Dissertation Dumpster Diving: Cross Section of Stock Returns

Dissertation Dumpster Diving: Cross Section of Stock Returns

March 15, 2014 Uncategorized
Print Friendly
(Last Updated On: March 8, 2014)

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!


Note: This site provides no information on our value investing ETFs or our momentum investing ETFs. Please refer to this site.


Join thousands of other readers and subscribe to our blog.


Please remember that past performance is not an indicator of future results. Please read our full disclaimer. The views and opinions expressed herein are those of the author and do not necessarily reflect the views of Alpha Architect, its affiliates or its employees. This material has been provided to you solely for information and educational purposes and does not constitute an offer or solicitation of an offer or any advice or recommendation to purchase any securities or other financial instruments and may not be construed as such. The factual information set forth herein has been obtained or derived from sources believed by the author and Alpha Architect to be reliable but it is not necessarily all-inclusive and is not guaranteed as to its accuracy and is not to be regarded as a representation or warranty, express or implied, as to the information’s accuracy or completeness, nor should the attached information serve as the basis of any investment decision. No part of this material may be reproduced in any form, or referred to in any other publication, without express written permission from Alpha Architect.


Definitions of common statistics used in our analysis are available here (towards the bottom)




About the Author

Wesley R. Gray, Ph.D.

After serving as a Captain in the United States Marine Corps, Dr. Gray received a PhD, and was a finance professor at Drexel University. Dr. Gray’s interest in entrepreneurship and behavioral finance led him to found Alpha Architect. Dr. Gray has published three books: EMBEDDED: A Marine Corps Adviser Inside the Iraqi Army, QUANTITATIVE VALUE: A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors, and DIY FINANCIAL ADVISOR: A Simple Solution to Build and Protect Your Wealth. His numerous published works has been highlighted on CBNC, CNN, NPR, Motley Fool, WSJ Market Watch, CFA Institute, Institutional Investor, and CBS News. 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.