Guidance on Performance Attribution Presentation
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Performance Measurement in Finance : Firms, Funds and Managers
PERFORMANCE MEASUREMENT IN FINANCE Butterworth-Heinemann Finance aims and objectives • books based on the work of financial market practitioners and academics • presenting cutting edge research to the professional/practitioner market • combining intellectual rigour and practical application • covering the interaction between mathematical theory and financial practice • to improve portfolio performance, risk management and trading book performance • covering quantitative techniques market Brokers/Traders; Actuaries; Consultants; Asset Managers; Fund Managers; Regulators; Central Bankers; Treasury Officials; Technical Analysts; and Academics for Masters in Finance and MBA market. series titles Return Distributions in Finance Derivative Instruments: theory, valuation, analysis Managing Downside Risk in Financial Markets: theory, practice and implementation Economics for Financial Markets Global Tactical Asset Allocation: theory and practice Performance Measurement in Finance: firms, funds and managers Real R&D Options series editor Dr Stephen Satchell Dr Satchell is Reader in Financial Econometrics at Trinity College, Cambridge; Visiting Professor at Birkbeck College, City University Business School and University of Technology, Sydney. He also works in a consultative capacity to many firms, and edits the journal Derivatives: use, trading and regulations. PERFORMANCE MEASUREMENT IN FINANCE Firms, Funds and Managers Edited by John Knight Stephen Satchell OXFORD AMSTERDAM BOSTON LONDON NEW YORK PARIS SAN DIEGO SAN FRANCISCO SINGAPORE SYDNEY TOKYO -
Performance Measurement for Traditional Investment Literature Survey
EDHEC RISK AND ASSET MANAGEMENT RESEARCH CENTRE Performance Measurement for Traditional Investment Literature Survey January 2007 Véronique Le Sourd Senior Research Engineer at the EDHEC Risk and Asset Management Research Centre Table of contents Introduction ................................................................................................................................................................. 5 1. Portfolio returns calculation ............................................................................................................................... 6 1.1. Basic formula .............................................................................................................................................................................................6 1.2. Taking capital flows into account ....................................................................................................................................................6 1.3. Evaluation over several periods .......................................................................................................................................................10 1.4. Choice of frequency to evaluate performance .........................................................................................................................11 2. Absolute risk-adjusted performance measures ............................................................................................13 2.1. Sharpe ratio (1966) ...............................................................................................................................................................................13 -
Multi-Dimensional Risk and Performance Analysis for Equity Portfolios
An EDHEC-Risk Institute Publication Multi-Dimensional Risk and Performance Analysis for Equity Portfolios October 2016 with the support of Institute Table of Contents Executive Summary .................................................................................................5 Introduction ...............................................................................................................15 1. Literature and Practice Reviews ........................................................................21 2. From Historical Betas (and Alphas) to Fundamental Betas (and Alphas) ...45 3. Applications of Fundamental Beta ..................................................................59 4. Conclusion .............................................................................................................75 Appendix ....................................................................................................................79 References ..................................................................................................................83 About Caceis ...........................................................................................................89 About EDHEC-Risk Institute ................................................................................91 EDHEC-Risk Institute Publications and Position Papers (2013-2016) ........95 Printed in France, October 2016. Copyright EDHEC 2016. 2 The opinions expressed in this study are those of the authors and do not necessarily reflect those of EDHEC -
Performance Measurement and Evaluation
Munich Personal RePEc Archive PERFORMANCE MEASUREMENT AND EVALUATION Plantinga, Auke University of Groningen 26 September 2007 Online at https://mpra.ub.uni-muenchen.de/5048/ MPRA Paper No. 5048, posted 26 Sep 2007 UTC 1 CHAPTER 10. PERFORMANCE MEASUREMENT AND EVALUATION Auke Plantinga Faculty of Business and Economics Department of Finance University of Groningen The Netherlands 10.1 Introduction This chapter discusses methods and techniques for measuring and evaluating performance for the purpose of controlling the investment process. However, many of the methods discussed in this chapter are also used in communicating investment performance between the investment management company and it’s (potential) customers. Therefore, performance measurements also play an important role in the competition between investments management companies. Substantial evidence from the net sales of mutual funds shows that investors buy mutual funds with good past performance records although they fail to sell funds with bad past performance2. This chapter provides an overview of commonly used methods for measuring and evaluating the performance of investment management processes. In section 10.2 we discuss methods of calculating the returns of investment portfolios. We focus on the precision of such measures and the practical considerations in choosing a measure. In section 10.3 we discuss methods for evaluating performance, which are base on standard measures of risk such as standard deviation and Beta. In section 10.4 we present several alternative performance measures, which are based on measures of downside risk. If the performance of a portfolio deviates from the benchmark, it is desirable to figure out what the causes of this deviation are. -
Determinants of Levered Portfolio Performance
Determinants of Levered Portfolio Performance Robert M. Anderson∗ Stephen W. Bianchiy Lisa R. Goldbergz University of California at Berkeley April 21, 2014x Forthcoming in Financial Analysts Journal Abstract The cumulative return to a levered strategy is determined by five elements that fit together in a simple, useful formula. A previously undocumented element is the covariance between leverage and excess return to the fully invested source portfolio underlying the strategy. In an empirical study of volatility-targeting strategies over the 84-year period 1929{2013, this covariance accounted for a reduction in return that substantially diminished the Sharpe ratio in all cases. Key terms: Leverage; Sharpe ratio; source portfolio; trading cost; financing cost; unintended market timing; magnified source return; excess borrowing return; risk parity; pension fund; hedge fund; fixed leverage; dynamic leverage; volatility target ∗Department of Economics, 530 Evans Hall #3880, University of California, Berkeley, CA 94720-3880, USA, email: [email protected]. yDepartment of Economics, 530 Evans Hall #3880, University of California, Berkeley, CA 94720-3880, USA, email: [email protected]. zDepartment of Statistics, University of California, Berkeley, CA 94720-3880, USA, email: [email protected]. xThis research was supported by the Center for Risk Management Research at the University of Cali- fornia, Berkeley. We are grateful to Patrice Boucher, Dan diBartolomeo, Claude Erb, Ralph Goldsticker, Nick Gunther, Rodney Sullivan, Betsy Treynor, Jack Treynor, Barton Waring and Sorina Zahan and two anonymous referees for insightful comments on the material discussed in this article. Earlier versions of this paper circulated under the title \The Decision to Lever." 1 1 A Simple Two-Period Example In this paper, we show that there are five elements that determine the cumulative return to a levered strategy, and they fit together in a simple, useful formula.