Portfolio Performance Measurement and Benchmarking, Chapter 16 - Factor Model (Barra) Performance Attribution PDF Download

Author: Jon A. Christopherson
Publisher: McGraw Hill Professional
ISBN: 0071733221
Category : Business & Economics
Languages : en
Pages : 18

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Book Description
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.

Author: Jon A. Christopherson
Publisher: McGraw Hill Professional
ISBN: 0071713662
Category : Business & Economics
Languages : en
Pages : 482

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Book Description
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.

Author: Philip Lawton, CIPM
Publisher: John Wiley & Sons
ISBN: 0470473711
Category : Business & Economics
Languages : en
Pages : 984

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Investment Performance Measurement Over the past two decades, the importance of measuring, presenting, and evaluating investment performance results has dramatically increased. With the growth of capital market data services, the development of quantitative analytical techniques, and the widespread acceptance of Global Investment Performance Standards (GIPS®), this discipline has emerged as a central component of effective asset management and, thanks in part to the Certificate in Investment Performance Measurement (CIPM) program, has become a recognized area of specialization for investment professionals. That's why Investment Performance Measurement: Evaluating and Presenting Results the second essential title in the CFA Institute Investment Perspectives series has been created. CFA Institute has a long tradition of publishing content from industry thought leaders, and now this new collection offers unparalleled guidance to those working in the rapidly evolving field of investment management. Drawing from the Research Foundation of CFA Institute, the Financial Analysts Journal, CFA Institute Conference Proceedings Quarterly, CFA Magazine, and the CIPM curriculum, this reliable resource taps into the vast store of knowledge of some of today's most prominent thought leaders from industry professionals to respected academics who have focused on investment performance evaluation for a majority of their careers. Divided into five comprehensive parts, this timely volume opens with an extensive overview of performance measurement, attribution, and appraisal. Here, you'll become familiar with everything from the algebra of time-weighted and money-weighted rates of return to the objectives and techniques of performance appraisal. After this informative introduction, Investment Performance Measurement moves on to: Provide a solid understanding of the theoretical grounds for benchmarking and the trade-offs encountered during practice in Part II: Performance Measurement Describe the different aspects of attribution analysis as well as the determinants of portfolio performance in Part III: Performance Attribution Address everything from hedge fund risks and returns to fund management changes and equity style shifts in Part IV: Performance Appraisal Recount the history and explain the provisions of the GIPS standards with attention paid to the many practical issues that arise in the course of its implementation in Part V: Global Investment Performance Standards Filled with invaluable insights from more than fifty experienced contributors, this practical guide will enhance your understanding of investment performance measurement and put you in a better position to present and evaluate results in the most effective way possible.

Author: Wai Lee
Publisher: John Wiley & Sons
ISBN: 9781883249724
Category : Business & Economics
Languages : en
Pages : 168

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Asset allocation has long been viewed as a safe bet for reducing risk in a portfolio. Asset allocators strive to buy when prices are low and sell when prices rise. Tactical asset allocation (TAA) practitioners tend to emphasize shorter-term adjustments, reducing exposure when recent market performance has been good, and increasing exposure in a slipping market (in contrast to dynamic asset allocation, or portfolio insurance). As interest in this technique continues to grow, J.P. Morgan's Wai Lee provides comprehensive coverage of the analytical tools needed to successfully implement and monitor tactical asset allocation.

Author: Richard C. Grinold
Publisher: McGraw Hill Professional
ISBN: 007137695X
Category : Business & Economics
Languages : en
Pages : 596

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"This new edition of Active Portfolio Management continues the standard of excellence established in the first edition, with new and clear insights to help investment professionals." -William E. Jacques, Partner and Chief Investment Officer, Martingale Asset Management. "Active Portfolio Management offers investors an opportunity to better understand the balance between manager skill and portfolio risk. Both fundamental and quantitative investment managers will benefit from studying this updated edition by Grinold and Kahn." -Scott Stewart, Portfolio Manager, Fidelity Select Equity ® Discipline Co-Manager, Fidelity Freedom ® Funds. "This Second edition will not remain on the shelf, but will be continually referenced by both novice and expert. There is a substantial expansion in both depth and breadth on the original. It clearly and concisely explains all aspects of the foundations and the latest thinking in active portfolio management." -Eric N. Remole, Managing Director, Head of Global Structured Equity, Credit Suisse Asset Management. Mathematically rigorous and meticulously organized, Active Portfolio Management broke new ground when it first became available to investment managers in 1994. By outlining an innovative process to uncover raw signals of asset returns, develop them into refined forecasts, then use those forecasts to construct portfolios of exceptional return and minimal risk, i.e., portfolios that consistently beat the market, this hallmark book helped thousands of investment managers. Active Portfolio Management, Second Edition, now sets the bar even higher. Like its predecessor, this volume details how to apply economics, econometrics, and operations research to solving practical investment problems, and uncovering superior profit opportunities. It outlines an active management framework that begins with a benchmark portfolio, then defines exceptional returns as they relate to that benchmark. Beyond the comprehensive treatment of the active management process covered previously, this new edition expands to cover asset allocation, long/short investing, information horizons, and other topics relevant today. It revisits a number of discussions from the first edition, shedding new light on some of today's most pressing issues, including risk, dispersion, market impact, and performance analysis, while providing empirical evidence where appropriate. The result is an updated, comprehensive set of strategic concepts and rules of thumb for guiding the process of-and increasing the profits from-active investment management.

Author: Laurence B. Siegel
Publisher: Research Foundation Publications
ISBN:
Category : Business & Economics
Languages : en
Pages : 158

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Author: Johan Hagenbjörk
Publisher: Linköping University Electronic Press
ISBN: 917929927X
Category :
Languages : sv
Pages : 156

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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.

Author: Emmanuel Jurczenko
Publisher: John Wiley & Sons
ISBN: 1786305445
Category : Business & Economics
Languages : en
Pages : 460

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Book Description
This new edited volume consists of a collection of original articles written by leading financial economists and industry experts in the area of machine learning for asset management. The chapters introduce the reader to some of the latest research developments in the area of equity, multi-asset and factor investing. Each chapter deals with new methods for return and risk forecasting, stock selection, portfolio construction, performance attribution and transaction costs modeling. This volume will be of great help to portfolio managers, asset owners and consultants, as well as academics and students who want to improve their knowledge of machine learning in asset management.

Author: Scott Stewart
Publisher:
ISBN:
Category :
Languages : en
Pages : 148

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Manager selection is a critical step in implementing any investment program. Investors hire portfolio managers to act as their agents, and portfolio managers are then expected to perform to the best of their abilities and in the investors' best interests. Investors must practice due diligence when selecting portfolio managers. They need to not only identify skillful managers, but also determine the appropriate weights to assign to those managers. This book is designed to help investors improve their ability to select managers. Achieving this goal includes reviewing techniques for hiring active, indexed, and alternative managers; highlighting strategies for setting portfolio manager weights and monitoring current managers; and considering the value of quantitative and qualitative methods for successful manager selection.

Author: John B. Guerard, Jr.
Publisher: Springer Science & Business Media
ISBN: 0387774394
Category : Business & Economics
Languages : en
Pages : 796

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Portfolio construction is fundamental to the investment management process. In the 1950s, Harry Markowitz demonstrated the benefits of efficient diversification by formulating a mathematical program for generating the "efficient frontier" to summarize optimal trade-offs between expected return and risk. The Markowitz framework continues to be used as a basis for both practical portfolio construction and emerging research in financial economics. Such concepts as the Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Theory (APT), for example, provide the foundation for setting benchmarks, for predicting returns and risk, and for performance measurement. This volume showcases original essays by some of today’s most prominent academics and practitioners in the field on the contemporary application of Markowitz techniques. Covering a wide spectrum of topics, including portfolio selection, data mining tests, and multi-factor risk models, the book presents a comprehensive approach to portfolio construction tools, models, frameworks, and analyses, with both practical and theoretical implications.