Do Hedge Funds Frontrun Mutual Funds?

/Do Hedge Funds Frontrun Mutual Funds?

Do Hedge Funds Frontrun Mutual Funds?

By | 2017-08-18T17:06:20+00:00 June 5th, 2014|Research Insights|2 Comments

Are Mutual Funds Sitting Ducks?

Abstract:

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.

Alpha Highlight:

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.

 

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

The results are hypothetical results and are NOT an indicator of future results and do NOT represent returns that any investor actually attained. Indexes are unmanaged, do not reflect management or trading fees, and one cannot invest directly in an index. Additional information regarding the construction of these results is available upon request.

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.

Comments:

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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About the Author:

Wes Gray
After serving as a Captain in the United States Marine Corps, Dr. Gray earned a PhD, and worked as a finance professor at Drexel University. Dr. Gray’s interest in bridging the research gap between academia and industry led him to found Alpha Architect, an asset management that delivers affordable active exposures for tax-sensitive investors. Dr. Gray has published four books and a number of academic articles. Wes is a regular contributor to multiple industry outlets, to include the following: Wall Street Journal, Forbes, ETF.com, and the CFA Institute. Dr. Gray earned an MBA and a PhD in finance from the University of Chicago and graduated magna cum laude with a BS from The Wharton School of the University of Pennsylvania.

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