Finance Theses and Dissertations
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Item Essays on Mutual Fund Performance Evaluation and Investors' Capital Allocations(2022) Cao, Bingkuan; Wermers, Russ; Business and Management: Finance; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The dissertation contains two chapters that studies the performance of mutual funds and investors' capital allocations. In the first chapter, I study mutual funds' portfolio management and investors' capital allocations in a unified framework under mandatory portfolio disclosure. By modeling fund managers and investors simultaneously, I show that more skill managers produce better performance by trading more actively, which causes investors to care about both fund performance and activeness when evaluating fund managers. This investor's behavior explains the convex flow-performance relation observed in the market. In addition, my model demonstrates that portfolio holdings information is more useful to investors than fund returns because portfolio holdings reveal manager activeness that is not fully captured by fund returns. My model offers three novel empirical predictions for which I find consistent evidence in the data. First, investor flows respond to both fund performance and activeness. Second, investor flows are more sensitive to the performance of illiquid holdings in the portfolio. Finally, in a diff-in-diff analysis, I show that investor flows become more sensitive to fund activeness when portfolios are disclosed more frequently. In the second chapter, I study the performance attribution of bond mutual funds. I build a comprehensive sample of U.S. actively managed bond mutual funds with a large cross section and long time series, and examine the characteristics of funds that are most associated with superior active bond fund performance. I construct several sets of covariates to measure different aspects of managerial ability, including risk management, credit analysis, activeness, beta timing, liquidity provision, and family synergy. Given the large set of covariates, I employ machine learning methods such as Boosted Regression Trees to select the best predictors of bond fund performance. Unlike equity funds, I find that risk management plays an important role in generating superior performance. In addition, funds that are better at credit analysis and charge lower fees outperform their peers.Item Triptych in Empirical Finance(2022) Delalay, Sylvain; Maksimovic, Vojislav; Santosh, Shrihari; Business and Management: Finance; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation contains three chapters that explore topics in empirical finance and political economy. In Chapter 1, I study how the fundraising revenues of political campaigns affect the outcome of U.S. elections. First, I assemble a novel and granular dataset that provides a comprehensive picture of cash flows and voting intentions during U.S. congressional races. Then, I extract weekly shocks to the fundraising revenues of campaigns by using machine learning on the dataset. I find that the effect of revenues on the vote share decreases over the course of general elections. In races involving an incumbent, an additional $100,000 in challenger revenues increases her vote share by 1.48pp in the first half of the general election, but has no effect in the second half. Early cash infusions are more valuable than late cash infusions because they provide flexibility to respond to the opponent’s actions and mitigate current and future financing constraints. In Chapter 2, I examine how strategic and financial considerations shape the spending behavior of political campaign committees. To discipline the empirical analysis, I derive a dynamic model of strategic investment under financing constraints. I test the predictions of the model using the revenue shocks constructed in Chapter 1. I find that a committee’s elasticity of advertising expenditures to the revenue shocks of its opponent is 8%, which is a third of a committee’s elasticity to its own shocks. Moreover, a committee that is relatively richer than its opponent reacts more aggressively to its opponent’s shocks, both in levels and as a fraction of cash reserves. This result suggests that the availability of internal financing can amplify the competitive aspect of political spending in electoral races. In Chapter 3, I identify investor overreaction in a setting where information flows are not observable and learning pertains to multiple dimensions of an asset. Specifically, I measure how investors react to the information released during merger attempts and whether they form rational beliefs about the probability of deal completion. Using a model of distorted learning that generates testable implications, I find evidence of relative mispricing in the cross-section of merger targets. Empirically, a low price-implied probability of success underestimates the actual probability of success, and vice versa, suggesting that investors overreact to deal-specific information. The overreaction is unrelated to the unconditional merger premium and not driven by exposure to traditional risk factors.Item ESSAYS ON EMPIRICAL ASSET PRICING(2020) xue, jinming; Wermers, Russ; Kyle, Albert; Business and Management: Finance; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In essay 1: This paper measures the time-varying provision of liquidity by buy-side customers (e.g., mutual funds and pension funds), relative to bond dealers, in corporate bond markets using a structural vector autoregression (SVAR) model. As indicated by my simple theory model, shocks to the relative willingness of customers and bond dealers to provide liquidity affect, in opposite directions, the choice of bond dealers between market-making (principal) and matchmaking (riskless principal) transactions. Motivated by this model, my SVAR empirically disentangles these shocks to customers versus bond dealers. My SVAR-derived patterns of these structural shocks provide fundamental insights into the mechanics in corporate bond markets following recent events, such as exposing the increased role of buy-side customers for liquidity provision after the many regulatory changes following the 2008 financial crisis. Furthermore, my empirical approach generates “factors” that provide an improved time-series asset-pricing model for yield spreads of corporate bonds of different credit ratings. In essay 2: We consider an approach to derive the conditional expectation of return quantities under the real-world probability measure, exploiting the form of the projected stochastic discount factor. Our treatment is formulaic in that the real-world expectation can be synthesized from the prices of the risk-free bond, the asset, and options on the asset. The method is free of distributional assumptions, and we use it to study empirical questions related to (i) conditional probability of a disaster and return upside and (ii) spanning hypothesis in the Treasury market. We examine empirical consistency and show that our theoretical treatment is relevant. In essay 3: Based on data until the mid 2000s, oil price changes were shown to predict international equity index returns with a negative predictive slope. Extending the sample to 2015, we document that this relationship has been reversed over the last ten years and therefore has not been stable over time. We then posit that oil price changes are still useful for forecasting equity returns once complemented with relevant information about oil supply and global economic activity. Using a structural VAR approach, we decompose oil price changes into oil supply shocks, global demand shocks, and oil-specific demand shocks. The hypothesis that oil supply shocks and oil-specific demand shocks (global demand shocks) predict equity returns with a negative (positive) slope is supported by the empirical evidence over the 1986--2015 period. The results are statistically and economically significant and do not appear to be consistent with time-varying risk premia.Item Essays on Market Microstructure and Asset Pricing(2019) Hu, Bo; Kyle, Albert S; Loewenstein, Mark V; Business and Management: Finance; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation contains three essays that explore various topics in market microstructure and asset pricing. These topics include statistical arbitrage, algorithmic trading, market manipulation, and term-structure modeling. Chapter 1 studies a model of statistical arbitrage trading in an environment with fat-tailed information. I show that if risk-neutral arbitrageurs are uncertain about the variance of fat-tail shocks and if they implement max-min robust optimization, they will choose to ignore a wide range of pricing errors. Although model risk hinders their willingness to trade, arbitrageurs can capture the most profitable opportunities because they follow a linear momentum strategy beyond the inaction zone. This is exactly equivalent to a famous machine-learning algorithm called LASSO. Arbitrageurs can also amass market power due to their conservative trading under this strategy. Their uncoordinated exercise of robust control facilitates tacit collusion, protecting their profits from being competed away even if their number goes to infinity. This work sheds light on how algorithmic trading by arbitrageurs may adversely affect the competitiveness and efficiency of financial markets. Chapter 2 extends the basic model in Chapter 1 by considering an insider who strategically interacts with a group of algorithmic arbitrageurs who follow machine-learning-type trading strategies. When market liquidity is good enough, arbitrageurs may be induced to trade too aggressively, giving the insider a reversal trading opportunity. In this case, the insider may play a pump-and-dump strategy to trick those arbitrageurs. This strategy is very similar to those controversial trading practices (such as momentum ignition and stop-loss hunting) in reality. We show that such strategies can largely distort price informativeness and threaten market stability at the expense of common investors. This study reveals a list of economic conditions under which this type of trade-based manipulations are likely to occur. Policy implications are discussed as well. Chapter 3 provides a simple proof for the long-run pricing kernel decomposition developed by Hansen and Scheinkman (Econometrica, 2009). In a stationary Markovian economy, the long forward rate should be flat so that the pricing kernel can be easily factorized in a multiplicative form of the transitory and permanent components. The permanent (martingale) component plays a key role as it induces the change of probabilities to the long forward measure where the long-maturity discount bond serves as the numeraire. I derive an explicit expression for this martingale component. It reveals a strong restriction on the market prices of risk in a popular approach of interest rates modeling. This approach neglects the permanent martingale component and restricts risk premia in a way undesirable for model calibration. Further analysis demonstrates the advantages of equilibrium modeling of a production economy since it is featured with a path-dependent pricing kernel that has a non-degenerate permanent martingale.Item Essays in Corporate Finance(2016) Bowen III, Donald Eugene; Faulkender, Michael; Business and Management: Finance; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation is comprised of three essays about investment, technology transfer, and corporate governance mandates. The first essay, “Patent Acquisition, Investment, and Contracting”, examines the transfer of intellectual property via the secondary market for patents and asks how patent acquisitions interact with firm investment policy. I find that patent acquirers subsequently invest in more R&D, increase internal patenting, and eventually make new investments in CAPX. Firms with more technological expertise and investment opportunities acquire more patents. Patent sales are the dominant type of contract and maximize investment incentives; patent licenses frequently contain royalties, which induce underinvestment problems. Nevertheless, licensing can be explained in part by financial and strategic considerations. Licensing is more likely when buyers become financially constrained, when revenue can be shifted to low tax sellers, and when the buyer is a competitor acquiring rights to a valuable patent. Overall, these results suggest patent acquisitions are motivated by the pursuit of investment synergies, rather than innovation substitution, commercialization motives, or legal threats. The second essay, “What's your Identification Strategy? Innovation in Corporate Finance Research”, co-authored with Laurent Fresard and Jerome P. Taillard, studies the diffusion of techniques designed to identify causal relationships in corporate finance research. We estimate the diffusion started in the mid-nineties, lags twenty years compared to economics, and is now used in the majority of corporate finance articles. Consistent with recent theories of technology diffusion, the adoption varies across researchers based on individuals' expected net benefits of adoption. Younger scholars, holders of PhDs in economics, and those working at top institutions adopt faster. Adoption is accelerated through networks of colleagues and alumnis and is also facilitated by straddlers who cross-over from economics to finance. Our findings highlight new forces that explain the diffusion of innovation and shape the norms of academic research. The third essay, “Were non-independent boards really captured before SOX?”, exploits the legal implementation of rules used by the major US stock exchanges following Sarbanes-Oxley (SOX) to study the pre-SOX optimality of board structure. The rules allowed firms to change the legal independence of their board without changing personnel by reclassifying a director from non-independent to independent. Many firms required to change their board structure used reclassification in order to minimize the alterations they made to their pre-SOX board structure, and I call these “placebo firms”. This observation makes feasible a DDD test that identifies the effect of the mandate by comparing treatment firms to placebo firms. Consistent with the view that boards are chosen optimally, real outcomes (profitability) are better for placebo firms than treatment firms. The magnitude of the difference, 4.9 percentage points, is economically meaningful, implying that the constraint is a significant impediment to the conduct of firms targeted by the regulations. Increased profitability is accounted for by increased revenue and typically flat expenses, including investment levels.Item Essays in Corporate Finance(2017) Duquerroy, Anne Nicole; Faulkender, Michael W; Business and Management: Finance; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation presents two essays in Corporate Finance. In the first essay, I study how political institutions affect corporate investment through the policy uncertainty channel. I examine investment response to changes in the ability of the governing party to implement its political agenda due to checks and balances. I use US gubernatorial elections from 1978 to 2010 and a regression discontinuity design to estimate the causal effects of giving a single party full versus split control over a state government. I find that shifts from a divided to a unified government depress investment and job creation. Investment drops by an average of 3 to 5 percent in the year after the election giving a single party control of the government. The effect is not limited to public firms, is stronger for firms operating in a single state and firms with more irreversible investment. The findings support the hypothesis that moving from divided to unified government translates into policy uncertainty, which in turn affects the investment and employment cycles. The second essay is joint with William Mullins and Christophe Cahn. How to support private lending to SMEs during aggregate contractions is a crucial but still open policy question. This paper exploits an unexpected drop in 2012 in the cost of funding bank loans to some firms but not others in France to uncover how banks adjust their SME lending portfolios in a crisis. The cost reduction causes bank debt to rise and payment defaults with suppliers to fall, providing evidence that funding cost can be an effective policy lever. The effect is driven by firms with only one bank relationship, a numerous but understudied group. The size of the effect varies, with additional credit flowing to firms with stronger observables, to high growth firms, to firms with high demand, and to firms with a deeper banking relationship. Further, a richer relationship appears to substitute for stronger observables in the lending decision. Finally, we provide suggestive evidence that, compared to multi-bank firms, single bank firms are particularly credit constrained in crisis periods.Item Short-Term Funding Markets and Systemic Risk(2015) Munyan, Benjamin Kendrick; Kyle, Albert S; Wermers, Russell R; Business and Management: Finance; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation presents two essays to study both theoretically and empirically the interaction of short-term funding and the banking system and its effects on systemic risk. Before its collapse in September 2008, Lehman Brothers had been using the repurchase agreement (repo) market to hide up to $50 billion from their balance sheet at the end of each quarter. When this "Repo 105" scheme was uncovered (a type of strategy called window dressing), the Securities and Exchange Commission conducted an inquiry into public US financial institutions and concluded that Lehman was an isolated case. Using confidential regulatory data on daily repo transactions from July 2008 to July 2014, in my first essay, I show that non-US banks continue to remove an average of $170 billion from the US tri-party repo market every quarter-end. This amount is more than double the $76 billion market-wide drop in tri-party repo during the turmoil of the 2008 financial crisis and represents about 10% of the entire tri-party repo market. Window dressing induced deleveraging spills over into agency bond markets and money market funds and affects market quality each quarter. Demand deposit contracts provide liquidity to investors; however by their nature they can expose the issuer to self-fulfilling runs. Existing models treat depositors as agents facing uncertain liquidity shocks, who seek to insure against that liquidity risk through use of a bank financed solely by deposits. Welfare-reducing bank runs then arise from the inherent difficulties depositors face in coordinating their withdrawals. My second essay extends the classic model of Diamond & Dybvig (1983) to allow for a more realistic mixed capital structure where the bank's investments are partly financed by equity, and where differing incentives between shareholders and depositors are allowed to operate. I also further extend the model to allow shareholders to choose the level of risk in bank-financed projects. I compute the ex-ante probability of a bank run in consideration of the bank capital ratio, and I additionally compute the level of bank risk chosen by utility-maximizing shareholders who are disciplined by uncoordinated depositors. I find that even in the absence of bank negotiating power of the form in Diamond & Rajan (2000), banks can be welfare-improving institutions, and there exists a socially optimal level of bank capital. I consider the policies of a minimum capital requirement, deposit insurance, and suspension of convertibility, and provide guidance on creating optimal bank regulation. I show that the level of bank capital involves a tradeoff between sharing portfolio risk and sharing liquidity risk. Increased bank capital results in less risk-sharing between shareholders and depositors. The demand deposit contract disciplines the bank and its shareholders, and equity capital in effect disciplines the depositors (by making runs less likely). There is a socially optimal level of natural bank capital, even when I make no further social planner restrictions on bank portfolio choice in the model.Item Essays on Asset Pricing and Financial Stability(2014) Lee, Jeongmin; Kyle, Albert S.; Loewenstein, Mark; Business and Management: Finance; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)My two-essay dissertation revolves around understanding the financial crisis of 2008. First I focus on the repo market, a major funding source of the shadow banking system, and show the repo market can create and amplify the fragility of the system. Then I investigate a broader economy with heterogeneous agents and demonstrate how the dynamics of equilibrium asset prices and wealth distributions are determined. In Essay 1, I develop a dynamic model of collateral circulation in a repo market, where a continuum of institutions borrow from and lend to one another against illiquid collateral. The model emphasizes an important tradeoff. On one hand, easier collateral circulation makes repos liquid and increases steady state investment through several multiplier effects, improving economic efficiency. On the other hand, it can harm financial stability because less capital is sitting on the sidelines waiting for investment opportunities. This fragility is further exacerbated by the endogenous repo spread through a positive feedback loop, and can result in an inefficient repo run. The model is relevant for understanding the repo markets during the financial crisis of 2008. In Essay 2, I study the dynamics of the wealth distribution and asset prices in a general equilibrium model. Agents face heterogeneous portfolio constraints that limit the shares of risky investments relative to wealth. The setup is motivated by empirical evidence that many households do not participate in the stock market and portfolio shares are heterogeneous and persistent conditional on stock market participation. There are two main results. First, one state variable can summarize the wealth distribution regardless of the number of types of agents. Second, when the economy is bad, it becomes more sensitive to additional negative shocks, meaning that not only magnitudes of the shocks but also their frequency matters.Item ESSAYS ON MARKET MICROSTRUCTURE AND HIGH FREQUENCY TRADING(2014) Li, Wei; Kyle, Albert S.; Business and Management: Finance; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation includes two chapters on topics related to market microstruc- ture and high frequency trading. In the first chapter, I explore the effects of speed differences among front-running high frequency traders (HFTs) in a model of one round of trading. Traders differ in speed and their speed differences matter. I model strategic interactions induced when HFTs have different speeds in an extended Kyle (1985) framework. HFTs are assumed to anticipate incoming orders and trade rapidly to exploit normal-speed traders' latencies. Upon observing a common noisy signal about the incoming order flow, faster HFTs react more quickly than slower HFTs. I find that these front-running HFTs effectively levy a tax on normal-speed traders, making markets less liquid and prices ultimately less informative. Such negative effects on market quality are more severe when HFTs have more heterogeneous speeds. Even when infinitely many HFTs compete, their negative effects in general do not vanish. I analyze policy proposals concerning HFTs and find that (1) lowering the frequency of trading reduces the negative impact of HFTs on market quality and (2) randomizing the sequence of order execution can degrade market quality when the randomizing interval is short. Consistent with empirical findings, a small number of HFTs can generate a large fraction of the trading volume and HFTs' profits depend on their speeds relative to other HFTs. In the second chapter, I study the effects of higher trading frequency and front-running in a dynamic model. I find that a higher trading frequency improves the informativeness of prices and increases the trading losses of liquidity driven noise traders. When the trading frequency is finite, the existence of HFT front-runners hampers price efficiency and market liquidity. In the limit when trading frequency is infinitely high, however, information efficiency is unaffected by front-running HFTs and these HFTs make all profits from noise traders who do not smooth out their trades.