Academic journal article Financial Management

Is Timing Everything? the Value of Mutual Fund Manager Trades

Academic journal article Financial Management

Is Timing Everything? the Value of Mutual Fund Manager Trades

Article excerpt

I develop new measures of the value of active mutual fund management using portfolio holdings. These measures simultaneously test for trading and selection skill within stocks, industries, and characteristics. I demonstrate that most of the skill documented in prior studies comes from correctly trading stocks within industries, though funds also have some skill in timing industries. However, prior research focuses on the period 1980-1994. I also test the hold out sample 1995-2007. Contrary to prior results, the latter period (and the full sample) demonstrates that mutual funds generate no excess returns from any category of skill.


The mutual fund literature examining the trading behavior of mutual funds documents skill in gross returns (Chen, Jegadeesh, and Wermers, 2000). Mutual fund buys outperform sells, and gross returns demonstrate positive excess returns. Therefore, fund managers are viewed as having some stock trading ability prior to expenses. What is less clear is the source of manager skill. I contribute to the literature on mutual fund performance by simultaneously testing for skill in a united framework of performance measures that control for both selection and trading ability. My measures decompose returns into two broad components. The trading component measures the additional return gained or lost through changing the portfolio and captures the value created by the short run anticipation of returns. The selection component measures how long-term holdings would have created value. A manager with selection ability creates value by tending to hold stocks that outperform over a longer period. The selection and trading components are not mutually exclusive and a fund may benefit from both.

My measures also test for multiple sources of skill within the trading and selection components. Prior research confirms skill in areas as diverse as market timing, anticipating individual stock news, and industry selection, but few studies control for multiple sources simultaneously. For example, Daniel et al. (1997) only test for trading skill in broad characteristics, while Kacperczyk, Sialm, and Zheng (2005) only allow for timing in industries. Chen et al. (2000) test for individual stock timing for the whole industry, but do not control for other forms of timing. In contrast, my measures allow researchers to isolate selection and trading skill in all three areas: 1) individual stocks, 2) industries, and 3) characteristic styles.

I apply these measures to mutual fund holdings from 1980 to 2007. I confirm that mutual funds demonstrate little trading ability with respect to individual stocks, industries, or characteristics. The funds do show some economically large stock selection ability, though most specifications do not reach conventional levels of statistical significance. Stock selection skill within industries is present from 1980 to 2007, but the measures are noisy and sensitive to timeframe. I conclude that industry expertise provides, at best, only modest benefits to the average mutual fund over the full sample.

My second contribution to the literature stems from the prior finding that excess returns can be attributed, in part, to timeframe. Daniel et al. (1997) find economically and statistically large excess returns for the shorter period of 1975-1994. I confirm that mutual funds generated excess returns over a similar period and that these excess returns come from stock trading (as suggested in Chen et al., 2000). The following thirteen years (1995-2007), however, indicate small losses from trading. Looking at the overall timeframe (1980-2007), the gains from trading are inconsistent through time and close to zero, on average.

My finding of small gains from industry expertise differs from Kacperczyk, Sialm, and Zheng (2005). Kacperczyk et al. (2005) find that funds with higher industry concentrations have higher excess returns and suggest that industry expertise may generate value. …

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