Reading PhD dissertations can be frustrating (lots of typos, jargon, etc.), but they can also be fascinating because they haven’t been “diluted” via the publishing process.
Here is a cool dissertation from an Ohio State Student:
This dissertation studies two distinct topics. First, I examine whether the idiosyncratic volatility discount anomaly documented by Ang, Hodrick, Xing, and Zhang (2006, 2009) is related to earnings shocks, and I find that a substantial portion of the idiosyncratic volatility discount can be explained by earnings momentum and post-formation earnings shocks. When these two effects are accounted for, idiosyncratic volatility has little, if any, return predictability. Second, I propose a parsimonious measure to characterize the severity of the microstructure noise at the individual stock level and assess the impact of this microstructure induced illiquidity on cross-sectional return predictability. One of the main advantages of this measure is that it is very simple to construct (requires only daily stock returns data). Using this measure I find that firms with the largest microstructure bias command a return premium as large as 9.61% per year, even after controlling for the premiums associated with size, book-to-market, momentum, and traditional liquidity price impact and cost measures. In addition, the bias premium is strongest among small, low price, volatile, and illiquid stocks. On the other hand, the premiums associated with size, illiquidity, and return reversal are most pronounced among stocks with the largest bias.
Go ahead and geek out–you know you want to!
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