An Up-and-Coming Behavioral Finance Pro: Casey Dougal, Ph.D.
We are proud to welcome Casey Dougal, Ph.D. to our advisory team. We were colleagues at Drexel and after engaging in multiple discussions on research and new ideas, we decided to formalize the relationship.
Many of you are already familiar with his work, since we’ve highlighted his compelling behavioral finance paper on anchoring in credit markets.
Dr. Dougal’s research interests revolves around behavioral finance (our favorite!). Specifically, one of his overarching research themes is documenting an individual’s ability to influence asset prices. Many of his findings are contrary to the underlying assumption of the efficient market hypothesis, which assumes there are hyper-rational resource-heavy arbitrage traders that force prices to be correct at all times.
The following three papers are a sample of Casey Dougal’s work:
- Joint with Joey Engelberg, Diego Garcia and Chris Parsons
- Review of Financial Studies (2012), RFS Best Paper Award (1st Prize)
From 1970 to 2007, we find that the short-term returns on the Dow Jones Industrial Average (DJIA) can be predicted knowing only the author of the Wall Street Journal’s “Abreast of the Market” column, a widely read market summary article. This is surprising because, both the nature of the article – a summary of the previous day’s market performance – and the unlikelihood that individual columnists consistently possess information advantages relative to the market as a whole suggests that the return predictability is related to specific author’s ability to spin public information. Importantly, because journalist writing schedules are randomly assigned (i.e., who writes each day is independent of current market returns), the observed predictability is necessarily due to journalists’ writings causally influencing aggregate market prices, rather than simply reflecting current market conditions.
- Joint with Joey Engelberg, Chris Parsons and Ed Van Wesep
- Journal of Finance (2015)
We find that when a firm borrows in the syndicated loan market, the spread it receives on its current loan reflects the spread it received on its most recent past loan. This is surprising since, generally, both the credit quality of the firm and market conditions have changed in the interim and subsequently past spreads should be irrelevant reference points for future transactions. The evidence suggests that borrowers and lenders are subject to the behavioral bias of “anchoring” (Tversky and Kahneman ).
What’s in a (school) name? Racial discrimination in higher education bond markets
- Joint with Pengjie Gao, William Mayew, and Chris Parsons
- Working Paper
We find that historically black colleges and universities (HBCUs) pay 15-30 basis points more in underwriting fees when issuing tax-exempt bonds, compared to similar, non-HBCU schools. Differential credit risk provides a poor account of these patterns. For example, identical differences are observed between HBCU and non-HBCU bonds: 1) having AAA credit ratings, and 2) insured by the same company (even prior to the Financial Crisis). The HBCU effect is three times larger in the Deep South, where anti-Black racial animus has historically been the strongest. HBCU-issued bonds are also more expensive to trade in the secondary market.
He also have a strand of research that looks at the influence of firm location on firm performance.
- Joint with Chris Parsons and Sheridan Titman
- Journal of Finance (2015)
We find that a firm’s investment is highly sensitive to the investments of other firms headquartered nearby, even those in very different industries. A firm’s investment also responds to fluctuations in the cash flows and stock prices (q) of local firms outside its sector. These patterns do not appear to reflect exogenous area shocks such as local shocks to labor or real estate values, but rather suggest that local agglomeration economies are important determinants of firm investment and growth.
- Working Paper
I find that growth in local proprietary income (i.e., small business income) is positively correlated with the future stock returns and fundamentals of public firms headquartered nearby. This predictability is strongest for public firms in high-tech industries, for young firms, and when proprietor financial constraints are relaxed as measured by changes in local housing prices. Proprietary income growth also predicts aggregate stock prices. There exists a common proprietary income growth factor across economic regions which pro-cyclically predicts aggregate market returns. This factor is highly correlated with the Silicon Valley proprietary income growth rate—which itself is a stronger predictor of aggregate returns than the dividend yield or CAY. These results are consistent with small businesses reacting faster than large firms to economic fluctuations, especially those driven by the introduction of new technologies.
Some highlights on Prof. Dougal:
- He learned how to arbitrage on the rough and tumble playground in his hometown of Caldwell, Idaho. (read the story)
- B.S. in mathematics from Brigham Young University
- M.A. in Economics from the University of Chicago
- Ph.D. in finance from the University of North Carolina
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