Finance - Theses
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ItemEssays in Corporate Finance( 2023-07)This thesis explores the determinants and effects of corporate innovation and technology spillovers, emphasizing their roles in productivity and economic gains. It contains a literature review and two essays examining different aspects of finance at its intersection with innovation. The first essay investigates how competition affects the economic value of innovation, the primary incentive for corporate R&D investments. I measure the economic value of innovation based on the changes in patenting firms' stock market value around patent issuance dates, following Kogan et al. (2017). The economic value of innovation is higher in industries with a low level of competition. Within an industry, firms at the technological frontier or those with relatively high pricing power enjoy higher economic returns from patents. I use a quasi-natural experimental design to compare the value of patents issued immediately before and after competition-altering events. Using horizontal M&A announcements as anti-competitive events, I show that an expected decrease in market competition leads to increased patent value. In the second essay, Lyndon Moore and I study technology diffusion mechanisms using a unique historical setting: the introduction of the cyanide method of gold extraction on the Witwatersrand goldfields in the late 19th and early 20th centuries. Mines managed by the same mining house were more likely to adopt the new process, which increased extraction rates by around 50%. Cyanide technology was continually improved after its introduction. We find evidence of "technological know-how" spillovers from engineers and mine managers but not white-collar employees. Geographical spillovers are extremely localized in nature.
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ItemEssays on the Political Economy of Finance( 2023-07)This thesis investigates corporate finance issues through the lens of political economy. It explores the relationship between politics and business in China, focusing on the politicians' influences on the corporate sector. The study contains two essays that examine different channels through which politicians exert their impact: policy-making and physical activities. The first essay studies whether political ideology motivates economic decisions in authoritarian regimes. Using a novel ideology measure, I document that during China's privatization wave, a provincial governor's communist belief substantially reduces the privatization intensity in his province. In contrast, a provincial party secretary's ideology only has a moderate indirect impact. Moreover, firms privatized under more communist-minded governors achieve lower post-sale efficiency improvements. In contrast, a party secretary's ideology does not influence post-privatization efficiency. The second essay examines how politicians' activities affect the stock market and firm performance. I investigate how China's national leaders' firm visits affect other firms in the visited industries. I find that, for industry peers, these visits have a positive value impact in the short run but a substantial negative performance impact in the long run. Further analyses reveal that industry peers increase their investments after the visits, presumably in anticipation of additional government subsidies and credits. However, these resources are never delivered, and consequently, the profitability of these firms falls.
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ItemThe Role of Fee Structure in Mutual Fund Management( 2023-07)Mutual funds have become an increasingly popular investment vehicle over the past few decades, with a wide range of options available to investors seeking exposure to various asset classes and investment strategies. However, one of the key factors that investors must consider when choosing a mutual fund is the fees charged by the fund manager. These fees can have a significant impact on an investor's returns over time, and yet they are often poorly understood or overlooked altogether. The purpose of this thesis is to provide a comprehensive analysis of mutual fund fees and their impact on investor returns. This research focuses on the relationship between fees and fund performance, as well as the factors that influence fee levels and how they are disclosed to investors. Chapter One introduces the topic of mutual fund fees, outlining the key research questions and objectives of the study. This chapter also presents a discussion of the various types of fees charged by mutual fund managers. Chapter Two presents a review of the existing literature on mutual fund fees, including both theoretical and empirical research. This chapter provides a critical evaluation of the key theories and models that have been used to analyse mutual fund fees, as well as a summary of the most significant empirical findings in this area. The chapter also identifies gaps in the current literature and sets out the research questions that will be addressed in the subsequent chapters. Chapter Three examines one specific family-level strategy: the loss-leader pricing strategy. In this chapter the discussion is rooted in the question of why do fund families price low some of its member funds. Anecdotal evidence suggests this is due to flow incentives. This chapter provides systematic evidence that supports the existence of strategic pricing and finds rich pattern that fund families are leveraging pricing strategies to maximize family-level benefit. The flow incentive of fund families is reflected by the choice of loss-leader funds and fund-level inflows. Chapter Four gauges how much do fund families and investors care about fund fees by investigating an event study surrounding an SEC policy change. The policy change imposes different level of effect to different share classes of the same fund. The exogenous event provides an opportunity to separate the flow reaction to changes in fees and performance since all share classes of the same fund share the same before-fee risk adjusted returns and differ only in the fee structure. Chapter Four serves as an extension to Chapter Three in that it investigates more deeply into the dynamic of fee, flow and performance. In one aspect, this study adds to the mutual fund literature by introducing the concept of family-level strategic pricing. It challenges the traditional focus on individual fund-level pricing and provides insights into how mutual fund families strategically set prices to influence investor flows. This approach builds on previous research while addressing a gap in the literature by examining the motivations and dynamics behind family-level pricing decisions. It emphasizes that fund families often manage multiple funds with varying performance levels, optimizing fees collectively rather than for individual funds, which has implications for resource allocation and benefits for fund families. In another dimension, the study explores how investors consider mutual fund fees in their investment decisions. It references early research highlighting the impact of fees on investor behavior and includes trading costs as a significant component of a fund's total expenses that can affect fund flows. Additionally, it contributes to the literature on the relationship between mutual fund performance and flows, considering the asymmetric nature of this relationship. What sets this study apart is its inclusion of management fees and operating expenses in the performance-flow sensitivity analysis, emphasizing the direct link between fees and performance and their indirect influence on investor behavior. These insights offer a valuable perspective on the role of fees in shaping investor decisions within the mutual fund industry. Overall, this thesis aims to contribute to our understanding of mutual fund fees and their impact on investor returns. By providing a comprehensive analysis of this important issue, this research can help investors make more informed decisions about their mutual fund investments and can also inform policymakers and regulators as they seek to ensure that the mutual fund industry operates in a fair and transparent manner.
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ItemEssays on Blockholder and Corporate Finance( 2023-05)This thesis explores the multifaceted role of large shareholders ("blockholders") in a firm. There has been an exponential growth of the asset management industry in the last few decades, giving rise to more non-controlling blockholders in the firm. Such blockholders are important in corporate governance because the large stakes they hold incentivize them to monitor the firm. Given blockholder's importance, it is critical to understand what determines blockholder's presence. On the other hand, the evidence of blockholder's impact on firm outcomes has been mixed in the literature. This thesis helps shed light on both the determinants and impacts of blockholders in a firm. The first essay investigates how CEO incentives, i.e., the sensitivity of the CEO's wealth to firm value, affect blockholder monitoring. CEO incentives can both 1) complement blockholder monitoring by punishing the CEO harder when a dissatisfied blockholder exits, and 2) substitute blockholder monitoring by reducing the CEO-shareholder conflict. I model the relation between managerial incentives and blockholder monitoring and show the substitution effect dominates. I also find empirical evidence of the substitution effect: blockholding in a firm is lower when CEO incentives are higher, and this negative relation is stronger in firms where blockholders are there to monitor. In the second essay, I look at how a firm's covenant violations affect blockholders' stakes in the firm. After covenant violations, creditors have more control over the firm by renegotiating debt contracts. It has been documented that creditors use the increased control to help turn around the firm. I find that blockholders have higher stakes in a firm after its covenant violations, consistent with the notion that blockholders try to gain from a firm's recovery. Blockholders who lack the ability to maximize value on their own are more likely to take the chance to gain from the recovery. Consistently, I find that blockholders who are experienced in governance activities are less likely to have higher stakes after covenant violations. In the third essay, which is a joint work with Yifan Zhou, we find that blockholders are positively associated a firm's crisis recovery. We discover that during the 2008-09 Global Financial Crisis, blockholders were associated with i) more votes against manager-initiated proposals, ii) a higher probability of appointing a new CEO and/or director, and iii) issuance of less net debt. These firm decisions are in turn associated with superior post-crisis performances.
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ItemHuman, Artificial Intelligence and Tail Risk( 2022)I study learning efficiency of artificial and human agents in the environment of financial markets. One prominent feature that distinguishes this environment is tail risk, which means that outliers are more frequent and substantial relative to Gaussian outliers. Failure to account for tail risk deteriorates learning efficiency, causing agents to derail from optimal actions. In the dissertation, I explore improvements to learning by artificial agents under tail risk, and whether human learning exhibits similar improvements. Finally I study to what extent agents' interactions and intelligence level would cause or amplify tail risk. A key success of artificial intelligence has been reinforcement learning. I first show that even the most advanced reinforcement learning protocol yields sub-optimal behavior in an environment with tail risk. Inspired by the concept of statistical efficiency, I propose a solution that nicely complements a recent protocol -- distributional reinforcement learning -- and improves the performance of algorithms. I show that the proposed algorithm learns much faster and is robust once it settles on a policy. Thus, efficiency gains are possible for artificial agents. Do humans exhibit the same kind of adjustment in an environment of tail risk? In the second study, I design an experiment to examine whether and how efficiency concerns drive human learning of stochastic rewards. While I find substantial heterogeneity, overall the answer is affirmative. Efficiency gains translate into enhanced choice confidence, except when participants fail to discover the most efficient estimator. In finance, the real causes of tail risk remain elusive. One conjecture is that, even without triggers from any extreme event, tail risk emerges because of agents' interactions in the marketplace. Motivated by the zero-intelligence and machine learning literature, I propose a paradigm to approach this conjecture in the third study. The paradigm comprises a single-widget economy, a continuous open-book market, and a group of trading agents with different intelligence levels. I demonstrate that trading generates excessive tail risk even when the underlying economic shifts follow a Gaussian law. Introducing a profit-seeking market maker further increases leptokurtosis, but the tail risk is not worsened. The latter suggests that tail risk and leptokurtosis may need to be distinguished.
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ItemNew Approaches of Utilizing Firm Characteristics in Empirical Asset Pricing( 2022)Firm characteristics carry very important information about stock prices and can be widely used in various aspects of asset pricing. This thesis contains 3 new applications of firm characteristics combined with some new technologies, which brings new understandings to several important questions: In chapter 3, my co-authors and I apply the General Empirical Likelihood (GEL) estimator to ask and answer the question of, which characteristic-sorted portfolios provide valuable information about the stochastic discount factor (SDF). We estimate a non-parametric SDF from a set of portfolios, then test whether excluding a portfolio changes the implied SDF. Though related to traditional asset pricing tests, our approach has several advantages: we test all portfolios jointly and can incorporate trading costs easily. We show four portfolios provide independent information about the SDF after accounting for trading costs: the Market and Profitability factors, an Investment-based portfolio, and the Value-Momentum-Profitability anomaly portfolio. The remaining portolios are redundant. We show both the joint testing and transaction cost adjustments are important for inference, and provide a simple way to implement our tests. In chapter 4, I introduce a Machine Learning (ML) based approach to construct comparable groups that researchers often use to compute the abnormal part of stock returns. The characteristics shown in chapter 3 to be important to asset pricing are included in this study as candidate characteristics. In order for stock expected returns to be similar within groups and disperse across groups, I use the ML based approach to select characteristics that best distinguish expected returns, and cutoffs points where returns are most sensitive to the underlying characteristics. I show that: 1) the combination of chosen characteristics changes over time; 2) fewer fund managers are identified to be stock pickers once the time-variation in comparable groups is incorporated; 3) and the resulting portfolios exhibit desirable properties as basis assets. In chapter 5, I adopt the ML based comparable groups from chapter 4 to analyze the market timing and stock picking skills of actively managed mutual funds. Compared to traditional studies which are prone to model mis-specification due to the difficulties in handling large dimensions and non-linearity, my approach can extract information about returns from a large number of characteristics, and allows for complex and time-varying relations between stock returns and firm characteristics. To the contrary of the consensus in prior literature, I find strong evidence in support of fund timing skills. On average, funds exhibit significantly positive timing performance. Cross-sectionally, the best timers continue to outperform others for at least three years after the ranking period. There is some picking return for the average fund but out-performance in picking does not persist. These results have real-world implications. I further show that investors can use my timing measure to identify funds with high future risk-adjusted performance.
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ItemComputational complexity of decisions: Quantifying computational hardness and its effects on human computation( 2021)Humans are presented daily with decisions that require solving complex problems. In many cases, solving these problems is computationally hard. This raises a tension between the computational capacity of the agent and the computational requirements of a task. Whilst the underlying invariants of this mechanism remain unclear in cognition, they have been widely studied in computer science. I build on theoretical and empirical work in computational complexity, which characterizes the intrinsic computational hardness of problems. I first present an adaptation of this theoretical framework for the study of human cognition by introducing a set of metrics of hardness of instances of problems. I do this in a way that is independent of any algorithm or computational model and that can be generalized to other problems. Based on this, I explore empirically, in a set of lab experiments, how these task-independent metrics of hardness affect human problem-solving. I do this at two levels of analysis. Firstly, I study how these metrics affect human performance at the behavioral level in three canonical computational problems: the knapsack problem, the traveling salesperson problem and the Boolean satisfiability problem. Secondly, I examine the relation between computational hardness and the neural processes associated with problem-solving, employing ultra-high field functional MRI. I find that the metrics of intrinsic hardness put forward here predict human performance and time-on-task across the three computational problems in a similar way. Moreover, I identify the neural correlates of computational hardness in the knapsack task, a complex problem-solving task. I show that this framework can be used for the study of the neural underpinnings of problem-solving by providing a generic definition of cognitive demand. The results of these studies provide support for the conceptual premise that the quantification of intrinsic hardness is fundamental in the development of more refined theories of human decision-making and its neural underpinnings. Critically, they provide a framework to study how humans adapt to computational complexity and how intrinsic hardness of tasks affect the reliability of human decision-making. This could inform public policy by identifying which decisions over products involve solving problems that require computational resources beyond those available to an agent, and how this affects decisions.
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ItemEssays on Political Economy of Finance( 2021)This thesis explores mechanisms that connect firms to politicians, as well as new channels through which firms benefit from being politically connected, under different ecopolitical environments. It contains three essays examining various aspects of finance at its intersection with political science. The first essay exploits Donald Trump’s nonpolitical background and surprise election victory to identify the value of sudden presidential ties among S&P 500 firms. In our setting firms did not choose to become politically connected, so we identify treatment effects comparatively free of selection bias prevalent in this literature. Firms with presidential ties enjoyed greater abnormal returns around the 2016 election. Since Trump’s inauguration, connected firms had better performance, received more government contracts, and were less subject to unfavorable regulatory actions. We rule out a number of confounding factors, including industry designation, sensitivity to Republican platforms, campaign finance, and lobbying expenditures. The second essay finds that borrowers from the same state as the Chairman of the US Senate Banking Committee, whom I term "connected", are able to borrow at spreads 14 basis points lower than other borrowers. Connected borrowers’ contributions toward the Chairman are influenced by their cost of loans, but the same is not true for nonconnected borrowers. Findings suggest the Chairman is incentivized by reelection to actively help connected borrowers obtain cheaper loans. Banks that offer a larger fraction of connected loans enjoy higher future excess stock returns. Results are consistent with the existence of a quid pro quo relationship triangle between firms, banks, and politicians. The third essay examines how changes in local political leadership affect firms’ gover- nance structures. Using a novel dataset, I document that following the appointment of a new city-level Chinese Communist Party (CCP) secretary, local firms increase (decrease) the fraction of directors who share a common birthplace with the incoming (departing) secretary. This appears to be a channel through which Chinese firms establish political connections. Firms with a higher percentage of birthplace-connected directors exhibit higher abnormal returns around secretary appointments. These firms enjoy superior accounting performances and attract institutional fund flows. I reject an alternative hypothesis that these directors are appointed to company boards on the "orders" of the politician, rather than actively recruited by firms.
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ItemThree Essays on CEO Compensation and the Agency Problem of Debt( 2020)Jensen and Meckling [1976] propose that compensating a manager with debt-like payment, a.k.a. “inside debt”, can be a mechanism to mitigate the agency problem of debt. Recent empirical papers document that higher inside debt held by a chief executive officer (“CEO”), which is measured by the present value of their supplemental retirement benefits, is associated with more conservative management and lower cost of debt. However, the grant of inside debt might originate from rent extraction purposes, and happens to encourage risk aversion among CEOs. Therefore, it remains unclear whether companies use CEO inside debt as a mechanism to mitigate the agency problem of debt. To address this question, my thesis examines how U.S. public companies adjust their use of CEO inside debt in three corporate events that involve changes to the agency problem of debt. In the first essay (Chapter 4), I show that new active blockholders adjust CEO inside debt-equity ratios to increase total firm value, not just equity value. These investors are more like to arise when CEO inside debt-equity ratios are not properly set up to maximize total firm value. The speed of adjustments towards the appropriate ratios triples in the presence of active blockholders, but returns to the normal level once these investors “exit”. Such compensation adjustments are associated with positive stock and bond abnormal returns over the active block holding period. I also find that new active blockholders arise and restructure compensation when the old structures over-align CEOs’ incentives to either shareholders’ or debtholders’ interests. I argue that superb stock-picking skill, a mean-reverting process of compensation changes, or co-founding firm characteristics cannot explain the large compensation adjustments during active blockholders’ presence. Instead, these blockholders actively affect CEO compensation structures by appointing their favored directors into the targeted firms’ boards, especially into the compensation or governance committees. In the second essay (Chapter 5), I show that companies raise their CEO inside debt to address the heightened agency problem of debt due to increased leverage, after they remove anti-takeover provisions (“ATPs”). By using a difference-in-difference-in-difference analysis, I document significant increases in CEO inside debt-equity ratios after companies remove ATPs. Inside debt also rises significantly after ATP removals, which accounts for 70% of increases in the overall ratios. In contrast, inside equity significantly decreases after companies remove ATPs, as these companies reduce the stocks and options awarded to their CEOs. These findings are robust to different explanatory variables, matching samples, and removals of certain ATPs. Further analysis displays that inside debt-equity ratios increase continually for the first three years after ATP removals. This trend coincides with the after-ATP-removal spike in leverage, which is caused by increased debt issuance. I also show that increasing inside debt-equity ratios, especially increasing inside debt, helps companies reduce the cost of borrowing after ATP removals. However, increasing inside debt can only address part of the heightened agency problem of debt, as companies still face more costly debt financing after ATP removals. Despite the increase in inside debt and decrease in inside equity, CEOs take more risks after their companies remove ATPs. This result suggests that removing ATPs can substitute for the role of inside equity in providing CEOs with more risk-taking incentives. In the third essay (Chapter 6), I explore the timing strategies for bond issuances based on disclosures of CEO inside debt. During the months before proxy statement releases, new changes in CEO inside debt are private information to companies’ insiders. Companies can exploit this information asymmetry to issue bonds when the market, based on publicly available information of inside debt, perceives these companies’ debt agency problems as relatively insignificant. I find that companies cluster their bond offerings in the immediate quarters after (before) disclosures of positive (negative) inside debt changes. The tendencies to time bond issuances based on inside debt disclosures also increase with the magnitudes of the disclosed changes. In addition, the adoption of these timing strategies is more observable when the issuing firms are regular issuers or when the new issues do not include covenants, especially the debt-restriction covenants. Finally, I verify that these timing strategies help reduce the cost of borrowing. The bonds issued at favorable times, i.e. right after positive change disclosures or before negative change disclosures, have lower offering yield spreads than those issued at non-favorable times.
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ItemEssays on Perfect Foresight in Asset Pricing( 2020)Through experimental and theoretical analysis, this thesis addresses the question of how the context of information in capital markets can affect the occurrence of perfect foresight equilibria. It contains three essays that build on theoretical and experimental applications of the perfect foresight assumption. The first essay contrasts theoretical and experimental strains of information aggregation – the ability of prices to aggregate disparate pieces. It contains a methodological guide for designing robust information aggregation experiments with a detailed description of the pilot studies that were used to develop the experimental study in the second essay. The second essay introduces two new theoretical concepts to the analysis of rational expectations equilibrium models. These concepts stem from “stability” characteristics inherent to the perfect foresight state-price mapping. Differences in stability characteristics are shown to arise from differences in the initial information structure underlying the aggregation problems. In the experiment, we test information aggregation with two fundamental information structures in continuous time double auction asset markets: The first information structure is motivated by the canonical information aggregation model in theoretical asset pricing. In this setting, the asset traded pays according to the average privately held information signal in the market. This setting has a stable state-price mapping and is shown to aggregate information well. The second information structure is motivated by prediction markets and studies in experimental finance. Both feature winner-take-all contracts where binary pay depends on the signal type held by the majority of agents. This setting is unstable under the theoretical stability concepts and is shown to aggregate information less efficiently. The third essay examines the use of perfect foresight when modelling disagreement in financial markets. In particular, we examine the conditions under which the perfect foresight approach can be used in a rational expectations equilibrium model. We show that an agent’s perfect foresight may be inconsistent with their own beliefs (based on subjective probabilities) unless their higher-order beliefs (about other participants’ beliefs) are correct.
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