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Noël Amenc, Lionel Martellini and Daphne SfeirEDHEC Risk And Asset Management Research Centre
Date:
February 2002
Abstract:
In this paper, we propose an integrated framework for assessing the risk-adjusted performance of mutual fund managers. The methodology is designed so as to be consistent not only with modern portfolio theory but also with constraints imposed by practical implementation in a context where the presence of a variety of investment styles needs to be acc ounted for.
Application of a Linear Regression Model to the Proactive Investment Strategy of a Pension Fund
Author:
Kenneth G. Buffin
Date:
2001
Abstract:
The consulting actuary is typically concerned with pension plan design and funding issues. For large pension plans, the preparation of asset/liability studies and fund projections will present many challenges and opportunities for the consultant, including the development of optimal asset allocation strategies and risk mitigation strategies. Investment performance measurement and attribution analysis are two other areas where actuaries can make useful contributions to effective asset/liability management. This paper advocates a broader role for actuaries in the proactive investment strategy of a pension fund by utilizing quantitative techniques and feedback analysis.
Equity fund managers are measured by track records relative to published benchmarks and their peers in performance surveys. These performance comparisons are based on pre-tax returns and, thus, hide important information for tax paying investors. This essay briefly outlines the impact of franked dividend yield and turnover on after-tax returns for superannuation investors in the Australian taxation environment...
The motto of professional investment performance evaluators has long been to evaluate skill, not luck."" However, about five years ago, those of us in the evaluation business became aware of the significance of investment style in measuring skill. That is, we learned that skill could only be properly identified if we first lifted the thick clouds of style that routinely distort our perspective. The immediate past is a good case in point. Damning Growth stock managers for their recent losses is folly because it's style, not skill, that is the culprit...
The year end client servicing cycle is upon us, and we’ll soon be putting investment performance into perspective. The following highlights from our December Surz Market Review should be helpful to this purpose.
The commentary covers the past year, 5 years and 80 years.
David B. Loeper, CIMA, Wealthcare Capital Management
Date:
December, 2000
Abstract:
...thousands of advisors who have promoted their value based on the theory of asset allocation and MPT are facing the reality of asset allocation’s practical failure being exposed by the mathematical facts of sophisticated Monte Carlo and probability analysis…
In July 2002, Morningstar unveiled a revised star-rating system designed to eliminate the style-based bias of the old system. The new system includes two innovations for categorizing funds that have received little attention.
The old star-rating system compared historic risk and returns of a mutual fund against the risk and return of one of four broad groups of funds: domestic stock, international stock, taxable bond and tax-exempt bond.
As a consequence, a fund's star rating primarily reflected whether its investment style had been hot or cold, while it was intended to reflect the fund's management skill.
The new system attempts to correct the style bias by comparing a fund's performance against a much smaller group of "similar" funds, such as comparing a small-cap value fund against other small-cap value funds. It promises to do a better job of reflecting the fund's management skill.
The method Morningstar has developed for assigning funds to a particular fund category (28 new stock fund categories and 20 new bond fund categories) creates two innovative ideas.
Equity funds are now separated across a value-growth dimension based on value and growth factors instead of value factors alone.
Investment-grade bond funds are now funneled into categories based on duration and government-general dimensions instead of duration and quality. While reasonable in theory, these approaches are untested empirically.
Singer and Karnosky's (1995) exact and complete return attribution framework does not account for risk, since it ignores accumulated historical information. Its implied investment strategy selection is based on simple return maximization and ignores....
This paper explores the investment styles in mutual funds and hedge funds. The results indicate that there are 39 dominant mutual fund styles that are mixes or specialized subsets of nine broadly defined asset classes. There is little evidence of market timing or asset class rotation in these dominant mutual fund styles. There are five dominant hedge fund styles. Two are correlated with broadly defined asset classes, while the other three are dynamic trading strategies on a number of asset classes. Thus, a 12-factor model with nine asset classes and three dynamic trading strategies should provide a good first step in a unified approach for performance attribution and style analysis of mutual funds and hedge funds.
Perspectives on Capital Markets in 2006 and Beyond
Author:
Ron Surz, PPCA
Date:
January 2007
Abstract:
The U.S. stock market, as measured by the entire Compustat database, returned 16% in 2006, as did the narrower S&P 500. As shown in the exhibit to the right, the 2006 S&P return is substantially higher than its long-run ( 81-year) history of 10% returns per year. By contrast, a 3% return on bonds, as measured by the Citigroup High Grade Corporate Bond Index, is below historical norms. Completing the annual picture, inflation at 3% and T-bill returns at 5% are both near historical averages. It was a good year for stock investors, but not so good for bonds, which is just the opposite of 2005....
Ratings and Rankings: What They Can Tell You About Financial Companies
Author:
Teachers Insurance and Annuity Association College Retirement Equities Fund
Date:
July 1998
Abstract:
When you’re saving and investing for the future, you want to rest assured that your money is in the hands of a solid, reputable organization — in other words, that your money is going to be there when you need it. You probably also want to know how these assets are performing, relative to the risk level you’re comfortable with for meeting your goals. Ratings of financial companies and investment funds can help answer both of these questions.
SEI Investments - Manager Selection and Monitoring
Author:
SEI Investments
Date:
June 2001
Abstract:
SEI Investments takes a highly disciplined approach to investing, based on years of research and experience. SEI has over 30 years of providing manager analysis and performance evaluation. Historically the nation’s largest pension consulting firm, our credentials have included being the performance “report card” for such firms as Fidelity Investments, Goldman Sachs, Salomon Brothers, Alex Brown and many others. These organizations looked to SEI to determine how well their managers were performing....
Selecting, Reviewing and Replacing Investment Managers
Author:
Investment Policy Committee, UWO Pension Plans for Academic and Administrative Staff
Date:
January 2000
Abstract:
Executive Summary: The Investment Policy Committee of the UWO Joint Pension Board recommend that the documentation of the selection, review and replacement process for investment managers for the UWO pension plan assets is essential. This document is reference for the pension board and all other interested parties which illustrates the consistent method employed by the committee in these activities.
The Investment Policy Committee first apply the Joint Pension Boards principles, which are outlined in detailed in their policy & governance document, for the selection, review and replacement of investment managers. In particular the principles of Choice, Fairness and Liquidity are considered as well as the bias towards Passive Management. Consideration of these principles, however, does not provide all the answers. The committee also considers the universe of alternatives available for the task, the professional research and opinions provided by the pension boards investment consultant, the performance history of the managers, the style and investment process employed by managers as well as the administrative implications selecting or replacing a manager. == This document lays out the board activities with respect to investment managers and includes certain actions that will normally be considered by the committee given certain situations, such as a change in the opinion of our investment consultants or consecutive quarters of under performance of a benchmark.
The committee also considers the universe of alternatives available for the task, the professional research and opinions provided by the pension boards investment consultant, the performance history of the managers, the style and investment process employed by managers as well as the administrative implications selecting or replacing a manager.
This document lays out the board activities with respect to investment managers and includes certain actions that will normally be considered by the committee given certain situations, such as a change in the opinion of our investment consultants or consecutive quarters of under performance of a benchmark.
The Performance of Local versus Foreign Mutual Fund Managers
Author:
Rogér Otten & Dennis Bams
Date:
January 2003
Abstract:
In this paper we examine the performance of local US equity funds versus foreign UK funds also investing in the US equity market. Based on informational disadvantages one would expect the foreign funds to under-perform the local funds, especially in the research intensive small company market. After controlling for tax treatment, fund objectives, investment style and time-variation in betas, we do not find evidence for this. In the small company segment we even find a slight out-performance for foreign funds compared to local funds. In addition to that we observe a home bias in the UK portfolios, which could not be explained by currency effects or other non-US equity holdings.
Trading Costs and Return Volatility: Evidence From Exchange Listings
Author:
Hendrik Bessembinder & Subhrendu Rath
Date:
January, 2002
Abstract:
Bid-ask spreads and return volatility both decline substantially following Exchange listing for firms that moved from Nasdaq to the NYSE between 1996 and 2000, with the largest reductions in volatility for firms with the largest reductions in spreads.
This finding is inconsistent with the often-expressed reasoning that volatility can be reduced by increasing trading costs, e.g. by imposing a transactions tax. Decreases in bid-ask spreads and volatility continue to be observed, but are smaller in magnitude, for stocks that list after the 1997 adoption of market reforms. Consistent with the results reported by Barclay (1997) for an earlier sample, but somewhat surprising in light of market reforms, the largest spread reductions are for stocks where Nasdaq liquidity providers round quotations most often.
Year End Investment Performance Reviews: Phlebotomy or Ideonomy?
Author:
Ron Surz, PPCA
Date:
January 2007
Abstract:
Annual investment performance reviews are showing that value has outperformed growth recently. Furthermore these reviews show that investors generally would have been better off with passive value indexes over active value managers, but that the reverse is true for the growth style because active growth managers have generally beaten growth indexes. What is going on here?
A Performance Attribution Model For Fixed-Income Portfolios
Author:
Nabil Khoury, Marc Veilleux & Robert Viau
Date:
2003
Abstract:
Eleven factors to consider when evaluating bond holdings.
Performance attribution analysis partitions a portfolio’s ex-post return into specific components associated with particular decisions made during the management process, in order to assess their impact on overall performance.
In the case of equity portfolios, attribution analysis typically breaks down ex-post return into three components related to asset allocation decisions, industry choice decisions and security selection decisions. The contribution of each component to the overall performance of the portfolio is then determined by calculating the negative or positive departure of its associated return from that of a corresponding benchmark.
This process can shed light on the efficiency of the portfolio’s management process and identify areas where changes could enhance performance...
Accurate Benchmarking is Gone but Not Forgotten: The Imperative Need to Get Back to Basics
Author:
Ron Surz, PPCA Inc & RCG LLC
Date:
September 2006
Abstract:
Investment performance evaluators have lost touch with a basic and self-evident truth: If the benchmark is wrong all of the analytics are wrong. The cost of this mistake is high because investment managers are hired and fired for the wrong reasons, sacrificing performance and fees.
It’s imperative that we get back to basics, that we get the benchmark right. Fiduciary prudence dictates best practice over common practice despite popular opinion to the contrary, as does the “do no harm” rule. Indexes and peer groups are the common forms of benchmarks. These are not best practices. The article describes how accurate benchmarks can be constructed from indexes and how peer group biases can be overcome.
Ted J. Schwartzman, Investments Management Institute Endowments and Foundation Forum
Date:
January 2002
Abstract:
This is a presentation that looks at alternative asset structure, private equity and alternative assets due diligence, and representative costs of alternative asset programs….
Apodictic Evaluation of Hedge Fund Performance: A Necessary Truth
Author:
Ron Surz, PPCA Inc
Date:
2004
Abstract:
A white paper on a significant breakthrough in the evaluation of hedge fund performance.
It takes a distinctive word to describe the subject of this article. The word “apodictic” means “expressing necessary truth”. This word also contains the letters POD, which is the acronym for the subject of this article: Portfolio Opportunity Distributions. Peer groups and indexes simply don’t work for hedge funds. POD for hedge funds, or HedgePOD, solves the problem that has vexed these other evaluation approaches: each hedge fund is unique, and therefore without peers...
The decision of asset allocation is one of, if not the, most important one an institutional investor can make. There are a number of considerations to take into account when trying to make this decision, and there is no right answer for all investors. The appropriate asset allocation is contingent upon the type of investor, risk appetite, and overall objective. The basic inputs for asset allocation models are expected returns, expected yields, risk estimates, correlations, time frame, expected payouts and any other client-specific factors. This paper will outline three different types of asset allocation....
Andrew Baum, Tony Key, George Matysiak, Joakim Franson
Date:
June 1999
Abstract:
Property investors, increasingly, use performance measurement - or 'benchmarking' -services. They exist, first and foremost, to show whether a portfolio has achieved a rate of return better or worse than the 'market' average, or met investment objectives specified in a more sophisticated fashion. After benchmarking has answered the question by how much did we out- (under-) perform the benchmark?, there is an inevitable demand for 'portfolio analysis' which addresses the question why did we out(under-) perform the benchmark? An ideal system of portfolio analysis would identify the contribution of all aspects of portfolio strategy and management to relative returns. It would separate, for example, profits earned on investments from returns on held properties. Those are two distinctly separate activities with different return and risk characteristics, and reflect different features of management 'skill'. Among held properties, relative return may be influenced by anything and everything from the broadest allocation of investment between sectors to skill in selecting tenants, negotiating rent reviews, and controlling operating expenses.
Evaluating Hedge Fund Performance: A brief presentation
Author:
Ron surz, PPCA Inc
Date:
September, 2006
Abstract:
Despite the growing popularity & importance of hedge fund investing, hedge fund due diligence, as it is currently conducted, is a sham. Well meaning analysts continue to use peer group comparisons to evaluate hedge fund performance even though hedge fund peer groups have well-documented deficiencies. Consequently, losers are hired while winners go undetected. This is a serious mistake that is a source of inferior fund-of-funds performance.
The short 20-slide presentation reviews 7 articles that document the following:
· The deficiencies of hedge fund peer groups
· A solution to the problems with hedge fund groups
· Examples of new & improved hedge fund due diligence
Hedge Fund Strategy Performance: Using Conditional Approaches
Author:
Bhaswar Gupta,Burak Cerrahoglu & Alper Daglioglu
Date:
October 2003
Abstract:
The search for methodologies that accurately measure performance and performance persistence continues to evolve. This is especially true for investment strategies such as hedge funds, which have been shown, in several instances, to not be normally distributed. In this article, we evaluate performance of hedge funds using conditional approaches and GMM. Unlike the Sharpe ratio or Jensen’s alpha, our results would still be valid even if hedge funds were not normally distributed. We use the CISDM hedge fund database for this study. We create three portfolios to measure performance: an Active portfolio (which consists of funds in the active database), a Dead portfolio (which consists of funds in the defunct database) and an All portfolio (which consists of funds in both the active and defunct databases). We find that while the Active portfolios show evidence of positive risk-adjusted returns in most cases, the Dead portfolios do not and only some of the All portfolios show evidence of positive risk-adjusted returns. The results are similar irrespective of whether we use Jensen’s alpha or conditional approaches. Our results point to two conclusions: one the explanatory variables used in this paper may not be able to capture the type of trading strategies followed by hedge fund strategies and two the estimated alphas are good estimates of the true alphas which are mostly due to managers’ skills and hence cannot be explained by naïve static or dynamic trading strategies. In our analysis of market timing models, we show that hedge fund managers in general lack market timing ability and fund level analysis is required to determine the few that do have market timing ability. The results also suggest that hedge fund returns have option-like properties and future research should include option-based factors in performance evaluation.
A presentation that was held at the Eighth Annual Asset Alternatives Private Equity Analyst Conference. The topic was on performance measurement, persistance and Internal Rate of Return….
Implementation Risk: An Important Piece of the Hedge Fund Risk Puzzle
Author:
Ron Surz, PPCA Inc
Date:
December 2005
Abstract:
The financial press has recently reported favourably that some long-only managers have added short selling to their process. For example Chernoff [2005] identifies several traditional managers who are offering portfolios that are 130% long and 30% short, thereby maintaining a 100% net exposure.
On its face this would appear to be a win-win: Net market exposure is unchanged, so risk is unchanged, but the manger can add value by selling short companies that he deems inferior.
The realities however are that risk is indeed increased....
The Property Council of New Zealand’s Investment Performance Index is an appraisal based accumulation index that measures the income, capital and total returns from institutional property in New Zealand. It was developed with the aim of providing subscribers with reliable and timely information on the investment performance of different property sectors and locations. The Index is compiled quarterly from information supplied by the industry’s largest property fund managers and owners. The Index collects direct information regardless of the investment holding structure. Therefore listed property trusts are included in the Index....
Monte Carlo simulations clarify hedge fund implementation risk
Author:
Ron surz, PPCA Inc & RCG LLC
Date:
August 2006
Abstract:
There’s an important aspect of hedge fund risk that is not currently being recognized, and its omission can lull investors into a false sense of comfort.
The “hedge” in hedge fund implies that risk is lower than it is in traditional investing....
.... Success in the hedge fund world can be substantial, and it can come with little apparent increase in risk, but there’s symmetry on the downside as well.
Hedge fund due diligence can be improved through the use of Monte Carlo simulations that compare the manager’s actual performance to all of the possible implementations of his strategy, thereby capturing both traditional and implementation risks.
Monte Carlo Simulations for Evaluating Hedge Funds
Author:
Ron Surz, PPCA
Date:
May 2005
Abstract:
Monte Carlo simulations are well-known to the alternative investment community. Randomly generated outcomes provide a backdrop for the decision making by revealing what could happen under uncertainty.
In this article we introduce a new use for Monte Carlo simulations that evaluates investment performance by comparing what actually happened -- a fund's actual return -- to what could have happened -- the range of possible implementations of the fund's strategy. Specifically we advocate the use of Monte Carlo simulations, rather than peer groups, for evaluating the performance of long-short equity hedge fund managers.
The Morningstar Index family consists of 16 U.S. equity indexes that track the U.S. market by capitalization and investment style. They were built using a comprehensive and non-overlapping approach, based on the methodology of the Morningstar Style Box ™ ....
This article is the winner of The Best Research Paper Presented by a Practicing Real Estate Professional manuscript prize [sponsored by the American Real Estate Society Foundation (ARESF)] presented at the 2001 American Real Estate Society Annual Meeting.
The popularity of performance attribution in the publicly-traded equities arena may soon spill over to real estate markets. With that in mind, this study analyzes the practical and statistical problem that may arise when real estate managers apply this technique to their portfolios. The study involves three data sets: a portfolio of publicly-traded REITs, a single-client separate account and a multi-client private REIT. The findings indicate that there is no clear distinction between stock selection and sector allocation in any of the data sets (i.e., the portfolio impact of the manager’s sector allocation and asset selection decisions are, on average, indistinguishable). Also, for the publicly-traded REIT portfolio (the only data set with sufficient sample size), the monthly returns attributed to stock selection versus sector allocation do not display significant serial persistence (i.e., the manager cannot consistently attribute the portfolio returns to either the stock selection or sector allocation decision).
Replication and Evaluation of Fund of Hedge Funds Returns
Author:
Harry M. Kat and Helder P. Palaro - Cass Business School, City University
Date:
January 2006
Abstract:
In this paper we use the hedge fund return replication technique recently introduced in Kat and Palaro (2005) to evaluate the net-of-fee performance of 485 funds of hedge funds. The results indicate that the majority of funds of funds have not provided their investors with returns, which they could not have generated themselves by trading S&P 500, T-bond and Eurodollar futures. Purely in terms of returns therefore, most funds of hedge funds have failed to add value.
Responses to the Preferences for Hazardous Peer Groups
Author:
Ron Surz, PPCA Inc
Date:
May 2005
Abstract:
Many who have read “Warning: Peer Groups Are Hazardous to Your Wealth” have responded with reasons that they still prefer peer groups over the alternative of Monte Carlo simulations. Monte Carlo Simulations, or MCS, really are superior backdrops for evaluating investment performance.
This article addresses the concerns that have been raised regarding the use of Monte Carlo simulations to evaluate investment erformance. We show that that these concerns are merely faulty rationalizations to cling to the old ways.
Executive Summary. In this study, we offer a refinement to a return attribution method proposed by the pioneers of return attribution analysis. Returns for the aggregate portfolio are decomposed into selection and allocation contributions as originally presented. We introduce the use of a neutral effect, which aggregates to zero at the portfolio level, that insures proper interpretation of the decomposition of the sector returns of the portfolio into selection and allocation contributions. This refinement is particularly relevant to private real estate investment, where portfolio performance is measured against both an aggregate benchmark and benchmarks for sub-sectors. In addition, we suggest a methodology for performing multi-period attribution analysis. Further, we offer a new presentation format to report both single and multi-period return attributes.
Risks and Portfolio Decisions involving Hedge Funds
Author:
Vikas Agarwal, Georgia State University & Narayan Y. Naik, London Business School
Date:
July 2002
Abstract:
Hedge funds are known to exhibit non-linear option-like exposures to standard asset classes and therefore the traditional linear factor model provides limited help in capturing their risk-return tradeoffs. We address this problem by augmenting the traditional model with option-based risk factors. Our results show that a large number of equity-oriented hedge fund strategies exhibit payoffs resembling a short position in a put option on the market index, and therefore bear significant left-tail risk, risk that is ignored by the commonly used mean-variance framework.
Using a mean-conditional Value-at-Risk framework, we demonstrate the extent to which the mean-variance framework underestimates the tail risk. Working with the underlying systematic risk factors, we compare the long-run performance with the recent performance of hedge funds and find that their recent performance appears significantly better than their long-run performance. Our analysis provides important insights that can be helpful in addressing issues like construction of fund of funds, risk management, benchmark design and manager compensation involving hedge funds.
Shame on the Sham: The Due Diligence Dreg in the Hedge Pledge
Author:
Ron surz, PPCA Inc & RCG LLC
Date:
May, 2006
Abstract:
The paper proposes a solution to problems associated with evaluating the performance of long-short equity hedge fund managers, and argues that contrasting a manager’s investment return to a peer group or index does not work for hedge funds.
Investors need to recognize the deficiencies of popular due diligence approaches and consider other methodologies, according to the author. Mr. Surz asserts that that hedge fund due diligence can be distilled down to two topics: a manager’s investment strategy and the manager’s execution of that strategy.
A vital part of a true due diligence process, according to the paper, is getting the numbers to tell their most important stories, confirming subjective judgments about the talent of the people and the wisdom of their processes and philosophy.
Testing the Hypothesis “Hedge Fund Performance Is Good”
Author:
Ron Surz, PPCA Inc
Date:
October, 2004
Abstract:
In this article, we describe the reasons traditional performance evaluation approaches do not work—for traditional investments as well as hedge funds. However, unlike previous articles that have simply documented the problems, we offer a solution: Namely, performance evaluation in general, and hedge fund performance evaluation in particular, should be viewed as a hypothesis test where we assess the validity of the hypothesis “Performance is good.”
To accept or reject this hypothesis, the textbooks say you should construct all of the possible outcomes and see where the actual performance result falls. If the observed performance is toward the top of all of the possibilities, the hypothesis is correct, and performance is good. Otherwise, it is not. In other words, the hypothesis test gives us a chance to determine if a manager truly has the skill to outperform a group of monkeys randomly playing the same game…
In the last decade, the investment community has witnessed the emergence of style investing, not only in the traditional long-only universe but also in the alternative investment universe. In this paper, we attempt to emphasize the need for a better understanding of investment style benchmarks by focusing on the alternative investment universe where the problems are most visible. The fact that hedge funds have started to gain wide acceptance while remaining a somewhat mysterious asset class enhances the need for better measurement and benchmarking of their performance. One serious problem is that the collection of existing hedge fund indexes consitutes a somewhat confusing partition of the alternative investment universe since the dozen existing competing hedge fund index providers provide a very contrasted picture of hedge fund returns.
Our contribution is two-fold. First, we provide detailed evidence of strong heterogeneity in the information conveyed by competing indexes. Second, we attempt to provide remedies to the problem and suggest a methodology designed to help build a “pure style index” or “index of the indexes” for a given style. In particular, we suggest using principal component analysis to extract the best possible one-dimensional summary of a set of competing indexes. We also provide evidence of the ability of the pure style indexes to improve current techniques for factor analysis and benchmarking of hedge fund returns. In particular, we find that our pure style indexes explain on average a significantly larger proportion of hedge fund returns than competing indexes. Our results can easily be extended to traditional investment styles such as growth/value, small cap/large cap.
A Paper Presented at the 8th Annual European Real Estate Society Meeting.
In estimating the inputs into the Modern Portfolio Theory (MPT) portfolio optimisation problem, it is usual to use equal weighted historic data. Equal weighting of the data, however, does not take account of the current state of the market. Consequently this approach is unlikely to perform well in any subsequent period as the data is still reflecting market conditions that are no longer valid. The need for some return-weighting scheme that gives greater weight to the most recent data would seem desirable. Therefore, this study uses returns data which are weighted to give greater weight to the most recent observations to see if such a weighting scheme can offer improved ex-ante performance over that based on un-weighted data.
Warning! : Peer Groups Are Hazardous to Our Wealth
Author:
Ron Surz, PPCA
Date:
January 2005
Abstract:
As annual performance reviews take place over the next couple of months, we ought to avoid making peer group comparisons. Despite popular belief, peer groups do not reveal who has succeeded or failed. Success against one peer group can easily be failure against another comparable peer group, so a manager can be both a success and a failure, and frequently is. It just doesn’t make sense.
Peer groups are hazardous to our wealth because they are more likely to mislead than to inform, so we make the wrong decisions. This is not just my opinion. Others have written about the problems with peer groups as well, and most readers have expressed their own concerns. Each peer group provider has its own definitions and its own collection of funds, so each provider has a different sample for the same investment mandate. “Large cap growth” is one set of funds in one provider’s peer group and another set of funds in the next provider’s peer group. These sampling idiosyncrasies are the sources of the biases that mislead.
Fortunately, there is a solution: Monte Carlo simulation of all of the portfolios that the manager could have held. Performance evaluation tests the validity of the hypothesis "performance is good" by comparing the actual performance number (what actually happened) to what could have happened. The primary beneficiaries of the recommended new approach are investment management firms, especially those in volatile styles/strategies, because survivor bias goes away, even though these firms are likely to feel most threatened by it. But the real beauty lies in the fact that investors benefit as well -- everybody wins.
Monte Carlo may sound like gambling but it actually takes risk off the table.
Investment manager researchers observe that when a style is in favor it becomes harder to beat the popular style indexes associated with that style. It also becomes easier to beat indexes for the style that is out of favor.
The common interpretation of this phenomenon is that skillful managers shine brightest when their style is out of favor. The reality is that it has nothing to do with skill and everything to do with faulty peer groups.
... An area of performance which hasn’t seen the development of standards is in the area of performance attribution. In fact, many have suggested that such standards would not be welcome. The author shared these same views until he was convinced that there could be significant benefits from developing standards. We have come to realize that standards are needed for attribution....
I applaud the proposed approach to performance attribution standards which aims at clearly conveying information, that enables informed evaluation of performance attribution models, by:
1. Imposing a common language,
2. Requiring that employed models be described and categorized,
3. Requiring that employed models be internally consistent,
4. Not imposing specific models.
My concern is that the definitions, requirements and recommendations of this draft of the proposal are not yet clear and unambiguous enough to fulfill these goals.
This is a letter that provides comments from the Dutch, Italian and Swiss practices of Ernst & Young as regards the proposed case for attribution standards….
New provisons have been added to the standards. Highlighted portions represent new provisions being added to the GIPS standards. All other (non-highlighted) provisions represent modifications to existing GIPS provisions.
EUROPEAN INVESTMENT PERFORMANCE COMMITTEE - Regional Investment Performance Subcommittee of the Investment Performance Council (IPC)
Date:
Not Provided
Abstract:
This article looks to answer some questions on "Return Attribution" which is a technique used to analyse the sources of excess returns of a portfolio against its benchmark into the active decisions of the investment management process.
This is becoming an increasingly valuable tool not only for assessing the abilities of asset managers and identifying where and how value is added but also for facilitating a meaningful dialogue between asset manager and client. Risk and return attribution are equally valuable tools for assessing the abilities of asset managers, however, the authors have focused on the attribution of historic returns.
The method used in the calculation and examination of the relevant investment performance(s) and the resulting presentation must depend on the purpose of the assessment. The periods over which the investment performance is calculated must be appropriate to the purpose of the measurement....
...Investors using investment management companies adhering to UKIPS can be confident that not just the information presented to them, but the entire firms process, has been independently verified in order to gain compliance with the Standards. As more managers come to understand the business-winning potential of providing information in a clear and standardised way, not just in the UK but in the international arena, the sooner investment understanding will improve....
Proposal For The Evolution of GIPS. Process Objective To Have The IPC and The AIMR Board Approve The “Gold” GIPS Standards By February 2005 Governing Consideration • Achieving The Right Balance...
A generalized performance attribution technigue for mutual funds.
Author:
Antonella Basso & Stefania Funari
Date:
September 2001
Abstract:
In this contribution we propose a model which can be used to define a measure of the relative performance of mutual funds that takes into account all the different aspects considered by the traditional performance indexes. In addition, the model proposed can take into account also the subscription and redemption costs.
This model adopts a data envelopment analysis approach. In particular, among the inputs considered by the model we have different risk measures of the portfolio and the subscription costs and redemption fees. The set of outputs taken into account comprise the portfolio expected return, the traditional performance indexes and a stochastic dominance indicator.
An average cross efficiency measure is also suggested, in order to give a measure of the rating of a fund from the point of view of the styles of all the funds under consideration.
The generalized performance attribution techniques proposed are tested using data of the Italian mutual funds market.
Addressing Attribution Through Contribution Analysis: Using Performance Measures Sensibly
Author:
John Mayne, Office of the Auditor General of Canada
Date:
June 1999
Abstract:
A significant element of public sector reform in many jurisdictions is the move away from a management regime focussed on rules and procedures toward an approach that pays greater attention to the results being sought for citizens with taxpayers’ dollars. Managing for results, results-based management and performance management have become common terms in public sector reform discussions (Auditor General of Canada 1997, Treasury Board Secretariat 1997, OECD 1997).
The aim is to change the culture of public administration from one that is rules focussed to a culture focussing instead on the results that matter to citizens. This approach is characterized by measuring progress toward results that are sought, having the flexibility to be able to adjust operations to better meet these expectations, and reporting on the outcomes accomplished. Some jurisdictions have legislated this approach to public administration.
In many cases, progress has been made in moving in this direction. Nevertheless, the challenges of managing for results have been and remain significant, in particular the difficulty of measuring outcomes in the public sector in a cost-effective manner. Some of these problems are discussed below. There is an additional related problem that has not received enough attention: the need to rethink how we deal with accountability in this new management paradigm....
This paper shows how to decompose the dollar profit earned from an option into two basic components:
*mispricing of the option relative to the asset at the time of purchase, and
* profit from subsequent fortuitous changes or mispricing of the underlying asset.
This separation hinges on measuring the “true relative value” of the option from its realized payoff. The payoff from any one option has a huge standard error about this value that can be reduced by averaging the payoff from several independent option positions. It appears from simulations that 95% reductions in standard errors can be further achieved by using the payoff of a dynamic replicating portfolio as a Monte Carlo control variate. In addition, it is shown that these low standard errors are robust to discrete rather than continuous dynamic replication and to the likely degree of misspecification of the benchmark formula used to implement the replication.
The first basic component, the option mispricing profit, can be further decomposed into profit due to superior estimation of the volatility (volatility profit) and profit from using a superior option valuation formula (formula profit). In order to make this decomposition reliably, the benchmark formula used for the attribution needs to be similar to the formula implicitly used by the market to price options. If so, then simulation indicates that this further decomposition can be achieved with low standard errors.
The second basic component can be further decomposed into profit from a forward contract on the underlying asset (asset profit) and what I term pure option profit. The asset profit indicates whether or not the investor was skillful by buying or selling options on mispriced underlying assets. However, asset profit could also simply be just compensation for bearing risk – a distinction beyond the scope of this paper. Although simulation indicates that the attribution procedure gives an unbiased allocation of the option profit to this source, its standard error is large – a feature common with attempts by others to measure performance of assets.
In order to delineate investment responsibility and measure performance contribution, pension plan sponsors and investment managers need a clear and relevant method of attributing returns to those activities that compose the investment management process investment policy, market timing and security selection. The authors provide a simple framework based on a passive, benchmark portfolio representing the plan´s long-term asset classes, weighted by their long-term allocations. Returns on this ´”investment policy” portfolio are compared with the actual returns resulting from the combination of investment policy plus market timing (over or under weighting asset classes relative to the plan benchmark) and security selection (active selection within an asset class)....
EIPC - Guidance on Performance Attribution Presentation
Author:
The European Investment Performance Committee (EIPC)
Date:
2004
Abstract:
Performance attribution has become an increasingly valuable tool not only for assessing asset managers’ skills and for identifying the sources of value added but also for facilitating a meaningful dialogue between investment managers and their clients.
Like any other performance presentation, a presentation of performance attribution results provides meaningful information to the user only to the extent the user understands the assumptions and concepts underlying this presentation. That’s why it is crucially important that the presentation of attribution results is provided in a way that does not mislead the users and contains all necessary disclosures to explain the underlying assumptions and concepts ...
Performance Attribution of Active Managers: Where are the excess returns coming from?
Author:
Robert A. Gillam, McKinley Capital Management
Date:
May 2003
Abstract:
Traditional attribution analysis focuses on identifying active returns in relation to a particular benchmark. Active returns are typically measured and broken-down by country, currency, sector, industry, size, and style, to discover where benefit came from, and thus, to determine if a specific roster of managers participated in that benefit. While this type of analysis may make for an interesting study, it is of little practical assistance to the plan sponsor community in that it does not assess these attributes to the concept of “manager skill”.
Identifying manager skill is the more important use of these attribution tools, because it allows plan sponsors to predict where positive active returns will come from in the future. Manager skill directly correlates to positive active returns. Therefore, this paper will focus on the task of identifying manager skill, specifically as it relates to international managers.
The paper’s purpose is to highlight the attribution pitfalls that prevent accurate identification of manager skill by simultaneously bringing together the available academic and practitioner research. It analyzes the differences in output that can occur as a result of specific attribution inputs or assumptions. The paper also undertakes a realistic review of the portfolio constraint impact on active return and its identification (or lack thereof) by attribution tools. Limitations of these tools in the international arena will be examined. Finally, solutions will be discussed and a comprehensive eight-step blueprint for identifying manager skill will be proposed.
In this paper, the authors propose a new method for return attribution in multiple periods. Several methods have been proposed in the literature (e.g., Cariño (1999), Frongello (2002a), Menchero (2000), Davies and Laker (2001)), which have been the cause of a heated debate among practitioners (e.g., Laker (2002), Frongello (2002b)). Acknowledging that it may be premature to speak of an “exact” or superior method, they feel that the method presented
• performance measures of managed funds
• how to adjust for risk
• the axiomatics of performance attribution
• multi-period performance attribution
• fixed-income performance attribution
Performance attribution is a mechanism by which investment management skills can be assessed. Managing portfolios requires managers (or team of managers) to build a strategy and make a combination of decisions in order to beat the return that would be obtained from a passively managed portfolio. The passive return, often called the benchmark, is usually represented by market indices or by model portfolios....
Stewart Eisenhart, Hedge Fund & Investment Technology
Date:
October 2005
Abstract:
Performance measurement and attribution capabilities continue to grow in importance to buy-side firms as institutional and regulatory pressures mount, but as with other middle- and back-office issues, managers active in fixed income and other more complex asset classes have largely had to rely on their own IT resources.
● Despite progress by a handful of vendors, fixedincome managers continue to rely on a combination of third-party and proprietary systems to attain accurate fixed income attribution.
● Performance measurement and attribution tools based on equities models are often used by managers for fixed income and other asset types, but are ultimately ill-suited to provide meaningful data on securities they weren’t designed to cover.
● The commoditisation of buy-side performance measurement has led to the outsourcing of the function to administrators, while attribution remains an in-house process and as a source of internal and external reports, as well as a competitive differentiator between managers.
An Analysis of a Source of Errors in Performance Measurement
Author:
Peter Vann, PhD, MSc, BSc,ASIA
Date:
1999
Abstract:
A portfolio’s return is a measure commonly used to determine the success of its management. It is not uncommon that a portfolio’s performance is compared to that of a benchmark, typically market indexes like the All Ordinaries and the SBC Bond Index. Most portfolios are actively managed and/or have contributions, withdrawals and income through performance measurement periods, and portfolio valuations are often less frequent (e.g. weekly or monthly); in these circumstances, money weighted return approximations are often used to calculate the portfolio managers return…
Investment Performance: How to Get It, How to Measure It
Author:
Al Hrabak
Date:
March 1998
Abstract:
This is a summary of the National Association of State Auditors, Comptrollers and Treasures 1998 Public Fund Investment Performance Conference. Agender topics included "The Custodian's Role in Investment Performance Reporting", "Active Management: Return Expectations and Benchmark Alternatives", "Performance Audit as a Management Tool", along with several others.
Performance Measures Leave Some Investors Seeing Double
Author:
Bill Montague, Consulting Group Senior Financial Writer
Abstract:
Sometimes it seems the investment industry has more returns than a department store on the day after Christmas. Total return, net return, relative return, risk-adjusted return – these are just a few of the measuring sticks used to evaluate portfolio gains and losses…
Time-Weighted Return - What is it and why it is the best choice for managed accounts?
Author:
www.orionadvisor.com
Date:
August, 2003
Abstract:
An investor evaluating their investment portfolio often simply wants to know whether they had a gain or a loss during a certain period. Defining that gain or loss brought about the creation of performance measures. Performance measures are designed to produce numbers that represent percentage returns. They are designed to give investors relevant information on their investments’ and total portfolio’s performances. The information should give them a common means of measure against other investments and other portfolio managers…
Michel M. Dacorogna, Ulrich A. Muller & Olivier V. Pictet
Date:
October 1991
Abstract:
The purpose of this paper is to suggest a new measure of trading model performance which accounts for the following requirements:
1. a high total return,
2. a smooth behavior around a straight line,
3. a small clustering of losses,
4. no bias towards low-frequency trading models.
It is important to define a value which describes the performance well in order to minimize the risk of over-fitting in the in-sample period and to be able to compare different trading models
with each other. In section 2 of this paper, we discuss the Sharpe index, a measure frequently used to evaluate portfolio models. We show that it does not account for all of the above requirements. In section 3, we propose a new measure based on a risk-averse trading profile and the utility function formalism of Keeney and Raiffa (1976). This measure is numerically more stable than the Sharpe index and exhibits fewer deficiencies. In section 4, this measure is extended to a multi-horizon measure in order to be able to account for the clustering of losses in the return curve. In the same section, some numerical aspects of the computation of this variable are discussed.
Unlike stocks, if you want to get more technical in the world of mutual funds, you will need to look at some key statistical data on the risk and return of funds that is not as accessible as performance data. Whether ou visit Morningstar.com or speak with any qualified financial advisor, you should be able to get this information. Translating this technical jargon into English isn't easy, but by using the Trimark Select Growth Fund as an example hopefully it will help you understand widely used mutual fund measures..
Uwe Schmock, RiskLab. Joint work with Daniel Straumann, RiskLab
Date:
October 1999
Abstract:
The allocation problem originated from an audit on RAC methods used by a large Swiss insurance company. Given risk bearing capital C>0 for a ?nancial institution,how to allocate it to business units for •measurement of risk contributions (for risk management), •performance measurement (for steering the company), •determination of bonuses for the management?
Hayne E. LelandHaas School of BusinessUniversity of California, Berkeley
Date:
October 1997
Abstract:
Most practitioners measure investment performance based on the CAPM, determining portfolio "alphas" or Sharpe Ratios. But the validity of this analysis rests on the validity of the CAPM, which assumes either normally distributed (and therefore symmetric) returns, or mean-variance preferences. Both assumptions are suspect: even if asset returns were normally distributed, the returns of options or dynamic strategies would not be. And investors distinguish upside from downside risks, implying skewness preference. This has led to the adoption of ad hoc criteria for measuring risk and performance, such as "Value at Risk" and the "Sortino Ratio."
We consider a world in which the market portfolio (but not necessarily individual securities) has identically and independently distributed (i.i.d.) returns. In this world the market portfolio will be mean-variance inefficient and the CAPM alpha will mismeasure the value added by investment managers. The problem is particularly severe for portfolios using options or dynamic strategies. Strategies purchasing (writing) fairly-priced options will be falsely accorded inferior (superior) performance using the CAPM alpha measure.
We show how a simple modification of the CAPM beta can lead to correct risk measurement for portfolios with arbitrary return distributions, and the resulting alphas of all fairly-priced options and/or dynamic strategies will be zero. We discuss extensions when the market portfolio is not assumed to be i.i.d.
Yong Bao - UC Riverside, Tae-Hwy Lee - UC Riverside, Burak Saltoglu - Marmara University
Date:
August 2003
Abstract:
We compare the predictive performance of various Value-at-Risk (VaR) models in several dimensions: (i) unfiltered VaR versus filtered VaR models; (ii) parametric distributions versus nonparametric distributions (estimated or simulated); (iii) conventional distributions versus extreme value distributions; and (iv) direct quantile modeling (the CaViaR models) versus inversion of the conditional distribution function. We apply these models to the stock markets of five Asian economies that su ?ered from the 1997-98 financial crisis and compare their predictive performance using the reality check test of White (2000). Two predictive likelihood functions for quantile forecasts and tail interval forecasts are used. We find that filtering is crucial in risk forecasting. Generally speaking, applying filtering to the extreme-value-theory-based models can produce better forecasts than conventional models and the CaViaR models.
Barra and Lipper joined forces to bring you a powerful mutual fund risk analysis tool, delivering the combined power of the industry leaders in sophisticated analysis of financial data…
The Morningstar Risk-Adjusted Return (MRAR) measure has the following characteristics:
1) no particular distribution of excess returns is assumed, 2) risk is penalized in all cases, and 3) the theoretical foundation is acceptable to sophisticated investors and investment analysts.
MRAR is motivated by expected utility theory, according to which an investor ranks alternative portfolios using the mathematical expectation of a function (called the utility function) of the ending value of each portfolio....
Michael K. Berkowitz & Jiaping Qiu, Univeristy of Toronto
Date:
February 2002
Abstract:
This paper compares the performance of mutual funds managed by publicly-traded management companies with those managed by private management companies. We find that publicly-traded
management companies invest in riskier assets and charge higher management fees relative to the funds managed by private management companies. At the same time, however, the risk-adjusted returns of the mutual funds managed by publicly-traded management companies do not appear to outperform those of the mutual funds managed by private management companies. This finding is consistent with both the risk reduction and agency cost arguments that have been made in the literature.
This third in a series of Research Notes on quantitative methods in asset management looks at measuring risk and performance. It is based on conversations with 36 persons responsible for risk and/or performance measurement from a representative sampling of asset management firms throughout Europe. It benefits from conversations with the industry for previous Research Notes* and with investment consultants, regulators and auditing firms. Highlights are summarised in the box below.
This fourth and final in a series of Research Notes on quantitative methods in asset management attempts to answer the question: Can we improve on today's modelling and if so, will this help generate superior returns? It is based on conversations with academics and suppliers of analytics on both sides of the Atlantic and comes after conversations with more than 100 persons from the European asset management community. Highlights are summarised in the box below.
Tom Fischer, Darmstadt University of Technology & Armin Roehrl, Approximity GMBH
Date:
October 2003
Abstract:
We explain how to optimize portfolios of bonds and stocks with respect to the Expected Shortfall (ES), respectively RORC or RORAC based on ES. In a pragmatic approach we combine and correlate a stock market model with geometric brownian motions with a two-factor Cox-Ingersoll-Ross (CIR-2) model for the interest rates/bonds. We use recent results from the theory of risk capital allocation, performance measurement and Swarm Intelligence for optimization. Examples for German market data as well as an analysis of the scalability of the solution to assure fast run-times on clusters of computers for large real-life portfolios are given.
Mutual funds are now the preferred way for individual investors and many institutions to participate in the capital markets, and their popularity has increased demand for evaluations of fund performance. Many business publications now rank mutual funds according to their performance, and information services exist specifically for this purpose. There is no general agreement, however, about how best to measure and compare fund performance and on what information funds should disclose to investors.
Risk and performance measurement is an active area for academic research and continues to be of vital interest to investors who need to make informed decisions and to mutual fund managers whose compensation is tied to performance. This article describes a number of performance measures. Their common feature is that they all measure funds? returns relative to risk. However, they differ in how they define and measure risk and, consequently, in how they define risk-adjusted performance. The author also compares rankings of a large sample of funds using two popular measures. She finds a surprisingly good agreement between the two measures for both stock and bond funds during the three-year period between 1995 and 1997.
One of the really fun things an investment advisor employing a multi-asset class strategy has to look forward to is the occasional reminder from a client that someone else is “doing it better” (thank God my wife isn’t a client). In most cases, the advisor doing it better has done so with a much more concentrated strategy that just happens to be in sync with current market trends. But the degree of concentration or even its relevance can get lost for obvious reasons. There is also the tendency to believe that the hot manager was in the right place at the right time by design—a belief that is usually easily dispelled with a little research....
Investors like to focus on the promise of high returns, but they should also ask how much risk they must assume in exchange for these returns. Although we often speak of risk in a general sense, there are also formal expressions of the risk-reward relationship. For example, the Sharpe ratio measures excess return per unit of risk, where risk is calculated as volatility, which is a traditional and popular risk measure. Its statistical properties are well known and it feeds into several frameworks, such as modern portfolio theory and the Black-Scholes model. In this article, we examine volatility in order to understand its uses and its limits...
Understanding Volatility Measurements of Mutual Funds
Author:
Shauna Croome
Date:
July 23rd, 2003
Abstract:
When considering a fund's volatility, an investor may find it difficult to decide which fund will provide the optimal risk-reward combination. Many websites provide various volatility measures for mutual funds free of charge; however, it can be hard to know not only what the figures mean but also how to read them. Furthermore, the relationship between these figures is not always obvious. Read on to learn about the four most common volatility measures and how they're applied in the type of risk analysis that is based on modern portfolio theory…
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