This dissertation consists of two essays that study how credit expansion and government policy on mortgages shaped the 1999-2010 U.S. housing cycle and business cycle. Chapter 1 studies whether credit expansion or speculation mainly causes the housing cycle. During the 1999-2009 U.S. housing cycle, two opposing empirical facts present a puzzle: the correlation between income growth and mortgage growth is negative across ZIP codes within metropolitan areas (some argue for the credit expansion view) but positive across metropolitan areas (others argue for the speculation view). First, this paper shows that the cross-metropolitan phenomenon, in fact, supports the credit expansion view: by an instrumental variable approach, this paper shows that net export growth across metropolitan areas causes income growth and credit expansion in mortgage growth, which eventually leads to the housing cycle. Second, this chapter builds a simple model to illustrate how credit expansion can reconcile the above two empirical facts. This model generates new predictions of double differences: the differential stronger boom and bust cycle in mortgages and house prices in low-income ZIP codes than in high-income ZIP codes within the same metropolitan area is more pronounced in high net-export-growth metropolitan areas. This paper provides empirical causal evidence for these predictions, further supporting the credit expansion view. Chapter 2 uses the causal framework in Chapter 1 to test which business cycle theory can explain the 1999-2010 U.S. business cycle. This chapter shows that credit expansion in private-label mortgages causes a differentially stronger boom (2000-2006) and bust (2007-2010) cycle in the house-related industries in the high net-export-growth areas. Thus, these results are consistent with the credit-driven household demand hypothesis. Most importantly, the unique research design enables a set of tests on theories (hypotheses) regarding the business cycle. This paper shows that the following theories (hypotheses) cannot explain the cause of the 1999-2010 U.S. business cycle: the speculative euphoria hypothesis, the real business cycle theory, the collateral-driven credit cycle theory, the business uncertainty theory, and the extrapolative expectation theory.

The first chapter uses data on birthplaces of 2,065 Chief Executive Officers (CEO) and a county-level measure of cultural individualism based on the westward expansion in American history to establish a positive relation between CEO cultural individ- ualism and corporate innovation. Difference-in-differences estimations around CEO turnovers support the causality. Individualistic CEOs increase innovation by creating an innovative corporate culture, providing more flexibility to employees, and tolerance for failure.The second chapter develops a model to study the corporate board structure and communication. Outside directors are related to potential competitors. As a result, they can bring valuable advice and cause information leakage. The firm needs to decide whether to have outside directors on the board. In the presence of the outside director, the other directors need to determine whether to communicate.

This dissertation consists of two essays. The essay “Is Capital Reallocation Really Procyclical?” studies the cyclicality of corporate asset reallocation and its implication for aggregate productivity efficiency. Empirically, aggregate reallocation is procyclical. This is puzzling given the documented evidence that the benefits of reallocation are countercyclical. I show that this procyclicality is driven entirely by the reallocation of bundled capital (e.g., business divisions), which is highly correlated with market valuations and is unrelated to measures of productivity dispersion. In contrast, reallocation of unbundled capital (e.g., specific machinery or equipment) is countercyclical and highly correlated with dispersion in productivity growth. To gauge the aggregate productivity impact of bundled transactions, I propose a heterogeneous agentmodel of investment featuring two distinct used-capital markets as well as a sentiment component. In equilibrium, unbundled capital is reallocated for productivity gains, whereas bundled capital is also reallocated for real, or perceived, synergies in the equity market. While equity overvaluation negatively affects aggregate productivity by encouraging excessive trading of capital, its adverse impact is largely offset by its positive externality on asset liquidity in the unbundled capital market. The second essay “The Profitability of Liquidity Provision” studies the profitability of liquidity provision in the US equity market. By tracking the cumulative inventory position of all passive liquidity providers and matching each aggregate position with its offsetting trade, I construct a measure of profits to liquidity provision (realized profitability) and assess how profitability varies with the average time to offset. Using a sample of all common stocks from 2017 to 2020, I show that there is substantial variation in the horizon at which trades are turned around even for the same stock. As a mark-to-market profit, the conventional realized spread—measured with a prespecified horizon—can deviate significantly from the realized profits to liquidity provision both in the cross-section and in the time series. I further show that, consistent with the risk-return tradeoff faced by liquidity providers as a whole, realized profitability is low for trades that are quickly turned around and high for trades that take longer to reverse.

This thesis explores the profitability of various technical trading strategies to explore their ability, generate returns in the American stock market. All strategies are based on five popular technical indicators, including the volume-weighted average price, moving average convergent-divergent index, Bollinger bands, support/resistance, and simple momentum trading. Most strategies were tested from 2019-2022 and tested for the SPY and QQQ stocks, representing the S&P 500 and NASDAQ. 3 of the 26 strategies had win rates of over 50%, but several were able to greatly outperform broader market returns. The best performing strategies were based on simple momentum trading, while the MACD and Bollinger Bands produced the worst results. Some strategies based on simple momentum trading or Bollinger bands found results greatly exceeding standard market returns in recent years, but most do not.

I propose new measures of investor attention for Mutual Funds. Using the Security and Exchange Commissions’ Electronic Data Gathering, Analysis, and Retrieval (EDGAR) system’s server log files, this study is the first to explore investor attention to specific mutual funds. I find that changes, or spikes, in mutual fund investor attention are associated with funds’ introduction of a new share class, decreases in expense ratio, past performance and volatility. On average, spikes to investor attention predict net inflows into mutual funds which outpace the overall growth of the mutual fund sector. Attention via this EDGAR channel is more important when investors are researching more opaque funds. Moreover, there is a positive relationship between mutual fund investor attention and fund returns. Yet, there is evidence that investors appear to be responding to the acquisition of stale information with flows. I additionally utilize Google Trends data for individual fund tickers and investigate its effects in Mutual Fund Market. I find that Investor Attention to individual mutual funds is concentrated within Equity funds, Index funds, and Institutional funds. Individual fund attention is strongly negatively associated with expense ratios, 12B-1 Fees, and 'broker sold' funds, suggesting that funds with higher fees get less attention than low cost index funds. I find limited support for the controversial convexity in the flow to performance sensitivity in the Mutual Fund market, but only in funds with high levels of individual attention.

My project has been a long journey, one that I have learned a tremendous amount on. The final version of my project has come out to be a booklet teaching first time users of code and python the basic steps of getting started and some vital information that I learned while I was learning the language. I started my thesis with the idea of creating a portfolio of stock, bonds and commodities to determine the best allocation of your money over a 30-year period. To do this, I needed to learn how to code and become proficient quickly so I could create a program that would be powerful enough as well as spit out the correct output in the end. Unfortunately, I fell short of being able to build this portfolio out. I took on the challenge of learning Python on my own with no knowledge of any coding language to see if I could pull the whole project together. I failed, but I learned so much along the way and that I think is more valuable than anything. Since I was unable to complete my code, I shifted my attention to creating a small booklet on the basics of getting started in Python as if you have never looked at a coding language. Many of the tips I discuss in my booklet are problems I struggled with when I began. In the beginning I couldn’t even figure out how to get to a coding platform to begin my work, so I began to research and found many helpful tips that took me quite a while to understand.

This paper explores the rationale and analysis of a global financial institution and the methodologies used to underwrite a deal between the commercial bank and a middle market client looking to renew existing commercial loans; particularly a real estate term loan, long-term revolving line of credit, guidance line of credit (GLOC), equipment line of credit, and an interest rate swap contract. Typical analysis in the form of risk allowance, collateral due diligence, industry observation, and company-specific financial and operational strength has been performed and the deal has been approved by JPMorgan Chase & Co. Additionally, the frequency of covenant default has been determined by a pro forma income statement simulation based on a combination of both normal and uniform distributions to determine various outcomes for sales and cost of goods sold growth in future years. The results of the simulation are used to determine probability of default on specific financial covenants in the deal to gain a better understanding of the risks associated with the proposed exposure amount and the client's future financial situation.

In the first chapter, I develop a representative agent model in which the purchase of consumption goods must be planned in advance. Volatility in the agent's portfolio increases the risk that a purchase cannot be implemented. This implementation risk causes the agent to make conservative consumption plans. In the model, this leads to persistent and negatively skewed consumption growth and a slow reaction of consumption to wealth shocks. The model proposes a novel explanation for the negative relation between volatility and expected utility. In equilibrium, prices of risky assets must compensate for the utility loss. Hence, the model suggests a new mechanism for generating the equity risk premium. Importantly, because implementation risk does not rely on the co-movement of asset prices with marginal utility, the resulting equity premium does not require concavity of the intratemporal utility function.

In the second chapter, I challenge the view that equity market timing always benefits

shareholders. By distinguishing the effect of a firm's equity decisions from the effect of mispricing itself, I show that market timing can decrease shareholder value. Additionally, the timing of equity sales has a more negative effect on existing shareholders than the timing of share repurchases. My theory can be used to infer firms' maximization objectives from their observed market timing strategies. I argue that the popularity of stock buybacks, the low frequency of seasoned equity offerings, and the observed post-event stock returns are consistent with managers maximizing current shareholder value.

I study the performance of hedge fund managers, using quarterly stock holdings from 1995 to 2010. I use the holdings-based measure built on Ferson and Mo (2012) to decompose a manager's overall performance into stock selection and three components of timing ability: market return, volatility, and liquidity. At the aggregate level, I find that hedge fund managers have stock picking skills but no timing skills, and overall I do not find strong evidence to support their superiority. I show that the lack of abilities is driven by the large fluctuations of timing performance with market conditions. I find that conditioning information, equity capital constraints, and priority in stocks to liquidate can partly explain the weak evidence. At the individual fund level, bootstrap analysis results suggest that even top managers' abilities cannot be separated from luck. Also, I find that hedge fund managers exhibit short-horizon persistence in selectivity skill.