I am a Visiting Assistant Professor of Finance at Indiana University Bloomington. I received my PhD in Finance from the University of Colorado Boulder in 2018. My research interests are:
Dynamic trading games
Cheap talk and disclosure
I have taught introductory finance, intermediate corporate finance, and intermediate investments.
*Scheduled, **Co-author, ***Scheduled and Co-author
Constrained Asset Prices
with Ed Van Wesep
Revise and Resubmit at the Journal of Finance
2017 Front Range Conference, 2017 SFS Cavalcade, 2018 European Winter Finance Conference**
We develop a model of asset pricing in which buyers are either unable or unwilling to buy an asset at a price substantially above its price in recent transactions. This constraint could result from legal restrictions on appraisals, behavioral preferences, or agency problems. The model features momentum, differential pricing for identical assets, buyers' and sellers' markets, and associations between price appreciation, volume, and liquidity. We apply the model to the market for residential real estate, in which a bank's willingness to lend for a home purchase is limited by the appraisal, which is, in turn, generated by recent transaction prices of similar properties. We confirm all six predictions of the model, none of which hold in the stock market, which is not subject to this constraint.
Learning by Owning in a Lemons Market
with Brian Waters and Kenneth Mirkin
Revise and Resubmit at the Journal of Finance
2019 MFA*, 2019 FIRS*, 2019 WFA***
We study market dynamics when an owner learns over time about the quality of her asset. Since this information is private, the owner sells strategically to a less informed buyer following sufficient negative information. In response, market prices feature a "U-shape" relative to the length of ownership prior to sale. As the owner initially acquires greater private information, buyers suffer greater adverse selection, and prices fall accordingly. Eventually, the probability of a strategic sale grows thin, and prices subsequently rebound. We provide evidence of a U-shaped price path in the markets for residential real estate, private equity, and construction equipment.
Internal Finance in Customer Owned Firms
2017 AFA PhD Poster Session
In the United States, customer owned firms are responsible for 35% of consumer insurance and 10% of consumer banking, yet receive little theoretical or empirical attention. In this paper, I propose a theory of internal finance for the customer owned firm. I show that its growth, pricing, and capital structure are tied together: higher sales tomorrow are achieved through higher prices today and lower leverage today. This result does not hold for a shareholder owned firm. I document stylized facts from the credit union industry and find that they are consistent with the theory's predictions. I discuss empirical implications for other customer owned firms, such as mutual insurance companies and agricultural credit associations.
2018 FIRS, 2019 RCFS/RAPS***
Ratings are often coarse. Examples include corporate debt ratings, stock analyst recommendations, Morningstar ratings, bank analyst evaluations, referee suggestions to editors, student grades, Yelp ratings, and film reviews. In the classic Crawford-Sobel (1982) model, coarse messaging is not optimal if the sender's and receiver's interests coincide. In the situations listed above, senders' and receivers' interests likely do coincide and the rating systems appear to be deliberately chosen. We provide a cheap talk model in which messages are received with exogenous noise and show that the optimal rating system may be coarse: while coarse messages are less precise, they are easier to interpret. In numerical work, we derive predictions for the distribution of ratings and show that the distributions we see in practice match the predictions of the model.
Optimal Disclosure to a Confirmation-Biased Market
2019 Marstrand Finance Conference***, 2019 Behavioural Finance Working Group Conference***, 2019 FMA European Conference***, Eleventh Accounting Research Workshop in Zurich***
with Jan Schneemier
We analyze a manager's optimal disclosure policy in a market in which some traders are confirmation-biased and ignore information inconsistent with their priors. The disclosed signal informs traders about the manager's unknown ability. By exerting costly effort, the manager can increase the precision of the disclosed signal and reveal more information to the market. The manager faces career concerns and maximizes the market's assessment of his ability. We find that more bias in the market leads to a more informative disclosure policy when traders overweight positive signals. Though some traders discard negative information, the overall market assessment can become more precise. Surprisingly, confirmation bias can reduce entrenchment and increase price efficiency and the expected firm value.