This dissertation consists of two essays. The first, titled “Sweep Order and the Cost of Market Fragmentation” takes a “revealed-preference” approach towards gauging the effects of market fragmentation by documenting the implicit costs borne by traders looking to avoid executing in a fragmented environment. I show that traders use Intermarket Sweep Orders (ISO) to trade “as-if” markets were single-venued and pay a premium to do so. Using a sample of over 2,600 securities over the period January 2019 to April 2021, this premium amounts to 1.3 bps on average (or 40%of the effective spread), amounting to a total of $3 billion over the sample period. I find a positive, robust, and significant relationship between the premium and different measures of market fragmentation, further supporting the interpretation of the premium as a cost of market fragmentation. The second essay, titled “The Profitability of Liquidity Provision” investigates the relationship between the profits realized from providing liquidity and the amount of time it takes liquidity providers to reverse their positions. By tracking the cumulative inventory position of all passive liquidity providers in the US equity market 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 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 dissertation consists of three essays studying topics in financial economicsthrough the lens of quantitative models. In particular, I provide three examples of the effective use of data in the disciplining of financial economics models. In the first essay, I provide evidence of a significant transitory component of aggregate equity payout. Leading asset pricing models assume exogenous dividend growth processes which are inconsistent with this fact. I find that imposing market clearing for consumption and income in these models induces the relevant behaviors in dividend growth, even when dividend growth is obtained indirectly. In the second essay, I provide a novel decomposition of the unconditional equity risk premium. In the data, the majority of the equity premium is attributable to moderate left tail risks, not those associated with disaster states. In stark contrast to the data, leading asset pricing models do not predict that this intermediate left tail region meaningfully contributes to the equity premium. The shortcomings of the models can be pinned on unreasonably low prices of risk for tail events relative to the data. In the third essay, I document a large dispersion in household allocations to risky assets conditional on age. I show that while standard household portfolio choice models can be made to match the average risky share over the lifecycle, the models fall short of generating sufficient heterogeneity in the cross-section of household portfolios.

Natural Language Processing (NLP) techniques have increasingly been used in finance, accounting, and economics research to analyze text-based information more efficiently and effectively than primarily human-centered methods. The literature is rich with computational textual analysis techniques applied to consistent annual or quarterly financial fillings, with promising results to identify similarities between documents and firms, in addition to further using this information in relation to other economic phenomena. Building upon the knowledge gained from previous research and extending the application of NLP methods to other categories of financial documents, this project explores financial credit contracts, better understanding the information provided through their textual data by assessing patterns and relationships between documents and firms. The main methods used throughout this project is Term Frequency-Inverse Document Frequency (to represent each document as a numerical vector), Cosine Similarity (to measure the similarity between contracts), and K-Means Clustering (to organically derive clusters of documents based on the text included in the contract itself). Using these methods, the dimensions analyzed are various grouping methodologies (external industry classifications and text derived classifications), various granularities (document-wise and firm-wise), various financial documents associated with a single firm (the relationship between credit contracts and 10-K product descriptions), and how various mean cosine similarity distributions change over time.

In this paper we conduct an out-of-sample test on gross profitability and investment in the same manner as Davis, Fama, and French (2000) for the pre-Compustat period (1926-1955). We hand-collect financial statement data from Moodys Industrial Manuals using the company PERMNO list first created by DFF. In total, we collect data from 1,291 firms, largely industrial firms but with some utilities. We then run Fama-Macbeth (1973) regressions using gross profit, scaled operating profit, scaled net income, and investment along with existing variables like book-to-market, market equity, one-month reversal, and one-year momentum. We find that the premiums on gross profitability and investment are not significant for any part of our sample period. For the overall sample period as well as the first half (before the 1933 Securities Act), our accounting data is often missing or cross-sectionally inconsistent. Despite the better-quality data in the period after 1935, however, neither gross profitability not investment have significant Fama-Macbeth slopes. We believe this is caused by inconsistent and incomplete accounting data, chiefly the number of firms that combine SG&A and COGS data into one "cost" number and the inclusion of investment-like costs, like R&D, in COGS or SG&A. This causes gross profitability to not reflect direct economic profitability as closely as in prior research. However, net income has significantly positive coefficients during this period and is not subsumed by gross profitability; this contradicts prior research for the post-1962 period. More data cleaning and analysis is needed in order to form firm conclusions on the gross profitability, net income, and investment premiums during this period.

The purpose of this thesis is to investigate the history of the Bitcoin arbitrage premium to see if the possibility of 'risk-free' gains existed previously and whether or not the opportunity is still present today. It investigates market structure and price discrepancies in $147B of trading volume across 53 different exchanges between July 2010 and February 2017. This paper aggregates exchange trading into five minute buckets of transaction volume in order to see what exchange volume could have been successfully arbitraged within the context of two cases. The first requires trades to close within the same 5-minute interval and the second requires a 10-minute delay before the position is closed. It finds that the monthly average spreads of these cases have fallen below 3% in 2017 from nearly 10% in 2010. Once exchange fees are included, these spreads fall below 2% on average.

This paper looks at defined contribution 401(k) plans in the United States to analyze whether or not participants have plans with better plan characteristics defined in this study by paying more for administration services, advisory services, and investments. By collecting and analyzing Form 5500 and audit data, I find that there is no relation between how much a plan and its participants are paying for recordkeeping, advisory, and investment fees and the analyzed characteristics of the plan that they receive in regards to active/passive allocation, revenue share, and the performance of the funds.

This report is a summary of a long-term project completed by Ido Gilboa for his Honors Thesis. The purpose of this project is to determine if an arbitrage between different crypto-currency exchanges exists, and if it is possible to acts upon such triangular arbitrage. Bitcoin, the specific crypto-currency this report focuses on, has become a household name, yet most do not understand its origin and patterns. The report will detail the process of collecting data from different sources, manipulating it in order to run the algorithms, explain the meaning behind the algorithms, results and important statistics found, and conclusion of the project. In addition to that, the report will go into detail discussing financial terms such as triangular arbitrage as well as information system concepts such as sockets and server communication. The project was completed with the assistance of Dr. Sunil Wahal and Dr. Daniel Mazzola, professors in the W.P. Carey School of business. This project has been stretched over along period of time, spanning from early 2013 to fall of 2015.

Shareholder Activism is a mechanism by which investors who hold a significant but

non-majority percentage of a company’s stock, exercise their voting rights, participate in

corporate governance and influence operational decisions of target companies. The

purpose is improve corporate governance, increase firm performance and boost share

-holders’ returns. Existing studies of shareholder activism, based largely in mature

capital markets like the US, come to different conclusions regarding its impact on firm

performance.

In this paper, I collect data on shareholder activism events in the China A Share

market between 2006 and 2016. The sample includes 60 companies targeted by 42

activist investors over this period. I find that institutional investors, typically industrial

capital and private funds, playing an increasingly important role in corporate governance

of Chinese listed companies through activism. The disclosure of the holdings of activists

results in large gains in the target firm. I also find subsequent improvements in long

-term operational performance of target firms. Activist investors in China focus on

smaller targets and those characterized by higher agency costs and lower operating

performance. Activists appear to be largely concerned with improvements in business

strategy and M&A activity. Non-hostile behavior is more likely to be related to successful

activism in China. In addition to statistical evidence, I present case studies of the

“BaoWan dispute” and the activist investment of Butterfly Capital in two firms,

“Guonong” and “Xiuqiang”. The case studies highlight the mechanism employed by these

firms to influence performance.

I conclude with policy recommendations and direction for further research.

This dissertation is a collection of three essays relating household financial obligations to asset prices. Financial obligations include both debt payments and other financial commitments.

In the first essay, I investigate how household financial obligations affect the equity premium. I modify the standard Mehra-Prescott (1985) consumption-based asset pricing model to resolve the equity risk premium puzzle. I focus on two channels: the preference channel and the borrowing constraints channel. Under reasonable parameterizations, my model generates equity risk premiums similar in magnitudes to those observed in U.S. data. Furthermore, I show that relaxing the borrowing constraint shrinks the equity risk premium.

In the Second essay, I test the predictability of excess market returns using the household financial obligations ratio. I show that deviations in the household financial obligations ratio from its long-run mean is a better forecaster of future market returns than alternative prediction variables. The results remain significant using either quarterly or annual data and are robust to out-of-sample tests.

In the third essay, I investigate whether the risk associated with household financial obligations is an economy-wide risk with the potential to explain fluctuations in the cross-section of stock returns. The multifactor model I propose, is a modification of the capital asset pricing model that includes the financial obligations ratio as a ``conditioning down" variable. The key finding is that there is an aggregate hedging demand for securities that pay off in periods characterized by higher levels of financial obligations ratios. The consistent pricing of financial obligations risk with a negative risk premium suggests that the financial obligations ratio acts as a state variable.