Manipulation-proof Performance Measure Research Articles

Manipulation and performance persistence: an examination of Iranian equity mutual fund performance

PurposeThis paper aims to study manipulation and performance persistence in equity mutual funds. To this end, Manipulation-Proof Performance Measure (MPPM) and Doubt Ratio, along with a number of current performance measures are used to evaluate the performance of equity mutual funds in Iran.Design/methodology/approachThe authors investigate performance manipulation by 1) comparing the results of the MPPM with the current performance measures, 2) checking the Doubt Ratio to detect suspicious funds. Additionally, the authors investigate performance persistence by forming and evaluating portfolios of the equity mutual funds at several time horizons.FindingsThe authors conclude that there is no evidence of performance manipulation in the equity mutual funds. Additionally, when comparing the performance of the upper (top) tertile portfolios and the lower tertile portfolios, in all of the studied 1, 3, 6 and 12-month horizons, the authors find performance persistence in the equity mutual funds.Originality/valueTo the best of the authors’ knowledge, this research is the first study to investigate the performance manipulation in the Iranian equity mutual funds, and also is the first study in Iran that uses the MPPM and the Doubt Ratio in addition to a number of current performance measures to investigate the performance persistence in the equity mutual funds at several time horizons.

Manipulation-Proof Performance Measure and the Cost of Tail Risk

This paper builds on the seminal Goetzmann, Ingersoll, Spiegel and Welch research on Manipulation-Proof Performance Measures (MPPM), with a different purpose. Manipulation of usual performance measures generally goes through taking risk which is not reflected in the second moment measure of return distribution, variance or volatility. The MPPM corrects the impact of tail risk – negative skewness and kurtosis – taken by a fund manager (not necessarily with the explicit aim to manipulate the performance measures). In our paper, we try to quantify, using a Cornish Fisher technology allowing us to control for tail risk, the impact of such risk on the MPPM. In that framework, we find that the MPPM effectively does impose a penalty on tail risk. This penalty increases nearly linearly with return kurtosis and return negative skewness. The size of the penalty is rather benign when return volatility is low or the risk parameter is low. It increases substantially for high volatilities and/or high risk parameters.

Stochastic Dominance in Mutual Fund Returns

We find that a large portion of U.S. equity mutual funds almost second-order stochastically dominates the market portfolio. Consistent with the canonical definition of second-order stochastic dominance, both fund investors and managers reveal their preference for funds with a higher degree of almost second-order stochastic dominance through higher inflows and higher manager ownership. Funds with a higher degree of stochastic dominance over the market portfolio significantly outperform their peers, after controlling for common performance predictors and the Sharpe ratio. Inference based on stochastic dominance is more consistent with the Manipulation-Proof Performance Measure (MPPM) than with the Sharpe ratio.

Comparison of Manipulation-proof Measures on Hungarian Data

The further development of performance measures has managed to remedy some of the problems with earlier solutions, but with regard to the measures used most widely today, the issue of performance manipulation still needs to be tackled. This article presents the manipulation-proof performance measure (MPPM) developed by Ingersoll et al. (2007), which addresses this problem in a general sense. The MPPM used by Brown et al. (2010) is also detailed, along with the doubt ratio they developed, which can be used as a manipulation-detecting measure assessing implied risk aversion. With the calculations included here, this paper is one of the first to compare the MPPM and doubt ratio values calculated with the methods of the two groups of authors, seeking to explain the differences by using data from Hungarian absolute return funds as a sample. The results allow the author to be the first to propose the use of the more accurate MPPM formula of Ingersoll et al. (2007) both for performance measurement and calculation of the doubt ratio.

Representative Investors Versus Best Clienteles: Performance Evaluation Disagreement in Mutual Funds

This paper develops a diagnostic tool for candidate performance measures that accounts for investor disagreement in mutual funds. We compare the evaluation for best clienteles, specified by an upper admissible performance bound, to the one for representative investors implicit in twelve models. The results show that linear factor models misrepresent best clientele alphas, with a disagreement that relates to fund characteristics. Consumption-based alphas are generally inadmissible. The manipulation-proof performance measure generates alphas that are sensitive to its risk aversion parameter and lack statistical precision. However, a reasonable parameter gives admissible values that reflect the alphas for the most favorable clienteles.

Hedge Fund Flows and Name Gravitas

We document that investors allocate more flows to hedge funds whose names exhibit gravitas -defined as a combination of words from geopolitics and economics, or suggesting power. The economic effects are relatively large: averaging across our models, adding one more word with gravitas to the name of the average fund brings over $300,000 more in quarterly flows. We also document that having a name with gravitas is associated with abnormal negative performance: high name gravitas funds have lower returns, alphas, Sharpe ratios and manipulation-proof performance measures, higher volatilities and maximum drawdowns as well as higher probabilities of extinction than the funds with lower name gravitas. Although we find evidence that investors learn about the true investment abilities of their funds and respond less to gravitas as they do so, the gravitas-chasing behavior survives all these controls and totals more than 5% of the overall assets managed by hedge funds. From the point of view of hedge fund managers, we document that funds with more name gravitas report to fewer databases, suggesting that giving the fund a good name serves as an alternative form of marketing. Finally, we show that our results are robust to a generous battery of additional tests, including corrections for potential endogeneity issues or for whether the fund only accepts qualified investors.

In search for managerial skills beyond common performance measures

Abstract One caveat of current literature on the value of active management is the lack of treatment for the performance measures that can be gamed. We propose to use the performance measure that can’t be manipulated with respect to the underlying distribution, time variation, nor estimation error, (the manipulation-proof performance measure (MPPM, Goetzmann et al. (2007)), to rank all active U.S. domestic equity mutual funds from 1980 to 2013 on a quarterly basis to analyze managerial skills. We find fund managers in the higher ranked persistently outperform lower ranked managers by posting higher gross and net fund returns, higher holding-based returns, and generating positive return gap. Analyzing the holdings of the portfolios indicates higher ranked managers hold stocks with higher information asymmetry, especially the growth companies that are younger, smaller, and with lower liquidity. Our results show that the spread on gross and net fund returns between highest ranked and the lowest ranked fund managers is between 49 and 52 basis points per month. The holding returns are statistically significant for up to six months indicating the stock picking skills exist for those higher ranked managers. Even though MPPM identifies managerial skills, the positive alphas may not be warranted due to their operating expenses.

Value of hedge and expected returns

ABSTRACTWe demonstrate how it is possible to generate value for an investor with a hedge attached to the buy-and-hold strategy of an S&P 500 index fund. We study the S&P 500 index portfolio (not including dividends) and the value-weighted S&P 500 index portfolio (including dividends) of the Center for Research in Securities Prices for 1967:01–2011:12, using the capacity utilization and the unemployment rates in real time to determine if a hedge position should be initiated or closed. A hedge is initiated if the capacity utilization, the unemployment rate or a combination of the two signals a contraction in the real economy. The hedge position is closed if it signals otherwise an expansion. We use utility gains (Campbell and Thompson 2008), the manipulation-proof performance measure (MPPM) statistics (Ingersoll et al. 2007) and the P-Sharpe ratio (Bailey and López de Prado 2012) to evaluate the performance of a particular hedge strategy. The empirical results show that there are infinitely many hedges that can generate positive utility gains, higher MPPM statistics and higher P-Sharpe ratios.

Persistent Doubt: An Examination of Hedge Fund Performance

We examine whether performance persistence is suspicious. Top quintile portfolios formed on the Sharpe ratio, alpha, and information ratio persistently outperform similarly constructed mediocre third quintile portfolios throughout our sample period, but performance is more modest and less persistent when portfolios are formed on the excess manipulation-proof performance measure (EMPPM). By selecting funds formed on ranking by Sharpe and information ratios, investors also select funds that have persistently doubtful performance according to the doubt ratio. In contrast, portfolios formed on alphas and especially the EMPPM have much less excess and persistent doubt.

On the Managerial Skills of Mutual Fund Managers (Manipulation-Proof Performance Measure)

The on-going debate over whether fund managers have skills and whether those skills are short-lived is still inconclusive. Using the performance measure that can’t be manipulated with respect to the underlying distribution, time variation, nor estimation error, (the manipulation-proof performance measure (MPPM, Goetzmann et al. (2007)), we rank all U.S. domestic equity mutual funds from 1980 to 2013 on a quarterly basis and analyze their portfolio holdings to generate few insights. First, fund managers in the higher ranked MPPM deciles persistently outperform lower ranked managers by posting higher gross and net fund returns, higher holding-based returns, and generating positive return gap. Second, the characteristic of the holdings indicates higher ranked fund managers would hold younger, smaller, growth, and particularly stocks with lower liquidity and higher information asymmetry. Based on the five-factor (Fama and French (2014)) analysis, our results show that higher ranked managers could generate 15 to 29 basis points while lower ranked managers would loss 20 to 26 basis points on their risk-adjusted ex-post monthly holding returns (alphas) based on their ex-ante constructed holdings. Fourth, the differences on managers of the highest rank and the lowest rank result in monthly risk-adjusted returns (alphas) up to 49 to 52 basis points. Even though the managerial skills are identified at the higher ranked managers, the persistent and the predictability of their superior holding-based returns and fund returns are merely limited to up to six months. We conclude that even though higher ranked managers have better stock picking skills, their net fund returns are not large enough to offset their expenses to warrant positive alphas.

On Market Timing, Stock Picking, and Managerial Skills of Mutual Fund Managers with Manipulation-Proof Performance Measure

The on-going debate over whether fund managers have skills and whether those skills are short-lived is still inconclusive. Using the performance measure that can’t be manipulated with respect to the underlying distribution, time variation, nor estimation error, (the manipulation-proof performance measure (MPPM, Goetzmann et al. (2007)), we rank all U.S. domestic equity mutual funds from 1980 to 2012 on a quarterly basis and analyze their portfolio holding to contribute to the literature in two folds. First, managers ranked highest on MPPM in the current quarter earn largest fee-adjusted fund returns in the following quarter. Those managers hold younger, smaller, lower book-to-market, and momentum stocks. Second, taking long positions of the addition and short positions of the removal from their quarterly holdings from the highest ranked managers would outperform the lowest ranked managers by 12 basis points at the following quarter. Even though higher ranked managers have better stock picking skills, their fund returns are not large enough to offset their frequent transactions and higher expenses to insure positive alphas.

Term structure information and bond strategies

We examine term structure theories by using a novel approach. We form bond investment strategies based on different theories of the term structure in order to determine which strategy performs best. When using a manipulation-proof performance measure, we find that consistent with prior literature, an active strategy that is based on time varying term premiums can indeed form the basis of a successful bond strategy that outperforms an unbiased expectation inspired passive bond buy and hold strategy. This is true, however, for an earlier time period when the literature first made this claim. In a later time period, we find that the passive buy and hold strategy is significantly superior to all active strategies. This result is confirmed by statistical tests and it suggests that once it became known that an active strategy based on time varying term premiums could outperform a passive buy and hold strategy, the markets adjusted and arbitraged away this opportunity. Overall, it appears that the unbiased expectation hypothesis is the most likely explanation of the behaviour of the term structure during more recent times. This is because economically and statistically significant superior performance cannot be achieved if one uses information from the forward curve or the term structure as a guide to adjusting bond portfolios in response to changes in the term premium.

Performance Manipulation and Manipulation-Proof Performance Measures: An Empirical Study in US Mutual Fund Industry

Performance Manipulation and Manipulation-Proof Performance Measures: An Empirical Study in US Mutual Fund Industry

Yes, the choice of performance measure does matter for ranking of us mutual funds

ABSTRACTRecent literature in performance evaluation has focused on preferences and characteristics of returns' distribution that go beyond mean and variance world. However, Eling (2008) compared the Sharpe ratio with some of these performance measures, and found virtually identical rank ordering using mutual fund data. This paper compares 13 performance measures with the traditional Sharpe Ratio using a sample of US Fixed‐Income, Equity and Asset Allocation Mutual Funds. Results show that performance measures based on absolute reward‐risk ratios have similar rankings, when the numerator (mean excess return) is the same. However, when we move to other types of performances measures, results may be significantly different. This is the case of the Manipulation‐Proof Performance Measure (MPPM), Upside Potential Ratio, and Appraisal Ratio. Results are especially different for the MPPM. Robustness checks show that some of the performance measures are very sensitive to parameters' changes. Therefore, the choice of the performance measure is actually important for mutual fund ranking and selection. As a consequence, we argue that the use of several performance measures and rankings have a positive impact on the mutual fund's industry, reducing concentration. Copyright © 2011 John Wiley & Sons, Ltd.

Do the Best Hedge Funds Hedge?

We provide a simple argument that suggests that better-informed hedge funds choose to have less exposure to factor risk. Consistent with this argument, we find that hedge funds that exhibit lower R-squareds with respect to systematic factors have higher Sharpe ratios, higher information ratios, and higher alphas. They also exhibit higher manipulation-proof performance measures and charge higher fees. The Author 2010. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.

Resisting the Manipulation of Performance Metrics: An Empirical Analysis of The Manipulation-Proof Performance Measure

Performance manipulation can make a fund more attractive to investors and, more seriously, managers can intentionally misreport returns to enhance performance scores. This paper empirically investigates whether the manipulation-proof performance measure derived by Goetzmann et al. (2007) really is impervious to performance anipulation, using TASS hedge fund data, which have very skewed and fat-tailed return distributions. This article determines that the MPPM can evaluate performance more correctly than other measures. At application level, we propose the Doubt Ratio (DR), a new simple measure to detect funds that might have been manipulated or whose returns were intentionally smoothed, as in Madoff’s case. Our findings will help investors select funds and financial supervisors filter out funds for further investigation.

Yes, the Choice of Performance Measure Does Matter for Ranking of US Mutual Funds

Recent literature in performance evaluation has focused on preferences and characteristics of returns’ distribution that go beyond mean and variance world. However, Eling (2008) compared the Sharpe ratio with some of these performance measures, and found virtually identical rank ordering using mutual fund data. This paper compares 13 performance measures with the traditional Sharpe Ratio using a sample of US Fixed-Income, Equity and Asset Allocation Mutual Funds. Results show that performance measures based on absolute reward-risk ratios have similar rankings, when the numerator (mean excess return) is the same. However, when we move to other types of performances measures, results may be significantly different. This is the case of the MPPM (Manipulation-proof Performance Measure), Upside Potential Ratio, Appraisal Ratio. Results are especially different for the MPPM. Robustness checks show that some of the performance measures are very sensitive to parameters’ changes. Therefore, the choice of the performance measure is actually important for mutual fund ranking and selection.

Manipulation-Proof Performance Evaluation of Brazilian Fixed Income and Multimarket Funds

Traditional performance measures are based on the mean-variance framework. Emerging literature in performance evaluation is concerned with other moments of returns' distribution and also to avoid manipulation of performance measures by portfolio managers. This paper compares two performance measures: the traditional Sharpe Ratio and a recently proposed measure, the Manipulation-Proof Performance Measure (MPPM) using a sample of Brazilian Fixed Income and Multimarkets funds. We found a low rank correlation between MPPM and Sharpe Ratio. The Top Funds' Lists of the two measures reveals that very few funds are present on both lists. Furthermore, data shows low risk-adjusted performance persistence over time, especially for Multimarkets, and when using a short-time interval.

Portfolio Performance Manipulation and Manipulation-proof Performance Measures

Numerous measures have been proposed to gauge the performance of active management. Unfortunately, these measures can be gamed. Our article shows that gaming can have a substantial impact on popular measures even in the presence of high transactions costs. Our article shows there are conditions under which a manipulation-proof measure exists and fully characterizes it. This measure looks like the average of a power utility function, calculated over the return history. The case for using our alternative ranking metric is particularly compelling for hedge funds whose use of derivatives is unconstrained and whose managers' compensation itself induces a nonlinear payoff.