Essays on Investor Beliefs, Attention, and Arbitrage
Date of Award
Spring 1-1-2025
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Economics
First Advisor
Barberis, Nicholas
Abstract
This dissertation comprises three essays on topics in financial economics: investor beliefs, attention, and arbitrage. In the first chapter, I propose a novel approach to institution-level asset demand estimation and then apply it to obtain estimates of investor beliefs. Across institutions, I divide investors' idiosyncratic beliefs about a given stock into two categories: “overt beliefs,†the beliefs of institutions that elected to own the stock, and “hidden beliefs,†the beliefs of institutions that elected not to own the stock. The demand estimation approach allows for recovery of overt beliefs and identifies strong upper bounds on hidden beliefs, which are obscured by both short sale constraints and 13F filings' non-reporting of short sales; the data is censored. I aggregate these bounds and estimates across institutions to create a Hidden Beliefs Index (HBI) and Overt Beliefs Index (OBI). The OBI displays minimal ability to forecast returns. Contrary to standard rational frameworks, however, the HBI strongly predicts returns in the cross section. These results suggest that markets largely incorporate overt beliefs, which can be more easily recovered from the 13F filings, but fail to fully account for the informational value of hidden beliefs. I show empirically and theoretically that this paper's results are consistent with a form of bounded rationality but inconsistent with a pure disagreement and short sale constraint mechanism. Investors engage in approximately Bayesian inference about others' information when they observe that an institution owns a stock, but when they observe that an institution does not own a stock, they fail to fully adjust their posterior beliefs about the stock's idiosyncratic return. In the second chapter, I establish a new empirical finance puzzle, the retail alignment puzzle: aggregate retail trader purchases and sales are nearly perfectly correlated across time and in the cross section of equities despite retail traders representing a small fraction of exchange volumes and being commonly represented as displaying lopsided flow patterns. Consistent with this puzzle, retail purchases and sales in the cross section are linearly predicted by the same two attention-associated factors, recent return salience and recent volume, with regressions on purchases and sales possessing almost identical coefficients. Using both directly measured attention through Google Trends search volumes and common indirect measures of attention such as volumes and extreme returns, I show that surges in retail attention consistently generate both large trading volumes and proportionally limited net trading. I then use an equilibrium disagreement model to show analytically and through simulations that while positive shocks to retail attention, sentiment, and disagreement all increase price, only shifts in attention are capable of reproducing empirical volume and return patterns. This paper's results suggest that attention is one of the core drivers of retail volume in common stocks. In the third chapter (co-authored with Eduardo Dávila and Cecilia Parlatore) we study the social value of closing price differentials in financial markets. We show that arbitrage gaps exactly correspond to the marginal social value of executing an arbitrage trade. Moreover, arbitrage gaps and price impact measures are sufficient to compute the total social value from closing an arbitrage gap, which may emerge for different reasons, including non-pecuniary benefits of holdings particular assets. Theoretically, we show that, for a given arbitrage gap, the total social value of arbitrage is higher in more liquid markets. We compute the welfare gains from closing arbitrage gaps for covered interest parity violations.
Recommended Citation
Graves, Daniel David, "Essays on Investor Beliefs, Attention, and Arbitrage" (2025). Yale Graduate School of Arts and Sciences Dissertations. 1658.
https://elischolar.library.yale.edu/gsas_dissertations/1658