Abstract
We develop a novel methodology to infer the amount of capital allocated to quantitative equity arbitrage strategies. Using this methodology, which exploits time-variation in the cross-section of short interest, we document that the amount of capital devoted to value and momentum strategies has grown significantly since the late 1980s. We provide evidence that this increase in capital has resulted in lower strategy returns. However, consistent with theories of limited arbitrage, we show that strategy-level capital flows are influenced by past strategy returns and strategy return volatility and that arbitrage capital is most limited during times when strategies perform best. This suggests that the growth of arbitrage capital may not completely eliminate returns to these strategies. (JEL G02, G12, G14, G23)
Highlights
We develop a novel methodology to infer the amount of capital allocated to quantitative equity arbitrage strategies
We provide evidence that the increasing level of arbitrage capital has been associated with a reduction in the returns that these anomaly strategies deliver
S t and ts measures have units of basis points of short interest. These are natural economic units as they inherit the units of short interest, expressing the amount of arbitrage capital allocated to a given equity anomaly strategy as a fraction of the total market value of the stocks in that strategy’s portfolio
Summary
4: Our cross-sectional regression-based measures of arbitrage capital should negatively forecast long-short anomaly returns in the time series. The expected returns on a long-short strategy using signal it are lower when more arbitrage capital is devoted to the signal. When there are more short-sellers using the signal, they arbitrage away more of the mispricing at time t, so there is less return predictability at t + 1. Because Result 3 shows that we can recover the amount of arbitrage capital from cross-sectional short interest regressions, Result 4 follows naturally. 1.2 Testable predictions The model provides formal motivation for our measure of arbitrage capital. We review the literature on the evolution and limits of arbitrage to develop the full set of testable asset-pricing predictions, which we will take to the data
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