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Dissertation Committee:
Jan Hanousek (chair)
Randall K. Filer
Evžen Kočenda

Abstract:

In the first chapter, I focus on the extent of information-driven trading originating from order flows to capture the behavior of the market makers on an emerging market. With my supervisor, we modified the classical Easley et al. (1996) model for the probability of informed trading using a jackknife approach in which trades of one particular market maker at a time are left out from the sum of all buys and sells. Using the estimates from the jackknife approach, for each market maker we test whether the order flows associated with the particular market maker behaved significantly different from the others. Data from the Prague Stock Exchange SPAD trading platform are used to demonstrate our methodology. Finding significant differences in the probability of informed trading computed from order flows, we conclude that order flows could reveal the extent of information-driven trading and could potentially be used by regulatory authorities to identify the suspicious behavior of market participants.

In the second chapter I analyze the potential conflict of interest between associated analysts and brokers. In contrast to the existing literature, with my supervisor, we do not analyze prediction accuracy and/or biases in analyst recommendations. Instead we focus our analysis on brokers and examine whether their behavior systematically differs before and after investment recommendations are released. The evolution and dynamics of brokers' quotes and trades are used to test for systematic trading patterns around the release of one's own investment recommendation. In the model we control for brokers' responses to other investment advice and employ a SUR estimation framework. Data from the Prague Stock Exchange are used to demonstrate our methodology. Finding significant and systematic differences in brokers' behavior, we conclude that misuse of investment recommendations is widespread.

In the third chapter, I analyze the risk preferences of bettors using data from the world largest betting exchange Betfair. The assumption of a constant bet size, commonly used in the current literature, leads to an unrealistic model of bettor's decision making as a choice between high return – low variance and low return – high variance bet, automatically implying risk loving preferences of bettor. However, the data show that bettors bet different amounts on different odds. Thus, simply by introducing the computed average bet size at given odds I transform bettor's decision problem into a standard choice between low return – low variance and high return – high variance bets, and I am able to correctly estimate the risk attitudes of bettors. Results indicate that bettors on Betfair are either risk neutral (tennis and soccer markets) or slightly risk loving (horse races market). I further use the information about the average bet size to test the validity of EUT theory. The results suggest that, when facing a number of outcomes with different winning probabilities, bettors tend to overweight small and underweight large differences in probabilities, which is in direct contradiction to the linear probability weighting function implied by EUT.

Full Text: “Essays on the Behavior of Agents in Financial Markets” by František Kopřiva