Capturing hedge fund risk factor exposures: Hedge fund return replication with ETFs

We develop a new factor selection methodology of spanning the space of hedge fund risk factors with all available exchange traded funds (ETFs). We demonstrate the efficacy of the methodology with out-of-sample individual hedge fund return replication by ETF clone portfolios. This is consistent with our interpretation of ETF returns as proxies to risk factors driving hedge fund returns. We further consider portfolios of “cloneable” and “noncloneable” hedge funds, defined as top and bottom in-sample R² matches, and demonstrate that our ETF clone portfolios slightly outperform cloneable hedge funds out of sample.     

Use of active peer benchmarks in assessing UK mutual fund performance and performance persistence

The majority of UK style-specific mutual funds either report a broad market index as their prospectus benchmark or give no benchmark at all – a practice that may be (a) strategic, or (b) cultural and attributable to the lack of UK style-specific indices (e.g. mid-cap-growth, small-cap-value). The choice of a broad market index as a benchmark can bias the inferences of a fund’s performance and performance persistence. This study is the first to provide an alternative to style-specific indices in the UK, and suggests the use style-specific peer group benchmarks, following [Hunter, D., E. Kandel, S. Kandel, and R. Wermers. 2014. “Mutual Fund Performance Evaluation with Active Peer Benchmarks.” Journal of Financial Economics 112 (1): 1–29]. Our sample comprises of 817 active UK long-only equity mutual funds allocated to nine Morningstar style categories (peer groups) during the period 1992–2016. We show that the funds with the most significant positive peer-group-adjusted alphas continue to perform well one year ahead, in terms of both parametric and non-parametric measures of persistence in performance. Moreover, persistence in performance is driven by both winner and loser funds. The results within each peer group are by and large consistent with these findings.     

Model uncertainty,performance persistence and flows

Model uncertainty makes it difficult to draw clear inference about mutual fund performance persistence. I propose a new performance measure, Bayesian model averaged (BMA) alpha, which explicitly accounts for model uncertainty. Using BMA alphas, I find evidence of performance persistence in a large sample of US funds. There is a positive and asymmetric relation between flows and past BMA alphas, suggesting that fund investors respond to the information in BMA alphas. My findings are robust to various sensitivity analyses, including alternative measures of post-ranking performance, flows and total net assets, and alternative econometric model specifications.     

Reverse Survivorship Bias

Mutual funds often disappear following poor performance. When this poor performance is partly attributable to negative idiosyncratic shocks, funds' estimated alphas understate their true alphas. This paper estimates a structural model to correct for this bias. Although most funds still have negative alphas, they are not nearly as low as those suggested by the fund‐by‐fund regressions. Approximately 12% of funds have net four‐factor model alphas greater than 2% per year. All studies that run fund‐by‐fund regressions to draw inferences about the prevalence of skill among mutual fund managers are subject to reverse survivorship bias.     

The performance of long-serving fund managers

Apparently “there is no substitute for experience”. This and similar phrases are often heard in the worlds of politics, business, sport and others. It is the sort of proposition that makes sense to people. However, while the performance of actively managed funds has attracted a great deal of attention in the past, the performance of managers with long track records has attracted relatively little. In this paper we focus on managers with track records of at least ten years, that is, managers that have been the sole manager of a fund for at least a decade. We find that the average, net of fee, risk-adjusted performance of these managers over the ten years of our sample is attractive compared to similar values calculated for wider samples of the manager population. However, this result may be a reflection of survivorship bias, since we find little evidence of performance persistence from year to year amongst these managers, and evidence to suggest that risk-adjusted performance over the ten year sample period declined. However, for those investors that would still prefer to invest with an experienced fund manager, the disaggregated analysis in this paper reveals certain key traits that are related to positive risk-adjusted performance of long-serving managers, such as relatively low fund fees, more concentrated portfolios and a small cap style bias.     

A review of behavioural and management effects in mutual fund performance

This paper surveys and critically evaluates the literature on the role of management effects and fund characteristics in mutual fund performance. First, a brief overview of performance measures is provided. Second, empirical findings on the predictive power of fund characteristics in explaining future returns are discussed. Third, the paper reviews the literature on fund manager behavioural biases and the impact these have on risk taking and returns. Finally, the impact of organizational structure, governance and strategy on both fund risk taking and future performance is examined. While a number of surveys on mutual fund performance are available, these have not focused on the role of manager behavioural biases, manager characteristics and fund management strategic behavior on fund performance and risk taking. This review is an attempt to fill this gap. Empirical results indicate that finding successful funds ex-ante is extremely difficult, if not impossible. In contrast, there is strong evidence that poor performance persists for many of the prior “loser fractile” portfolios of funds. A number of manager behavioural biases are prevalent in the mutual fund industry and they generally detract from returns.     

Conditional performance evaluation for German equity mutual funds

We investigate the conditional performance of a sample of German equity mutual funds over the period from 1994 to 2003 using both the beta-pricing approach and the stochastic discount factor (SDF) framework. On average, mutual funds cannot generate excess returns relative to their benchmark that are large enough to cover their total expenses. Compared to unconditional alphas, fund performance sharply deteriorates when we measure conditional alphas. Given that stock returns are to some extent predictable based on publicly available information, conditional performance evaluation raises the benchmark for active fund managers because it gives them no credit for exploiting readily available information. Underperformance is more pronounced in the SDF framework than in beta-pricing models. The fund performance measures derived from alternative model specifications differ depending on the number of primitive assets taken to calibrate the SDF as well as the number of instrument variables used to scale assets and/or factors.     

Asset management and investment banking

We find evidence that conflicts of interest are pervasive in the asset management business owned by investment banks. Using data from 1990 to 2008, we compare the alphas of mutual funds, hedge funds, and institutional funds operated by investment banks and non-bank conglomerates. We find that, while no difference exists in performance by fund type, being owned by an investment bank reduces alphas by 46 basis points per year in our baseline model. Making lead loans increases alphas, but the dispersion of fees across portfolios decreases alphas. The economic loss is $4.9 billion per year.     

Of Tournaments and Temptations: An Analysis of Managerial Incentives in the Mutual Fund Industry

We test the hypothesis that when their compensation is linked to relative performance, managers of investment portfolios likely to end up as “losers” will manipulate fund risk differently than those managing portfolios likely to be “winners.” An empirical investigation of the performance of 334 growth-oriented mutual funds during 1976 to 1991 demonstrates that mid-year losers tend to increase fund volatility in the latter part of an annual assessment period to a greater extent than mid-year winners. Furthermore, we show that this effect became stronger as industry growth and investor awareness of fund performance increased over time.     

Style and performance of international socially responsible funds in Europe

This paper analyses the performance and investment styles of internationally oriented Socially Responsible Investment (SRI) funds, domiciled in eight European markets, in comparison with characteristics-matched conventional funds. To the best of our knowledge, this is the first multi-country study, focused on international SRI funds (investing in Global and in European equities), to combine the matched-pairs approach with the use of robust conditional multi-factor performance evaluation models, which allow for both time-varying alphas and betas and also control for home biases and spurious regression biases.In general, the results show that differences in the performance of international SRI funds and their conventional peers are not statistically significant. Regarding investment styles, SRI and conventional funds exhibit similar factor exposures in most cases. In addition, conventional benchmarks present a higher explaining power of SRI fund returns than SRI benchmarks. Our results also show significant differences in the investment styles of SRI funds according to whether they use “best-in-class” screening strategies or not. When compared to SRI funds that employ simple negative and/or positive screens, SRI “best-in-class” funds present significantly lower exposures to small caps and momentum strategies and significantly higher exposures to local stocks.     

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.     

The performance of enhanced-return index funds: evidence from bootstrap analysis

We apply the bootstrap technique proposed by Kosowski et al. [J. Finance, 2006, 61, 2551–2595] in conjunction with Carhart's [J. Finance, 1997, 52, 57–82] unconditional and Ferson and Schadt's [J. Finance, 1996, 51, 425–461] conditional four-factor models of performance to examine whether the performances of enhanced-return index funds over the 1996 to 2007 period are based on luck or superior ‘enhancing’ skills. The advantages of using the bootstrap to rank fund performance are many. It eliminates the need to specify the exact shape of the distribution from which returns are drawn and does not require estimating correlations between portfolio returns. It also eliminates the need to explicitly control for potential ‘data snooping’ biases that arise from an ex-post sort. Our results show evidence of enhanced-return index funds with positive and significant alphas after controlling for luck and sampling variability. The results are robust to both stock-only and derivative-enhanced index funds, although the spread of cross-sectional alphas for derivative-enhanced funds is slightly more pronounced. The study also examines various sub-periods within the sample horizon.     

Leading the herd: evidence from mutual funds’ buy and sell decisions

This article investigates whether a mutual fund’s performance is related to its herding behavior. Using the methodology of Sias (Rev Finance Stud 17:165–206, 2004), we develop a measure to capture the magnitude that a fund’s buy (sell) decisions are leading other funds’ buys (sells), and find that a fund’s performance is positively (negatively) related to its “buy leading” (“sell leading”). We interpret these findings as evidence that “buy leaders” (“sell leaders”)’ performance benefits (suffers) from the positive (negative) price effect associated with buy (sell) herds. Additionally, we find a positive relationship between fund performance and valuation-motivated “buy leading”, while we find weak evidence on the relationship between performance and valuation-motivated “sell leading”. We interpret these results as evidence that leading funds’ outperformance is due, in part, to their ability to value stocks.     

Investor learning and mutual fund family

In this paper we revisit the cross-fund learning method suggested by Jones and Shanken (2005) and construct a linear hierarchical model to consider the learning across funds within the fund family during the performance evaluation. We provide a full Bayesian treatment on all the factors of the pricing model and allow both the fund family and the individual manager to have dependent prior information regarding funds' alphas. The simulation results suggest that returns from peer funds within the family significantly affect investors' updating on fund alphas since the posterior distribution on fund alphas experiences a faster shrinkage than those reported in the previous literature. The model can also be simulated with specific prior belief on different factors of the pricing model, i.e. fund alphas, betas and factor loadings of each pricing benchmark, to better address the learning issue.     

Mutual fund performance with learning across funds

The average level and cross-sectional variability of fund alphas are estimated from a large sample of mutual funds. This information is incorporated, along with the usual regression estimate of alpha, in a (roughly) precision-weighted average measure of individual fund performance. Substantial “learning across funds” is documented, with significant effects on investment decisions. In a Bayesian framework, this form of learning is inconsistent with the assumption, made in the past literature, of prior independence across funds. Independence can be viewed as an extreme scenario in which the true cross-sectional distribution of alphas is presumed to be known a priori.     

The performance of US bond mutual funds

We evaluate the performance of the US bond mutual fund industry using a comprehensive sample of bond funds over a long time period from January 1998 to February 2017. In this one study, we examine bond fund selectivity, market timing and performance persistence. We evaluate bond funds relative to their self-declared benchmarks and in terms of both gross-of-fee returns and net-of-fee returns. We document considerable abnormal performance among funds both to the fund (gross returns) and to the investor (net returns). Bond fund performance is found to be superior in the post financial crisis period. However, past strong performance cannot be relied upon to predict future performance. Finally, while some funds exhibit market timing ability; we find a predominance of negative market timing among US bond mutual funds.     

European Mutual Fund Performance

This paper presents an overview of the European mutual fund industry and investigates mutual fund performance using a survivorship bias controlled sample of 506 funds from the five most important mutual fund countries. The latter is done using the Carhart (1997) 4-factor asset-pricing model. In addition we investigate whether European fund managers exhibit 'hot hands', persistence in performance. Finally the influence of fund characteristics on risk-adjusted performance is considered. Our overall results suggest that European mutual funds, and especially small cap funds are able to add value, as indicated by their positive after cost alphas. If we add back management fees, four out of five countries exhibit significant out-performance at an aggregate level. Finally, we detect strong persistence in mean returns for funds investing in the UK. Our results deviate from most US studies that argue mutual funds under-perform the market by the amount of expenses they charge.     

Hedge fund allocation: Evaluating parametric and nonparametric forecasts using alternative portfolio construction techniques

We propose a model for constructing Asian funds of hedge funds. We compare the accuracy of forecasts of hedge fund returns using an ordinary least squares (OLS) regression model, a nonparametric regression model, and a nonlinear nonparametric model. We backtest to assess these forecasts using three different portfolio construction processes: an “optimized” portfolio, an equally-weighted portfolio, and the Kelly criterion-based portfolio. We find that the Kelly criterion is a reasonable method for constructing a fund of hedge funds, producing better results than a basic optimization or an equally-weighted portfolio construction method. Our backtests also indicate that the nonparametric forecasts and the OLS forecasts produce similar performance at the hedge fund index level. At the individual fund level, our analysis indicates that the OLS forecasts produce higher directional accuracy than the nonparametric methods but the nonparametric methods produce more accurate forecasts than OLS. In backtests, the highest information ratio to predict hedge fund returns is obtained from a combination of the OLS regression with the Fung–Hsieh eight-factor variables as predictors using the Kelly criterion portfolio construction method. Similarly, the highest information ratio using forecasts generated from a combination of the nonparametric regression using the Fung–Hsieh eight-factor model variables is achieved using the Kelly criterion portfolio construction method. Simulations using risk-adjusted total returns indicate that the nonparametric regression model generates superior information ratios than the analogous backtest results using the OLS. However, the benefits of diversification plateau with portfolios of more than 20 hedge funds. These results generally hold with portfolio implementation lags up to 12 months.     

Asset allocation and portfolio performance: Evidence from university endowment funds

We use university endowment funds to study the relationship between asset allocation decisions and performance in multiple asset class portfolios. Although endowments differ substantially in asset class composition, policy portfolio returns and volatilities are remarkably similar across the sample. The risk-adjusted performance of the average endowment is negligible, but actively managed funds generate significantly larger alphas than passive ones. This is consistent with endowment managers exploiting their security selection abilities by over-weighting asset classes in which they have superior skills. Contrary to both theory and prevailing beliefs, asset allocation is not related to portfolio returns in the cross-section but does indirectly influence performance.     

UK equity mutual fund alphas make a comeback

In this study, we re-visit the performance of 887 active UK equity mutual funds using a new approach proposed by Angelidis, Giamouridis, and Tessaromatis. The authors argue that mutual funds stock selection is driven by the benchmark index, so if the benchmark generates alpha, there will be a bias in interpretation of manager's stock-picking ability. In their model, the alpha of a fund is adjusted by the benchmark's alpha. By applying this method, we eliminate bias inflicted by the persistently negative alphas of FTSE 100 Index in the period 1992–2013. We find that adjusted Fama–French and Carhat alphas of UK equity mutual funds are higher than those implied by the standard three- and four-factor models and are overall positive, contrary to most of the existing literature on UK fund performance. This result is consistent across funds' investment styles and robust to the use of FTSE Small Cap as benchmark for a sub-sample of small cap funds.