The effect of arbitrage activity in low volatility strategies : an empirical analysis of return comovements

Abstract

The goal of this thesis is to examine the effect arbitrageurs have on prices in the stock market. More specifically, we seek to investigate arbitrage activity in the low volatility anomaly by decomposing it into systematic- and firm-specific parts. Our main contribution is to create a measure of arbitrage activity for the idiosyncratic volatility strategy, which goes long stocks with low idiosyncratic- and short stocks with high idiosyncratic volatility. We fulfil this by mainly utilizing previous methodology of Ang et al. (2006), Lou and Polk (2013) and Huang et al. (2016). First, for a proof that we are able to construct our own measure of arbitrage activity in low volatility strategies, we implement the methodology of Huang et al. (2016) and successfully replicate CoBAR, a measure of arbitrage activity in beta-strategies. We then proceed by creating our own measure of arbitrage activity in the idiosyncratic volatility strategy, which we dub CoIVOL. This proxy is used to identify periods of relatively low and high arbitrage activity and asses whether trading in the strategy is crowded. We use this to examine the implications and effects arbitrageurs have on prices. Our findings indicate that abnormal returns to the idiosyncratic volatility strategy, conditional on the arbitrage activity, are decreasing with time and activity. More specifically, we find that when activity is at its lowest, we achieve an average alpha of 1.71%/month for the first six months after portfolio formation. This alpha decreases monotonically with activity, and eventually becomes insignificant when arbitrage activity peaks. We conclude that arbitrageurs exploiting the idiosyncratic volatility anomaly has a stabilizing effect on prices.