Are Mutual Funds Sitting Ducks?
- S. Shive and H. Yun
- A version of the paper can be found here.
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We find that patient traders profit from the predictable, flow-induced trades of mutual funds. In anticipation of a 1%-of-volume change in mutual fund flows into a stock next quarter, the institutions in the same 13F category as hedge funds trade 0.31-0.45% of volume in the current quarter. A third of the trading is associated with the subset of 504 identified hedge funds. The effect is stronger when quarterly mutual fund portfolio disclosure is required and among hedge funds with more patient capital. A one standard deviation higher measure of anticipatory trading by a hedge fund is associated with a 0.9% higher annualized four-factor alpha. A one standard deviation higher measure of anticipation of a mutual fund’s trades by institutions is associated with a 0.07-0.15% lower annualized four-factor alpha. The effect is stronger for more constrained mutual funds.
The authors claim the following result:
Using past work as a guide, our prediction model uses lagged ﬂows and mutual fund returns as predictors and the fact that mutual funds tend to scale their existing portfolios up or down in response to ﬂows. We ﬁnd that in anticipation of a 1% of volume change in mutual ﬂows into a stock, hedge funds put on trades worth 0.18-0.25% of volume. This type of anticipatory trading by hedge funds is stronger in smaller, less liquid stocks…we show that hedge funds proﬁt from this type of trading: a one standard deviation difference in hedge fund beta (with respect to predicted mutual fund ﬂow) is associated with a 0.53% annualized difference in hedge fund excess return.
They first highlight that mutual fund trades become more predictable post-2002–notice how the circles stabilize. This more reliable predictability facilitates exploitation by smart investors.
I’ll spare you the details from Table 3, which highlight the statistics behind the authors claim. Instead, I’ll quote the interpretation of the results from the paper:
The results in the 2003-2010 data are economically as well as statistically signiﬁcant. A 1% of volume diﬀerence in predicted aggregate mutual fund ﬂows into a stock is associated with roughly a 0.00344*0.01 = 0.0000344 proportion of quarterly volume traded by each institution in the prior quarter. Multiplying this by the average number of funds trading each stock in each quarter, 52, yields 0.18% of quarterly volume on average per stock. Summing the institutional trades by stock removes some noise, as shown in the last column of Table 3, Panel A. A 1% of volume diﬀerence in predicted aggregate mutual fund ﬂows is associated with a 0.01*0.255=0.00255 or 0.25% of volume in anticipatory trading by institutions.
An interesting attempt at identifying if “smart” money exploits the predictability of mutual fund flows. I’m skeptical of the results because of the empirical challenges associated with the question the authors are trying to address. That said, I think this is a commendable attempt at addressing an interesting question.
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