Here is a chapter from Portfolio Performance Measurement and Benchmarking, which will help you create a system you can use to accurately measure your performance. The authors highlight common mechanical problems involved in building benchmarks and clearly illustrate the resulting fallouts. The failure to choose the right investing performance benchmarks often leads to bad decisions or inaction and, inevitably, lost profits. In this book you will discover a foundation for benchmark construction and discuss methods for all different asset classes and investment styles.
In order to make sound investment choices, investors must know the projected return on investment in relation to the risk of not being paid. Benchmarks are excellent evaluators, but the failure to choose the right investing performance benchmark often leads to bad decisions or inaction, which inevitably results in lost profits. The first book of its kind, Portfolio Performance Measurement and Benchmarking is a complete guide to benchmarks and performace evaluation using benchmarks. In one inclusive volume, readers get foundational coverage on benchmark construction, as well as expert insight into specific benchmarks for asset classes and investment styles. Starting with the basics—such as return calculations and methods of dealing with cash flows—this thorough book covers a wide variety of performance measurement methodologies and evaluation techniques before moving into more technical material that deconstructs both the creation of indexes and the components of a desirable benchmark. Portfolio Performance Measurement and Benchmarking provides detailed coverage of benchmarks for: U.S. equities Global and international equities Fixed income Real estate The team of renowned authors offers illuminating opinions on the philosophy and development of equity indexes, while highlighting numerous mechanical problems inherent in building benchmarks and the implications of each one. Before you make your next investment, be certain your return will be worth the risk with Portfolio Performance Measurement and Benchmarking.
An intuitive and effective desk reference for performance measurement in asset and wealth management In The Complete Guide to Portfolio Performance: Appraise, Analyse, Act, a team of finance professors with extended practical experience deliver a hands-on desk reference for asset and wealth managers suitable for everyday use. Intuitively organized and full of concrete examples of the real-world implementation of the concepts discussed within, the book provides a comprehensive coverage of all important portfolio performance matters across 18 chapters of actionable and clearly described content. The authors have provided relevant cross-referencing where appropriate, “Key Takeaways and Equations” sections at the end of each chapter, and pointers to additional resources for anyone interested in pursuing further research. You'll also find: Discussions of more than a hundred classical and modern performance measures organized logically and with a focus on their applications Strategies for selecting appropriate performance measures based on your situation as a manager or investor Explanations of analytical techniques (statistical approaches, attribution, fund ratings...) enabling a comprehensive use of performance-related information Applications of portfolio performance criteria in concrete investment decision-making processes Highly actionable and logically organized material that's easy to find at a moment's notice A full set of pedagogical powerpoint slides and excel worksheets with all data and formulas Perfect for investors, portfolio managers, advisors, analysts, and regulators, The Complete Guide to Portfolio Performance is also a must-read reference for students and practitioners of asset and wealth management, as well as those pursuing certification such as CFA, CIPM, CIIA, and CAIA.
Portfolio Management in Practice, Volume 1: Investment Management delivers a comprehensive overview of investment management for students and industry professionals. As the first volume in the CFA Institute’s new Portfolio Management in Practice series, Investment Management offers professionals looking to enhance their skillsets and students building foundational knowledge an essential understanding of key investment management concepts. Designed to be an accessible resource for a wide range of learners, this volume explores the full portfolio management process. Inside, readers will find detailed coverage of: Forming capital market expectations Principles of the asset allocation process Determining investment strategies within each asset class Integrating considerations specific to high net worth individuals or institutions into chosen strategies And more To apply the concepts outlined in the Investment Management volume, explore the accompanying Portfolio Management in Practice, Volume 1: Investment Management Workbook. The perfect companion resource, this workbook aligns chapter-by-chapter with Investment Management for easy referencing so readers can draw connections between theoretical content and challenging practice problems. Featuring contributions from the CFA Institute’s subject matter experts, Portfolio Management in Practice, Volume 1: Investment Management distills the knowledge forward-thinking professionals will need to succeed in today’s fast-paced financial world.
A practitioner's guide to the role and implications of performance measurement and attribution analysis in asset management firms Practical Portfolio Performance Measurement and Attribution is a comprehensive reference and guide to the use and calculation of performance returns in the investment decision process. Focusing on real-world application rather than academic theory, this highly practical book helps asset managers and investors determine return on assets, analyse portfolio behaviour and improve performance. Author Carl R. Bacon clearly describes each of the methodologies used by performance analysts in today's financial environment whilst sharing valuable insights drawn from his experience as a Director of Performance Measurement & Risk Control. The third edition is revised to reflect recent developments in performance attribution and presentation standards. Fully up-to-date chapters cover the entire performance measurement process, including return calculations, attribution methodologies, risk measures, manager selection and presentation of performance information. Written by an acknowledged leader in global investment performance standards, performance attribution technique and risk measurement Aligns with the publication of the 2020 Global Investment Performance Standards (GIPS®) Explains the mathematical aspects of performance measurement and attribution in a clear, easy-to-understand manner Provides numerous practical and worked examples of attribution analysis and risk calculations supported by Excel spreadsheets Includes signposts for the future development of performance measurement Practical Portfolio Performance Measurement and Attribution, Third Edition, remains a must-have for performance analysts and risk controllers, portfolio managers, compliance professionals and all asset managers, owners, consultants and servicing firms.
Here is a chapter from Portfolio Performance Measurement and Benchmarking, which will help you create a system you can use to accurately measure your performance. The authors highlight common mechanical problems involved in building benchmarks and clearly illustrate the resulting fallouts. The failure to choose the right investing performance benchmarks often leads to bad decisions or inaction and, inevitably, lost profits. In this book you will discover a foundation for benchmark construction and discuss methods for all different asset classes and investment styles.
Performance measurement and attribution are key tools in informing investment decisions and strategies. Performance measurement is the quality control of the investment decision process, enabling money managers to calculate return, understand the behaviour of a portfolio of assets, communicate with clients and determine how performance can be improved. Focusing on the practical use and calculation of performance returns rather than the academic background, Practical Portfolio Performance Measurement and Attribution provides a clear guide to the role and implications of these methods in today's financial environment, enabling readers to apply their knowledge with immediate effect. Fully updated from the first edition, this book covers key new developments such as fixed income attribution, attribution of derivative instruments and alternative investment strategies, leverage and short positions, risk-adjusted performance measures for hedge funds plus updates on presentation standards. The book covers the mathematical aspects of the topic in an accessible and practical way, making this book an essential reference for anyone involved in asset management.
For many years asset management was considered to be a marginal activity, but today, it is central to the development of financial industry throughout the world. Asset management's transition from an "art and craft" to an industry has inevitably called integrated business models into question, favouring specialisation strategies based on cost optimisation and learning curve objectives. This book connects each of these major categories of techniques and practices to the unifying and seminal conceptual developments of modern portfolio theory. In these bear market times, performance evaluation of portfolio managers is of central focus. This book will be one of very few on the market and is by a respected member of the profession. Allows the professionals, whether managers or investors, to take a step back and clearly separate true innovations from mere improvements to well-known, existing techniques Puts into context the importance of innovations with regard to the fundamental portfolio management questions, which are the evolution of the investment management process, risk analysis and performance measurement Takes the explicit or implicit assumptions contained in the promoted tools into account and, by so doing, evaluate the inherent interpretative or practical limits
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.
Investment Performance Attribution involves identifying and quantifying those activities that increase investment return above a given benchmark--and is the hottest topic in institutional investing today. Investment Performance Attribution is the first book to provide clear and in-depth coverage of how and when to use the varying forms of attribution. It makes necessarily high-level attribution mathematics accessible, and will become an essential reference for professional money managers and institutional investors.
