CaltechTHESIS advisor: Monograph
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https://resolver.caltech.edu/CaltechETD:etd-05292009-150803
Year: 2009
DOI: 10.7907/B75A-MW79
<p>We investigate behaviors in organizational and financial economics by utilizing and developing the latest techniques from game theory, experimental economics, computational testbed, and decision-making under risk and uncertainty.</p>
<p>In the first chapter, we use game theory and experimental economics approaches to analyze the relationships between corporate culture and the persistent performance differences among seemingly similar enterprises. First, we show that competition leads to higher minimum effort levels in the minimum effort coordination game. Furthermore, we show that organizations with better coordination also lead to higher rates of cooperation in the prisoner's dilemma game. This supports the theory that the high-efficiency culture developed in coordination games act as a focal point for the outcome of subsequent prisoner's dilemma game. In turn, we argue that these endogenous features of culture developed from coordination and cooperation can help explain the persistent performance differences.</p>
<p>In the second chapter, using a computational testbed, we theoretically predict and experimentally show that in the minimum effort coordination game, as the cost of effort increases: 1. the game converges to lower effort levels, 2. convergence speed increases, and 3. average payoff is not monotonically decreasing. In fact, the average profit is an U-shaped curve as a function of cost. Therefore, contrary to the intuition, one can obtain a higher average profit by increasing the cost of effort.</p>
<p>In the last chapter, we investigate a well-known paradox in finance. The equity market home bias occurs when the investors over-invest in their home country assets. The equity market home bias is a paradox because the investors are not hedging their risk optimally. Even with unrealistic levels of risk aversion, the equity market home bias cannot be explained using the standard mean-variance model. We propose ambiguity aversion to be the behavioral explanation. We design six experiments using real-world assets and derivatives to show the relationship between ambiguity aversion and home bias. We tested for ambiguity aversion by showing that the investor's subjective probability is sub-additive. The result from the experiment provides support for the assertion that ambiguity aversion is related to the equity market home bias paradox.</p>
https://resolver.caltech.edu/CaltechETD:etd-05292009-150803Credit Risk and Nonlinear Filtering: Computational Aspects and Empirical Evidence
https://resolver.caltech.edu/CaltechETD:etd-05272009-141742
Year: 2009
DOI: 10.7907/7XV3-9Q45
<p>This thesis proposes a novel credit risk model which deals with incomplete information on the firm's asset value. Such incompleteness is due to reporting bias deliberately introduced by insider managers and executives of the firm and unobserved by outsiders.</p>
<p>The pricing of corporate securities and the evaluation of default measures in our credit risk framework requires the solution of a computationally unfeasible nonlinear filtering problem. The model introduces computational issues arising from the fact that the optimal probability density on the firm's asset value is the solution of a nonlinear filtering problem, which is computationally unfeasible. We propose a polynomial time-sequential Bayesian approximation scheme which employs convex optimization methods to iteratively approximate the optimal conditional density of the state on the basis of received market observations. We also provide an upper bound on the total variation distance between the actual filter density and our approximate estimator. We use the filter estimator to derive analytical expressions for the price of corporate securities (bond and equity) as well as for default measures (default probabilities, recovery rates, and credit spreads) under our credit risk framework. We propose a novel statistical calibration method to recover the parameters of our credit risk model from market price of equity and balance sheet indicators. We apply the method to the Parmalat case, a real case of misreporting and show that the model is able to successfully isolate the misreporting component. We also provide empirical evidence that the term structure of credit default swaps quotes exhibits special patterns in cases of misreporting by using three well known cases of accounting irregularities in US history: Tyco, Enron, and WorldCom.</p>
<p>We conclude the thesis with a study of bilateral credit risk, which accommodates the case in which both parties of the financial contract may default on their payments. We introduce the general arbitrage-free valuation framework for counterparty risk adjustments in presence of bilateral default risk. We illustrate the symmetry in the valuation and show that the adjustment involves a long position in a put option plus a short position in a call option, both with zero strike and written on the residual net value of the contract at the relevant default times. We allow for correlation between the default times of each party of the contract and the underlying portfolio risk factors. We introduce stochastic intensity models and a trivariate copula function on the default times exponential variables to model default dependence. We provide evidence that both default correlation and credit spread volatilities have a relevant and structured impact on the adjustment. We also study a case involving British Airways, Lehman Brothers, and Royal Dutch Shell, illustrating the bilateral adjustments in concrete crisis situations.</p>
https://resolver.caltech.edu/CaltechETD:etd-05272009-141742Essays on the Impact of Information Asymmetry
https://resolver.caltech.edu/CaltechTHESIS:06042017-015517588
Year: 2017
DOI: 10.7907/Z9571925
<p>This dissertation consists of three essays focusing on how information asymmetry affects agents’ behavior across different environments. The first essay characterizes the optimal contract when a firm can employ two incentive schemes, promotion and pay for performance, simultaneously (Chapter 2). In the second essay, I study how information asymmetry can lead a firm to choose a less profitable short-term over a more profitable long-term project (Chapter 3). The other essay analyzes a career choice problem when agents have private information about their ability (Chapter 4).</p>
<p>Chapter 2 presents the effect of information asymmetry on executive pay structure to examine the cause of the rise in CEO compensation and wage inequality between CEO and other executives. To analyze the effect of the interaction of two incentive schemes, promotion and pay for performance, on CEO compensation and within-firm wage inequality, I embed a pay for performance framework into a tournament structure. The model shows that when CEO and managers contribute to a firm’s output independently, it is optimal for the firm to provide the CEO a compensation far beyond her reservation value in order to provide promotion incentives for managers. However, I find that the promotion incentive motive can disappear if there is interdependency between the CEO’s and managers’ outputs. In this case, the main purpose of a high CEO compensation is to induce the CEO to exert effort. The tension between incentives for CEO and managers makes it difficult to interpret the meaning of within-firm wage gap. As a possible solution, this paper suggests the use of CEO’s base salary to identify which incentive factor is driving the pay gap.</p>
<p>In Chapter 3, I study the optimal contract problem when a firm faces a long-term project. I consider a long-term project as one that requires an indefinite amount of time to complete its objective. I assume that the long-term project generates profits once it is accomplished. Using a continuous-time moral hazard model, I characterize the incentive compatibility condition in a relatively general contracting space. Moreover, I find a unique optimal contract under a restricted contracting space which consists of the two components: the termination level and the completion payment. The firm might invest in a short-term project: one that generates an instantaneous profit to the firm without any effect on the future, as analyzed by DeMarzo and Sannikov (2006). Comparison of optimal contracts for long and short-term projects provides an interesting insight to managerial short-termism: the firm, not the agent, could prefer a short-term project to a long-term project if there is a moral hazard problem.</p>
<p>Chapter 4 analyzes the role of asymmetry information on one’s career choice. I examine how people choose their career when they do not know ability of the rest of the applicant pool. The goal is to understand labor supply in the markets where ability is widely distributed. In particular, I consider a situation where there are two exclusive labor markets and the upper and lower bounds of one market’s payoffs are both higher than those of the other market. Under the market setting, agents decide which market to participate in. I find that the symmetric Bayesian Nash equilibrium of this problem is unique. In the equilibrium, agents are divided into two groups according to their ability. Members of the high ability group use a pure strategy and only apply to the more desirable market. Members of the low ability group apply to both markets with positive probability.</p>
https://resolver.caltech.edu/CaltechTHESIS:06042017-015517588Essays on Investor Beliefs and Asset Pricing
https://resolver.caltech.edu/CaltechTHESIS:05292018-140741507
Year: 2018
DOI: 10.7907/F2BV-8Y73
<p>This dissertation is composed of three chapters addressing the connections between investor beliefs and asset pricing. Specifically, I focus on one prevailing pattern of investor beliefs in the finance literature, return extrapolation. The idea is that investor expectations about future market returns are a positive function of the recent past returns. In this dissertation, I use this concept to understand a number of facts in the asset pricing literature.</p>
<p>Return extrapolation attracts growing attention in the literature, not only because it well explains real-world investors' expectations in the survey, but also because it significantly drives investor demand towards stocks. Therefore, we should anticipate a connection between return extrapolation measurement and the stock market dynamics. However, contrary to the intuition, previous empirical studies fail to document a significant connection. In Chapter 1, "Time-varying Impact of Investor Sentiment", I recover this connection. Specifically, I formally define investors who extrapolate past returns as extrapolators and incorporate their wealth level into analysis. My main finding is that return extrapolation interacts strongly with extrapolators' wealth level in predicting future market returns. Therefore, conditional on extrapolators' wealth level, return extrapolation significantly explains stock market returns.</p>
<p>The return extrapolation concept also raises challenges to the asset pricing models under the rational expectation frameworks. Specifically, rational expectation theories lead to a positive correlation between expectations and future realized returns, whereas return extrapolation indicates a negative correlation. Given this discrepancy, there is a clear demand for a behavioral asset pricing model that can simultaneously explain survey evidence on investor expectations and the classical asset pricing puzzles. In Chapter 2, "Asset Pricing with Return Extrapolation", coauthored with Lawrence Jin, we present a new model of asset prices based on return extrapolation. The model is a Lucas-type general equilibrium framework, in which the agent has Epstein-Zin preferences and extrapolative beliefs. Unlike earlier return extrapolation models, our model allows for a quantitative comparison with the data on asset prices. When the agent's beliefs are calibrated to match survey expectations of investors, the model generates excess volatility and predictability of stock returns, a high equity premium, a low and stable risk-free rate, and a low correlation between stock returns and consumption growth.</p>
<p>In Chapter 3, "Dark Matter" of Finance in the Survey, I investigate another attribute of investor beliefs—tail risk perceptions. Although tail risks play significant roles in explaining asset pricing puzzles, researchers have very limited knowledge about them because tail events are difficult to observe. I use Shiller tail risk survey to empirically investigate tail risk perceptions. In this survey, investors are asked to report their estimated probability for a crash event in the U.S. stock market. However, when using survey data to understand investors’ perception of tail risks, there are two fundamental challenges. First, is tail risks survey reliable? Second, to avoid cherry-picking, is there a unified framework to explain different attributes of investor beliefs? My analysis provides positive answers to both questions. First, I show that Shiller tail risk survey is reliable. More importantly, I show that return extrapolation can serve as a unified belief formation framework to explain not only variations in investor expectations but also in tail risk perceptions.</p>
https://resolver.caltech.edu/CaltechTHESIS:05292018-140741507Essays on Investor Beliefs and Asset Pricing
https://resolver.caltech.edu/CaltechTHESIS:05292018-140741507
Year: 2018
DOI: 10.7907/F2BV-8Y73
<p>This dissertation is composed of three chapters addressing the connections between investor beliefs and asset pricing. Specifically, I focus on one prevailing pattern of investor beliefs in the finance literature, return extrapolation. The idea is that investor expectations about future market returns are a positive function of the recent past returns. In this dissertation, I use this concept to understand a number of facts in the asset pricing literature.</p>
<p>Return extrapolation attracts growing attention in the literature, not only because it well explains real-world investors' expectations in the survey, but also because it significantly drives investor demand towards stocks. Therefore, we should anticipate a connection between return extrapolation measurement and the stock market dynamics. However, contrary to the intuition, previous empirical studies fail to document a significant connection. In Chapter 1, "Time-varying Impact of Investor Sentiment", I recover this connection. Specifically, I formally define investors who extrapolate past returns as extrapolators and incorporate their wealth level into analysis. My main finding is that return extrapolation interacts strongly with extrapolators' wealth level in predicting future market returns. Therefore, conditional on extrapolators' wealth level, return extrapolation significantly explains stock market returns.</p>
<p>The return extrapolation concept also raises challenges to the asset pricing models under the rational expectation frameworks. Specifically, rational expectation theories lead to a positive correlation between expectations and future realized returns, whereas return extrapolation indicates a negative correlation. Given this discrepancy, there is a clear demand for a behavioral asset pricing model that can simultaneously explain survey evidence on investor expectations and the classical asset pricing puzzles. In Chapter 2, "Asset Pricing with Return Extrapolation", coauthored with Lawrence Jin, we present a new model of asset prices based on return extrapolation. The model is a Lucas-type general equilibrium framework, in which the agent has Epstein-Zin preferences and extrapolative beliefs. Unlike earlier return extrapolation models, our model allows for a quantitative comparison with the data on asset prices. When the agent's beliefs are calibrated to match survey expectations of investors, the model generates excess volatility and predictability of stock returns, a high equity premium, a low and stable risk-free rate, and a low correlation between stock returns and consumption growth.</p>
<p>In Chapter 3, "Dark Matter" of Finance in the Survey, I investigate another attribute of investor beliefs—tail risk perceptions. Although tail risks play significant roles in explaining asset pricing puzzles, researchers have very limited knowledge about them because tail events are difficult to observe. I use Shiller tail risk survey to empirically investigate tail risk perceptions. In this survey, investors are asked to report their estimated probability for a crash event in the U.S. stock market. However, when using survey data to understand investors’ perception of tail risks, there are two fundamental challenges. First, is tail risks survey reliable? Second, to avoid cherry-picking, is there a unified framework to explain different attributes of investor beliefs? My analysis provides positive answers to both questions. First, I show that Shiller tail risk survey is reliable. More importantly, I show that return extrapolation can serve as a unified belief formation framework to explain not only variations in investor expectations but also in tail risk perceptions.</p>
https://resolver.caltech.edu/CaltechTHESIS:05292018-140741507Mathematical Models of Trading
https://resolver.caltech.edu/CaltechTHESIS:09282020-021601265
Year: 2021
DOI: 10.7907/9ks2-fa45
<p>This thesis presents a mathematical framework to model trading of financial assets on an exchange. The interaction between agents on the exchange is modeled as the Nash equilibrium of a demand schedule auction. The submission of demand schedules in the auction is meant to proxy for the submission of limit and market orders on an exchange. Chapter 1 considers this auction in a one-period setting, highlighting the importance of noisy flow for obtaining a unique Nash equilibrium.</p>
<p>Chapter 2 is the core of the thesis and considers the auction in a continuous time setting. Here the agents trading on the exchange have quadratic-type preferences, and in equilibrium they must clear an exogenously specified stream of market orders. Chapter 3 considers alternative and more realistic dynamics for the exogenous market orders. Chapter 4 endogenizes the market orders by considering an agent executing orders on behalf of noisy clients.. Chapter 5 considers the same model as in Chapter 2, except with a consumption based utility function for each agent.</p>https://resolver.caltech.edu/CaltechTHESIS:09282020-021601265Theory of Mathematical Optimization for Delegated Portfolio Management
https://resolver.caltech.edu/CaltechTHESIS:05272022-034901698
Year: 2022
DOI: 10.7907/km2b-er60
<p>We study the optimization problem of finding closed convex sets Γ ⊆ R<sup>d</sup> containing the origin that minimize F(Γ) = ∑<sub>i=1</sub><sup>k</sup> w<sub>i</sub> | θ<sub>i</sub>/2 - p<sub>Γ</sub>(θ<sub>i</sub>) | <sup>2</sup>, where w<sub>1</sub>, ..., w<sub>k</sub> > 0, θ<sub>1</sub>, ..., θ<sub>k</sub> in R<sup>d</sup> are given, and p<sub>Γ</sub>(θ<sub>i</sub>) are the closest points in Γ to θ<sub>i</sub>, i = 1, ..., k. This problem is motivated by the topic of delegated portfolio management in finance. In Chapter 2, we will explore this connection. To approach the problem, we first prove existence of a solution for the general problem. To further study properties of the solution, we next introduce the semidefinite programming relaxation, for which we have a first-order characterization of optimality. We then explore the question of exactness of this relaxation, which turns out to be equivalent to the notion of localizability: the shape optimization problem embedded in higher dimensions must have solutions in the original dimension. Finally, we present special cases for which localizability holds.</p>https://resolver.caltech.edu/CaltechTHESIS:05272022-034901698