Revisiting mutual fund performance evaluation

Mutual fund manager excess performance should be measured relative to their self-reported benchmark rather than the return of a passive portfolio with the same risk characteristics. Ignoring the self-reported benchmark results in different measurement of stock selection and timing components of excess performance. We revisit baseline empirical evidence fund performance evaluation utilizing stock selection and timing measures that incorporate the self-reported benchmark. We introduce a new factor exposure based approach for measuring the – static and dynamic – timing capabilities of mutual fund managers. We overall conclude that current studies are likely to be misstating skill because they ignore the managers’ self-reported benchmark in the performance evaluation process.     

Do funds selected by managers’ skills perform better?

We construct a simple intuitive rating mechanism to evaluate stock picking and market timing skills of equity and hybrid equity fund managers in China. We find that both our skill-rated 5-star (SR-5S) fund and the Morningstar 5-star (MS-5S) fund portfolios outperform the market. The SR-5S fund portfolio outperforms its counterpart MS-5S portfolio in most situations, depending on whether portfolio performance is measured by the abnormal returns of the CAPM model, the Fama-French three-factor (FF3) model, the Carhart four-factor (CH4) model and the Fama-French five-factor (FF5) model. Both market timing skill and stock picking skill affect the performance difference between the SR-5S fund and MS-5S fund portfolios. Additionally, the departure of a SR-5S or MS-5S fund manager is associated with fund performance declines, and the declines in performance for SR-5S funds are generally larger than the declines for the MS-5S funds.     

Rating mutual funds: Construction and information content of an investor-cost based rating of Danish mutual funds

We develop a new rating of mutual funds: the atpRating. The atpRating assigns crowns to each individual mutual fund based upon the costs an investor pays when investing in the fund in relation to what it would cost to invest in the fund's peers. Within each investment category, the rating assigns five crowns to funds with the lowest costs and one crown to funds with the highest costs.We investigate the ability of the atpRating to predict the future performance of a fund. We find that an investor who has invested in the funds with the lowest costs within an investment category would have obtained a risk-adjusted excess return that is approximately 3–4 percentage points higher per annum than if the funds with the highest costs had been invested in.We compare the atpRating with the Morningstar Rating. We show that one reason why the atpRating and the Morningstar Rating contain different information is that the returns Morningstar uses as inputs when rating funds are highly volatile whereas the costs the atpRating uses as inputs when rating funds are highly persistent. In other words, a fund that has low costs one year will most likely also have low costs the following year, whereas the return of a fund in a certain year generally contains only little information about the future return that the fund will generate.Finally, we have information on the investments in different mutual funds made by a small subgroup of investors known to have been exposed to both the atpRating and the Morningstar Rating. We find that investors have clear preferences for funds rated high by both the atpRating and the Morningstar Rating.     

Performance attribution of mutual funds in India: outperformance or mis‐representation?

We conduct a novel holdings‐based performance attribution, particularly suited to emerging markets, for equity‐oriented active mutual funds in India. Although, we find significantly positive alphas for an average fund, the stated benchmarks are grossly mis‐specified. A style‐adjusted benchmark could beat the stated benchmarks by greater margins than the funds themselves. While funds’ trading activity consistently adds value, cash drag and market timing usually diminish value. Although, the best‐performing funds exhibit superior security selection abilities, their outperformance does not persist. However, despite the lack of persistence winner funds continue to generate significantly higher alphas than loser funds for quite some time.     

中国基金业业绩持续性问题研究：基于羊群行为的分析

以2005～2010年上半年开放式股票型基金为样本,从羊群行为角度考量开放式股票型基金业绩持续性。结果表明,基金卖出股票羊群行为强于买入股票羊群行为,且没有证据表明我国基金有联手坐庄行为。相对于输者组合,赢者组合在卖出价格下跌股票时行为更加趋同,且受市场行情影响较小,这与其业绩压力和研究能力有关。     

Australian retail fund performance persistence

The present study extends the Australian fund performance persistence literature through the use of five performance metrics: raw returns, the Sharpe ratio, the single‐factor model and two multifactor models, the Carhart (1997) model and the Gruber (1996) model, in analysis of Australian retail fund performance over the period 1991–2000. Analysis suggests that performance persistence is sensitive to fund objective and appears to be driven by inadequate adjustment for risk.     

The Euro and inflation uncertainty in the European Monetary Union

This paper adopts a time-varying GARCH framework to estimate short-run and steady-state inflation uncertainty in 12 EMU countries, and then investigates their relationship with inflation. The effects of the Euro introduction in 1999 are examined by utilising a dummy variable. Tests for endogenously determined breaks are also employed. We find a considerable degree of heterogeneity across EMU countries in terms of average inflation, its degree of persistence, and both types of uncertainty, whilst the trend component of inflation is generally decreasing. Various breaks in the relationship between inflation and inflation uncertainty are found, frequently well before the Euro introduction.     

How to measure mutual fund performance: economic versus statistical relevance

In the present paper a comprehensive assessment of existing mutual fund performance models is presented. Using a survivor‐bias free database of all US mutual funds, we explore the added value of introducing extra variables such as size, book‐to‐market, momentum and a bond index. In addition to that we evaluate the use of introducing time‐variation in betas and alpha. The search for the most suitable model to measure mutual fund performance will be addressed along two lines. First, we are interested in the statistical significance of adding more factors to the single factor model. Second, we focus on the economic importance of more elaborate model specifications. The added value of the present study lies both in the step‐wise process of identifying relevant factors, and the use of a rich US mutual fund database that was recently released by the Center for Research in Security Prices.     

Why mutual funds “underperform”

I propose a parsimonious model that reproduces the negative risk-adjusted performance of actively managed equity mutual funds. In the model, a fund manager can generate state-dependent active returns at a disutility. Negative expected performance and mutual fund investing simultaneously arise in equilibrium because the active return the fund manager generates covaries positively with a component of the pricing kernel that the performance measure omits, consistent with recent empirical evidence. Using data on U.S. funds, I also document new empirical evidence consistent with the model's cross-sectional implications.     

Attribution of investment performance: an analysis of Australian pooled superannuation funds*

This paper evaluates the market timing and security selection capabilities of Australian pooled superannuation funds over the eight‐year period from January 1991 to December 1998. Evaluation of both components of investment performance is surprisingly scarce in the Australian literature despite active investment managers engaging in both market timing and security selection. The paper also evaluates performance for the three largest asset classes within diversified superannuation funds and their contribution to overall portfolio return. The importance of an accurately specified market portfolio proxy in the measurement of investment performance is demonstrated. This paper employs performance benchmarks that account for the multi‐sector investment decisions of active investment managers in a manner that is consistent with their unique investment strategy. Consistent with U.S. literature, the empirical results indicate that Australian pooled superannuation funds do not exhibit significantly positive security selection or market timing skill.     

Attribution of investment performance: an analysis of Australian pooled superannuation funds*

This paper evaluates the market timing and security selection capabilities of Australian pooled superannuation funds over the eight‐year period from January 1991 to December 1998. Evaluation of both components of investment performance is surprisingly scarce in the Australian literature despite active investment managers engaging in both market timing and security selection. The paper also evaluates performance for the three largest asset classes within diversified superannuation funds and their contribution to overall portfolio return. The importance of an accurately specified market portfolio proxy in the measurement of investment performance is demonstrated. This paper employs performance benchmarks that account for the multi‐sector investment decisions of active investment managers in a manner that is consistent with their unique investment strategy. Consistent with U.S. literature, the empirical results indicate that Australian pooled superannuation funds do not exhibit significantly positive security selection or market timing skill.     

Inflation persistence: Alternative interpretations and policy implications

In this paper, I consider the policy implications of two alternative structural interpretations of observed inflation persistence, which correspond to two alternative specifications of the new Keynesian Phillips curve (NKPC). The first specification allows for some degree of intrinsic persistence by way of a lagged inflation term in the NKPC. The second is a purely forward-looking model, in which expectations farther into the future matter and coefficients are time-varying. In this specification, most of the observed inflation persistence is attributed to fluctuations in the underlying inflation trend, which are a consequence of monetary policy rather than a structural feature of the economy. With a simple quantitative exercise, I illustrate the consequences of implementing monetary policy, assuming a degree of intrinsic persistence that differs from the true one. The results suggest that the costs of implementing a stabilization policy when the policymaker overestimates the degree of intrinsic persistence are potentially higher than the costs of ignoring actual structural persistence; the result is more clear-cut when the policymaker minimizes a welfare-based loss function.