An Up-and-Coming Behavioral Finance Pro: Casey Dougal, Ph.D.

/An Up-and-Coming Behavioral Finance Pro: Casey Dougal, Ph.D.

An Up-and-Coming Behavioral Finance Pro: Casey Dougal, Ph.D.

By | 2017-08-18T17:10:34+00:00 August 14th, 2015|Business Updates|5 Comments

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:

Journalists and the Stock Market

  • 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.

Anchoring on Credit Spreads

  • 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 [1974]).

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.

Urban Vibrancy and Corporate Growth

  • 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.

Small Business Performance and Stock Return Predictability

  • 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

casey dougal

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About the Author:

Wes Gray
After serving as a Captain in the United States Marine Corps, Dr. Gray earned a PhD, and worked as a finance professor at Drexel University. Dr. Gray’s interest in bridging the research gap between academia and industry led him to found Alpha Architect, an asset management that delivers affordable active exposures for tax-sensitive investors. Dr. Gray has published four books and a number of academic articles. Wes is a regular contributor to multiple industry outlets, to include the following: Wall Street Journal, Forbes,, and the CFA Institute. 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.
  • sixchickensleft

    The notion that racial discrimination in higher ed bond markets is CRAP and is the antithesis of what it means to be a value investor. If the additional basis points were due to racial animus rather than actuarial differences in credit risk, some actor would discover this and eventually arbitrage the difference away……or do you have some other fundamental understanding of how value investors expect their stocks to ultimately reward them.

    Sorry, I realize that you (Wes) didn’t author the paper, but this politically correct crap has permeated our universities beyond belief. Dr. Dougal’s certificate – I can’t bring myself to use the term “education” – from Chapel Hill explains his sad and unfortunate Progressive indoctrination. If Professor Dougal really believes that credit markets have discriminated against black colleges because of racial animus rather than some rational (while perhaps incorrect) belief in their credit risk, perhaps he should put his money where his mouth is and take financial advantage of this price imbalance.

  • Sixchickens, thanks for the comments…

    I sat down with Casey when he was drafting up a super early draft of that paper. The hypothesis is certainly controversial! I had many of the same reservations you did when we had our initial discussions.

    re results/abstract: I have not seen the latest version of the paper or assessed the validity of the tests, so I can’t really comment on his conclusions…

    I’ll step aside as the messenger and leave the defense of the work to Casey…

  • Casey Dougal

    We have not yet posted a draft of our HBCU paper online. However, here are a few points to think about:

    1. Far from being driven by progressive ideals, the initial impetus for our paper came from discussions with a VP in fixed income from a major investment bank who has personally traded over 6.5 billion in par value with a focus on colleges and universities. This person suggested that bonds issued by HBCUs are particularly illiquid, and wondered whether the racial animus of potential investors was the source of this illiquidity. Talks with other muni bond traders yielded similar conclusions.

    2. In our paper we pay special attention to the possibility that our findings are driven by HBCUs’ higher credit risk. To examine this possibility we do the following:

    A) We limit the sample of university-issued bonds to AAA-rated issues. Given that no municipal bond with an AAA has ever defaulted, focusing on this subset should largely eliminate any role played by default risk. Yet, among this reduced sample (about 40% of the data), the HBCU effect remains stable at 15 basis points.

    B) We examine only insured bonds and compare the difference in issue gross spreads between HBCU and non-HBCU bonds insured by the same entity. Here, too, the difference remains stable (17 b.p.), even removing the Financial Crisis of 2008 and beyond period (16 b.p.).

    C) We utilize the nearest neighbor algorithm, developed by Adadie and Imbens (2006), to match each HBCU issuance with a non-HBCU issuance on various bond, school, and underwriter attributes. We require an exact match on state of issuance and credit rating. The result of this exercise confirms our prior findings: underwriter spreads for HBCUs are 21 basis points higher than those for matching non-HBCUs, a difference significant at the 1% level.

    3. We find very suggestive evidence that our results are driven by racial animus. We look at the difference in differences between HBCU bonds issued in states with high and low racial animus. While there is no difference in the underwriter discount of non-HBCU bonds among states with high and low racial animus, the difference between HBCU bond discounts in high racial animus states is roughly three times larger than the HBCU discount in low racial animus states.

    4. Why isn’t this arbitraged away? In the context of our study, this question is somewhat misplaced. We’re not showing that HBCU bonds are mispriced, only that underwriters charge HBCUs more to place the bonds. Our findings show no statistical difference between the sale prices of HBCU and non-HBCU bonds. Naively, this latter fact would seem inconsistent with HBCUs facing a “discrimination discount” in the bond market. However, such a conclusion would be premature. When a sale occurs, this is conditional on underwriters having found a willing buyer, and, accordingly, having incurred the required search costs. In equilibrium, discounts on sold bonds may end up being small, with HBCU-issued bonds being held by those without racial animus. However, this does not imply that frictions to external finance are no higher for HBCUs, but rather that underwriters are fulfilling their obligations to them, and being compensated accordingly.

  • YanLiu

    Dear Mr Casey Dougal,

    I am a graduate student of Nankai University in China. I major in Finance . Recently, I found one of your articles, titled Urban Vibrancy and Corporate Growth in The Journal of Finance. I found it may help me achieve my goals in this research field. I’m very interested to know the data aplied to the model in the third part of the article about all public companies from January1970 to December 2009 from is balanced panel data or unbalanced panel data because of the difference of the time to go public. The other question I am confused in is the fixed effect including firm, area, and year which is in last paragraph paged 178 . I would be much appreciated if you can reply me about the two questions. If you were kindly offering us the other articles about this field you have writed , it would be very helpful for me.Thank you for your kind consideration of this request.

  • Casey Dougal

    Hi Yan,

    The panel is unbalanced and the firm and area fixed effects are included to control for any unobserved, time-invariant heterogeneity at the firm and area level, while the year fixed effects are included to control for common variation across firms within a year.

    Feel free to email me at [email protected] if you have anymore questions.