Matching Items (25)
Description
Schennach (2007) has shown that the Empirical Likelihood (EL) estimator may not be asymptotically normal when a misspecified model is estimated. This problem occurs because the empirical probabilities of individual observations are restricted to be positive. I find that even the EL estimator computed without the restriction can fail to be asymptotically normal for misspecified models if the sample moments weighted by unrestricted empirical probabilities do not have finite population moments. As a remedy for this problem, I propose a group of alternative estimators which I refer to as modified EL (MEL) estimators. For correctly specified models, these estimators have the same higher order asymptotic properties as the EL estimator. The MEL estimators are obtained by the Generalized Method of Moments (GMM) applied to an exactly identified model. The simulation results provide promising evidence for these estimators. In the second chapter, I introduce an alternative group of estimators to the Generalized Empirical Likelihood (GEL) family. The new group is constructed by employing demeaned moment functions in the objective function while using the original moment functions in the constraints. This designation modifies the higher-order properties of estimators. I refer to these new estimators as Demeaned Generalized Empirical Likelihood (DGEL) estimators. Although Newey and Smith (2004) show that the EL estimator in the GEL family has fewer sources of bias and is higher-order efficient after bias-correction, the demeaned exponential tilting (DET) estimator in the DGEL group has those superior properties. In addition, if data are symmetrically distributed, every estimator in the DGEL family shares the same higher-order properties as the best member.
ContributorsXiang, Jin (Author) / Ahn, Seung (Thesis advisor) / Wahal, Sunil (Thesis advisor) / Bharath, Sreedhar (Committee member) / Mehra, Rajnish (Committee member) / Tserlukevich, Yuri (Committee member) / Arizona State University (Publisher)
Created2013
Description
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.
ContributorsKang, MinJeong (Author) / Aragon, George O. (Thesis advisor) / Hertzel, Michael G (Committee member) / Boguth, Oliver (Committee member) / Arizona State University (Publisher)
Created2013
Description
This paper examines dealers' inventory holding periods and the associated price markups on corporate bonds from 2003 to 2010. Changes in these measures explain a large part of the time series variation in aggregate corporate bond prices. In the cross-section, holding periods and markups overshadow extant liquidity measures and have significant explanatory power for individual bond prices. Both measures shed light on the credit spread puzzle: changes in credit spread are positively correlated with changes in holding periods and markups, and a large portion of credit spread changes is explained by them. The economic effects of holding periods and markups are particularly sharp during crisis periods.
ContributorsQian, Zhiyi (Author) / Wahal, Sunil (Thesis advisor) / Bharath, Sreedhar (Committee member) / Coles, Jeffrey (Committee member) / Mehra, Rajnish (Committee member) / Arizona State University (Publisher)
Created2012
Description
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.
ContributorsAziz, Julian (Author) / Wahal, Sunil (Thesis director) / Bharath, Sreedhar (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / Department of Finance (Contributor)
Created2015-05
Description
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.
ContributorsGilboa, Ido (Author) / Wahal, Sunil (Thesis director) / Mazzola, Daniel (Committee member) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
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.
ContributorsHebert, Troy Thomas (Author) / Boguth, Oliver (Thesis director) / Budolfson, Arthur (Committee member) / Hoyt, Jeffrey (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor)
Created2013-05
Description
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.
ContributorsLiu, Jeremy J (Author) / Wahal, Sunil (Thesis director) / Bharath, Sreedhar (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / School for the Future of Innovation in Society (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
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.
ContributorsToumbs, Jason David (Author) / Boguth, Oliver (Thesis director) / Schreindorfer, David (Committee member) / Department of Finance (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
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.
ContributorsNowicki, Gregory Arthur (Author) / Wahal, Sunil (Thesis director) / Simonson, Mark (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
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.
ContributorsWymbs, Michael (Author) / Aragon, George (Thesis advisor) / Tserlukevich, Yuri (Committee member) / Boguth, Oliver (Committee member) / Arizona State University (Publisher)
Created2021