable read for the savvy investor." —Ibrahima Kobar, CFA, Global Chief Investment Officer, Ostrum AM, France "This book offers a highly engaging account of the current work by the Barclays QPS Group. It is a fascinating mix of original ideas, rigorous analytical techniques, and fundamental insights informed by a long history of frontline work in this area. This is a must-read from the long-time leaders in the field." —Professor Leonid Kogan, Nippon Telephone and Telegraph Professor of Management and Finance, MIT "This book provides corporate bond portfolio managers with an abundance of relevant, comprehensive, data-driven research for the implementation of superior investment performance strategies." —Professor Stanley J. Kon, Editor, Journal of Fixed income "This book is a treasure trove for both pension investors and trustees seeking to improve performance through credit. It provides a wealth of empirical evidence to guide long-term allocation to credit, optimize portfolio construction and harvest returns from systematic credit factors. By extending their research to ESG ratings, the authors also provide timely insights in the expanding field of sustainable finance." —Eloy Lindeijer, former Chief of Investment Management, PGGM, Netherlands "Over more than a decade, Lev Dynkin and his QPS team has provided me and APG with numerous innovative insights in credit markets. Their work gave us valuable quantitative substantiation of some of our investment beliefs. This book covers new and under-researched areas of our markets, like ESG and factor investing, next to the rigorous and practical work akin to the earlier work of the group. I'd say read this book—and learn from one of the best." —Herman Slooijer, Managing Director, Head of Fixed Income, APG Asset Management, Netherlands

A highly-detailed, practical analysis of fixed income management The Advanced Fixed Income and Derivatives Management Guide provides a completely novel framework for analysis of fixed income securities and portfolio management, with over 700 useful equations. The most detailed analysis of inflation linked and corporate securities and bond options analysis available;, this book features numerous practical examples that can be used for creating alpha transfer to any fixed income portfolio. With a framework that unifies back office operations, such as risk management and portfolio management in a consistent way, readers will be able to better manage all sectors of fixed income, including bonds, mortgages, credits, and currencies, and their respective derivatives, including bond and interest rate futures and options, callable bonds, credit default swaps, interest rate swaps, swaptions and inflation swaps. Coverage includes never-before-seen detail on topics including recovery value, partial yields, arbitrage, and more, and the companion website features downloadable worksheets that can be used for measuring the risks of securities based on the term structure models. Many theoretical models of the Term Structure of Interest Rates (TSIR) lack the accuracy to be used by market practitioners, and the most popular models are not mathematically stable. This book helps readers develop stable and accurate TSIR for all fundamental rates, enabling analysis of even the most complex securities or cash flow structure. The components of the TSIR are almost identical to the modes of fluctuations of interest rates and represent the language with which the markets speak. Examine unique arbitrage, risk measurement, performance attribution, and replication of bond futures Learn to estimate recovery value from market data, and the impact of recovery value on risks Gain deeper insight into partial yields, product design, and portfolio construction Discover the proof that corporate bonds cannot follow efficient market hypothesis This useful guide provides a framework for systematic and consistent management of all global fixed income assets based on the term structure of rates. Practitioners seeking a more thorough management system will find solutions in The Advanced Fixed Income and Derivatives Management Guide.

The essential guide to fixed income portfolio management, from the experts at CFA Fixed Income Analysis is a new edition of Frank Fabozzi's Fixed Income Analysis, Second Edition that provides authoritative and up-to-date coverage of how investment professionals analyze and manage fixed income portfolios. With detailed information from CFA Institute, this guide contains comprehensive, example-driven presentations of all essential topics in the field to provide value for self-study, general reference, and classroom use. Readers are first introduced to the fundamental concepts of fixed income before continuing on to analysis of risk, asset-backed securities, term structure analysis, and a general framework for valuation that assumes no prior relevant background. The final section of the book consists of three readings that build the knowledge and skills needed to effectively manage fixed income portfolios, giving readers a real-world understanding of how the concepts discussed are practically applied in client-based scenarios. Part of the CFA Institute Investment series, this book provides a thorough exploration of fixed income analysis, clearly presented by experts in the field. Readers gain critical knowledge of underlying concepts, and gain the skills they need to translate theory into practice. Understand fixed income securities, markets, and valuation Master risk analysis and general valuation of fixed income securities Learn how fixed income securities are backed by pools of assets Explore the relationships between bond yields of different maturities Investment analysts, portfolio managers, individual and institutional investors and their advisors, and anyone with an interest in fixed income markets will appreciate this access to the best in professional quality information. For a deeper understanding of fixed income portfolio management practices, Fixed Income Analysis is a complete, essential resource.

The global fixed income market is an enormous financial market whose value by far exceeds that of the public stock markets. The interbank market consists of interest rate derivatives, whose primary purpose is to manage interest rate risk. The credit market primarily consists of the bond market, which links investors to companies, institutions, and governments with borrowing needs. This dissertation takes an optimization perspective upon modeling both these areas of the fixed-income market. Legislators on the national markets require financial actors to value their financial assets in accordance with market prices. Thus, prices of many assets, which are not publicly traded, must be determined mathematically. The financial quantities needed for pricing are not directly observable but must be measured through solving inverse optimization problems. These measurements are based on the available market prices, which are observed with various degrees of measurement noise. For the interbank market, the relevant financial quantities consist of term structures of interest rates, which are curves displaying the market rates for different maturities. For the bond market, credit risk is an additional factor that can be modeled through default intensity curves and term structures of recovery rates in case of default. By formulating suitable optimization models, the different underlying financial quantities can be measured in accordance with observable market prices, while conditions for economic realism are imposed. Measuring and managing risk is closely connected to the measurement of the underlying financial quantities. Through a data-driven method, we can show that six systematic risk factors can be used to explain almost all variance in the interest rate curves. By modeling the dynamics of these six risk factors, possible outcomes can be simulated in the form of term structure scenarios. For short-term simulation horizons, this results in a representation of the portfolio value distribution that is consistent with the realized outcomes from historically observed term structures. This enables more accurate measurements of interest rate risk, where our proposed method exhibits both lower risk and lower pricing errors compared to traditional models. We propose a method for decomposing changes in portfolio values for an arbitrary portfolio into the risk factors that affect the value of each instrument. By demonstrating the method for the six systematic risk factors identified for the interbank market, we show that almost all changes in portfolio value and portfolio variance can be attributed to these risk factors. Additional risk factors and approximation errors are gathered into two terms, which can be studied to ensure the quality of the performance attribution, and possibly improve it. To eliminate undesired risk within trading books, banks use hedging. Traditional methods do not take transaction costs into account. We, therefore, propose a method for managing the risks in the interbank market through a stochastic optimization model that considers transaction costs. This method is based on a scenario approximation of the optimization problem where the six systematic risk factors are simulated, and the portfolio variance is weighted against the transaction costs. This results in a method that is preferred over the traditional methods for all risk-averse investors. For the credit market, we use data from the bond market in combination with the interbank market to make accurate measurements of the financial quantities. We address the notoriously difficult problem of separating default risk from recovery risk. In addition to the previous identified six systematic risk factors for risk-free interests, we identify four risk factors that explain almost all variance in default intensities, while a single risk factor seems sufficient to model the recovery risk. Overall, this is a higher number of risk factors than is usually found in the literature. Through a simple model, we can measure the variance in bond prices in terms of these systematic risk factors, and through performance attribution, we relate these values to the empirically realized variances from the quoted bond prices. De globala ränte- och kreditmarknaderna är enorma finansiella marknader vars sammanlagda värden vida överstiger de publika aktiemarknadernas. Räntemarknaden består av räntederivat vars främsta användningsområde är hantering av ränterisker. Kreditmarknaden utgörs i första hand av obligationsmarknaden som syftar till att förmedla pengar från investerare till företag, institutioner och stater med upplåningsbehov. Denna avhandling fokuserar på att utifrån ett optimeringsperspektiv modellera både ränte- och obligationsmarknaden. Lagstiftarna på de nationella marknaderna kräver att de finansiella aktörerna värderar sina finansiella tillgångar i enlighet med marknadspriser. Därmed måste priserna på många instrument, som inte handlas publikt, beräknas matematiskt. De finansiella storheter som krävs för denna prissättning är inte direkt observerbara, utan måste mätas genom att lösa inversa optimeringsproblem. Dessa mätningar görs utifrån tillgängliga marknadspriser, som observeras med varierande grad av mätbrus. För räntemarknaden utgörs de relevanta finansiella storheterna av räntekurvor som åskådliggör marknadsräntorna för olika löptider. För obligationsmarknaden utgör kreditrisken en ytterligare faktor som modelleras via fallissemangsintensitetskurvor och kurvor kopplade till förväntat återvunnet kapital vid eventuellt fallissemang. Genom att formulera lämpliga optimeringsmodeller kan de olika underliggande finansiella storheterna mätas i enlighet med observerbara marknadspriser samtidigt som ekonomisk realism eftersträvas. Mätning och hantering av risker är nära kopplat till mätningen av de underliggande finansiella storheterna. Genom en datadriven metod kan vi visa att sex systematiska riskfaktorer kan användas för att förklara nästan all varians i räntekurvorna. Genom att modellera dynamiken i dessa sex riskfaktorer kan tänkbara utfall för räntekurvor simuleras. För kortsiktiga simuleringshorisonter resulterar detta i en representation av fördelningen av portföljvärden som väl överensstämmer med de realiserade utfallen från historiskt observerade räntekurvor. Detta möjliggör noggrannare mätningar av ränterisk där vår föreslagna metod uppvisar såväl lägre risk som mindre prissättningsfel jämfört med traditionella modeller. Vi föreslår en metod för att dekomponera portföljutvecklingen för en godtycklig portfölj till de riskfaktorer som påverkar värdet för respektive instrument. Genom att demonstrera metoden för de sex systematiska riskfaktorerna som identifierats för räntemarknaden visar vi att nästan all portföljutveckling och portföljvarians kan härledas till dessa riskfaktorer. Övriga riskfaktorer och approximationsfel samlas i två termer, vilka kan användas för att säkerställa och eventuellt förbättra kvaliteten i prestationshärledningen. För att eliminera oönskad risk i sina tradingböcker använder banker sig av hedging. Traditionella metoder tar ingen hänsyn till transaktionskostnader. Vi föreslår därför en metod för att hantera riskerna på räntemarknaden genom en stokastisk optimeringsmodell som också tar hänsyn till transaktionskostnader. Denna metod bygger på en scenarioapproximation av optimeringsproblemet där de sex systematiska riskfaktorerna simuleras och portföljvariansen vägs mot transaktionskostnaderna. Detta resulterar i en metod som, för alla riskaverta investerare, är att föredra framför de traditionella metoderna. På kreditmarknaden använder vi data från obligationsmarknaden i kombination räntemarknaden för att göra noggranna mätningar av de finansiella storheterna. Vi angriper det erkänt svåra problemet att separera fallissemangsrisk från återvinningsrisk. Förutom de tidigare sex systematiska riskfaktorerna för riskfri ränta, identifierar vi fyra riskfaktorer som förklarar nästan all varians i fallissemangsintensiteter, medan en enda riskfaktor tycks räcka för att modellera återvinningsrisken. Sammanlagt är detta ett större antal riskfaktorer än vad som brukar användas i litteraturen. Via en enkel modell kan vi mäta variansen i obligationspriser i termer av dessa systematiska riskfaktorer och genom prestationshärledningen relatera dessa värden till de empiriskt realiserade varianserna från kvoterade obligationspriser.

A unique, authoritative, and comprehensive treatment of fixed income markets Fixed Income Trading and Risk Management: The Complete Guide delivers a comprehensive and innovative exposition of fixed income markets. Written by European Central Bank portfolio manager Alexander During, this book takes a practical view of how several different national fixed income markets operate in detail. The book presents common theoretical models but adds a lot of information on the actually observed behavior of real markets. You’ll benefit from the book’s: Fulsome overview of money, credit, and monetary policy Description of cash instruments, inflation-linked debt, and credit claims Analysis of derivative instruments, standard trading strategies, and data analysis In-depth focus on risk management in fixed income markets Perfect for new and junior staff in financial institutions working in sales and trading, risk management, back office operations, and portfolio management positions, Fixed Income Trading and Risk Management also belongs on the bookshelves of research analysts and postgraduate students in finance, economics, or MBA programs.

A unique perspective on the implications of incorporating ESG considerations in systematic investing In Integrating ESG in Systematic Investing, a team of authors from Barclays’ top-ranked Quantitative Portfolio Strategy group (ranked #1 by Institutional Investor in its 2022 Global Fixed Income Research Survey in both the US and Europe) delivers an insightful and practical discussion of how to reflect ESG considerations in systematic investing. The authors offer a cross-asset class perspective—incorporating both credit and equity markets in the United States, Europe, and China—a unique coverage scope amongst books on this subject. They discuss the interaction between ESG ratings and various other security characteristics, suggest a methodology for isolating the ESG-specific risk premia, analyse the impact of an ESG tilt on systematic strategies and risk factors, and identify several ESG-based signals that are predictive of future performance. You’ll also discover: Analysis of companies in the process of improving their ESG ranking (“ESG improvers”) vs. firms with best-in-class ESG ratings A study using natural language processing (NLP) to predict changes in corporate ESG rankings from company job postings for sustainability-related positions In-depth explorations of ESG equity fund performance and flows and the information content of ESG ratings dispersion across several providers Perfect for portfolio managers including non-quantitative, fundamental investors, risk managers, and research analysts at financial institutions such as asset managers, pension funds, banks, sovereign wealth funds, hedge funds, and insurance companies, Integrating ESG in Systematic Investing is also a must-read resource for academics with a research interest in the performance and risk implications of ESG investing.