Date of Award
Doctor of Business Administration (DBA)
Economics and Finance
We test the cross-sectional relation between daily maximum return (MAX) and return in the following month for stocks with high and low idiosyncratic volatility. We use portfolio level analysis and firm-level cross-sectional regression to find that the negative and significant relation between MAX and expected stock return (known as the "MAX effect") is a non-January phenomenon observed predominantly on a sample of stocks with high idiosyncratic volatility. We find that the effect of investor sentiment on the MAX effect depends on arbitrage risk. Our findings suggest that arbitrageurs find it difficult to correct the mispricing of stocks with extreme positive return due to high idiosyncratic volatility, a support for the limits to arbitrage theory.
Tah, Kenneth A., "" (2015). Dissertation. 231.