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Category Archives: G

Investigating the Costs of Religious Observance: Cross-Country Analysis of Islamic Banking

By Myla Swallow and Richard Vargo

This study regresses key variables that influence the profitability of Conventional and Islamic banks as measured by Return on Average Assets, to determine the impact of Islamicity on the profitability of the banks in a given country. The study compares 36564 banks in 77 countries belonging to both Islamic and non-Islamic countries. We  find that Islamic banks have higher operating costs and overall experience lower return on average assets.

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Advisors: Professor Kent Kimbrough, Professor Michelle Connolly | JEL Codes: F30; G21; Z12

The Impact of Post-IPO Private Equity Ownership on Long-Term Company Performance

By Maria Suhail and Cipriano Echavarría

This thesis contributes to existing knowledge of private equity (PE) by analyzing the
impact of PE ownership post-IPO upon the long-term performance of companies. It considers whether companies perform better when PE funds maintain their ownership stakes post-IPO and whether this performance is also impacted by the degree of ownership that is maintained after IPO. This study uses stock performance (measured by cumulative excess stock returns) as a proxy for long-run company performance. The paper constructs and analyzes a sample of 487 companies that underwent an IPO between 2004 and 2012 to determine the implications of the maintenance and level of PE ownership by analyzing the performance of these companies for six years post-IPO. Results suggest that PE ownership post-IPO positively impacts long-term stock performance of companies. Duration and degree of PE ownership post-IPO are also important determinants of long-run performance likely due to the positive signal that continued PE ownership sends to outside investors about the quality of the company, the information asymmetry that exists between public and private markets and that PE firms are experienced managers that add value to companies.

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Advisors: Professor David Robinson, Professor Michelle Connolly | JEL Codes: G11, G14, G24

Social Capital and Financial Development after Economic Shocks: Evidence from Italy after the Financial Crisis of 2007-2009

By Sujay Rao & Ethan Lampert

Like traditional forms of capital, social capital – an intangible measure of an individual’s social networks, trust in institutions, and participation in civic life – has implications for personal and financial behavior. Individuals from educated, well established backgrounds with fruitful family ties may be more amenable to opening new lines of credit or investing in stock markets due to their trust in and connectedness with society. But what happens after a major economic shock, such as the financial crisis of 2008? Using Italy as a case study and panel data from the Survey of Household Income and Wealth, we find that social capital has significant effects on an individual’s credit card usage, informal borrowing, and choice to invest in securities.

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Advisors: Professor Grace Kim, Professor Michelle Connolly, Professor Giovanni Zanalda | JEL Codes: G01, G2, O1, D1, D14

Leverage and Varying Metrics of Firm Performance

By Preston Jiateng Huang

This paper sets out to examine the effect of leverage on company performance. Drawing on the methodology of key prior research, this study finds that leverage has a consistent negative effect on firm growth; by contrast, no such negative impact was found on return on equity. Importantly, such patterns hold throughout the entire period under study (1970-2017), during which several disruptive economic events have occurred. These results highlight the importance of selecting appropriate company performance measures when studying the effect of debt load on a firm as well as the misalignment of incentives for policymakers and company management. Other implications are also discussed.

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Advisor: Professor Kyle Jurado | JEL Codes: G24; G31; G32

Wrangling the Herd: A Cross-Cultural and Cross-Industry Approach to Herding Market Behavior

By Tyler Fenton and Jarred Kotzin

The traditional efficient market hypothesis serves as the foundation of modern economic theory, governing the investigation of financial markets. While this premise assumes all investors are rational and all information is immediately incorporated into markets, this paper explores herding behavior – a central tenet of behavioral finance that explains the apparent inefficiencies of financial markets. Utilizing return data from the past 10 years from eight exchanges around the world, segmented into 10 industry classes as well as a broad market index, we compare levels of herd behavior using return dispersion proxies. We find significant evidence of herding in nearly all exchanges and all industries included in the study and the degree of this herd behavior varies across industries in different countries. Overall, we find support for the behavioral finance principle of herding and conclude that certain cultural or non cultural factors affect this activity differently in various countries and industries.

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Advisors: Professor Connel Fullenkamp | JEL Codes: G4, G14, G15

Is Smart Money Smart? The Costs of Hedge Funds Trading Market Anomalies

By Matthew J. Farrell

Do hedge funds earn statistically significant premia on common factor trading strategies after trading costs are accounted for? Furthermore, what is the gap between what a hedge fund would earn and the paper portfolios that they hold? I answer this question by using the latest cutting-edge methodology to estimate trading costs for major financial market anomalies. This methodology uses the familiar asset-pricing Fama-MacBeth procedure to compare the on-paper compensation to factor exposures with those earned by hedge funds. I find that the typical hedge fund does not earn profits to value or momentum, and and low returns to size.

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Advisor: Professor Brian Weller | JEL Codes: G12; G14; G23;

Prediction in Economics: a Case Study of Economists’ Views on the 2008 Financial Crisis

By Weiran Zeng

Prediction in economics is the focal point of debate for the future of economics, ever since economists were burdened with the failure to “predict” the 2008 Financial Crisis. This paper discusses positions held by philosophers and economic methodologists regarding what kinds of predictions there are and creates a taxonomy of prediction. Through evaluation of those positions, this paper presents different senses of prediction that can be expected of economics, and assess economists’ reflections according to those senses.

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Advisor: Kevin Hoover | JEL Codes: B41, N1, G17

Evaluating Asset Bubbles within Cryptocurrencies using the LPPL Model

By Rafal Rokosz

The advent of blockchain technology has created a new asset class named cryptocurrencies that have experienced tremendous price appreciation leading to speculation that the asset class is experiencing an asset bubble. This paper examines the novelty and functionality of cryptocurrencies and potential factors that may lead to conclude the existence of an asset bubble. To empirically evaluate whether the asset class is experiencing an asset bubble the LPPL model is used. The LPPL model was able to successfully identify two of the four crashes within the data set signifying that cryptocurrencies are within an asset bubble.

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Advisors: Ed Tiryakian and Grace Kim | JEL Codes: G12, Z00, C60

Effect of Sentiment on Bitcoin Price Formation

By Brian Perry-Carrera

With the recent growth in the investment of cryptocurrencies, such as bitcoin, it has become increasingly relevant to understand what drives price formation. Given that investment in bitcoin is greatly determined by speculation, this paper seeks to find the econometric relationship between public sentiment and the price of bitcoin. After scraping over 500,000 tweets related to bitcoin, sentiment analysis was performed for each tweet and then aggregated for each day between December 1st, 2017 and December 31st, 2017. This study found that both gold futures and market volatility are negatively related to the price of bitcoin, while sentiment demonstrates a positive relationship.

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Advisor: Grace Kim | JEL Codes: G12, G41, Z00

Multi-Horizon Forecast Optimality Based on Related Forecast Errors

By Christopher G. MacGibbon

This thesis develops a new Multi-Horizon Moment Conditions test for evaluating multi-horizon forecast optimality. The test is based on the variances, covariances and autocovariances of optimal forecast errors that should have a non-zero relationship for multi-horizon forecasts. A simulation study is conducted to determine the test’s size and power properties. Also, the effects of combining the Multi-Horizon Moment Conditions test and the well-known Mincer-Zarnowitz and zero autocorrelation tests into one forecast optimality test are examined. Lastly, an empirical study evaluating forecast optimality for four multi-horizon forecasts made by the Survey of Professional Forecasters is included.

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Advisors: Andrew Patton, Grace Kim and Kent Kimbrough | JEL Codes: G1, G17, G00

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