OSAMA M. KHAWAR
Finance Ph.D. Candidate, University of Florida
I am a Job Market Candidate at the UF Warrington College of Business, under the supervision of Professor Mark Flannery. My Job Market Paper uses a combination of Machine Learning/Textual Analysis Methods on a century of newspaper articles to study the effects of bank regulation in the US.
I am on the 2023-2024 Job Market.
Ph.D. in Finance, University of Florida (2018-Present)
B.S. in Mathematics & Economics, New York University Abu Dhabi (2014-2018)
Financial Intermediation, Banking, Investments, Mutual Funds, ETFs
Machine Learning, Natural Language Processing, Textual Analysis
Python, SAS, Stata
Job Market Paper
Presentations (* scheduled): University of Florida (Sep 2023), Louisiana State University - E. J. Ourso College of Business (Nov 2023), Contemporary Issues in Financial Markets and Banking (Jan 2024)*, Southwestern Finance Association (Feb 2024)*
Abstract: Exploiting a unique century-long dataset of U.S. bank balance sheets and stock prices, I study how bank regulation impacts financial intermediaries both in the short- and long-run. I begin by constructing a novel Bank Regulation Index (BRI) from historical newspaper articles. The index quantifies cycles, from the Great Depression to the 2023 bank failures, in which crises prompt regulations, instill stability, and set the stage for subsequent deregulations. Short-term analysis of news text, using FinBERT, reveals that deregulations consistently receive positive media coverage. Bank-level evidence demonstrates that, while regulations are costly in the short-term, they make the banks safer and profitable in the long-term. The BRI provides predictive power of future crises over established predictors such as credit growth. Decomposition into different regulatory topics, using Latent Dirichlet Allocation (LDA), shows that regulations on bank activities and consumer lending mainly drive the predictive results.
Presentations (* co-author presentations): Midwest Macroeconomics Meeting*, Rutgers University*, Utah State University (Huntsman)*
Abstract: The Glass-Steagall Act of 1933 is one of the most influential and controversial pieces of financial regulation in U.S. history. Enforced for 66 years, the legislation was designed to restrict commercial banks from speculating in the stock market. The Act required banks to dissolve security affiliates and cap investment portfolios at 10 percent of liabilities. We test the bank speculation hypothesis by measuring bank risk using hand-collected daily stock prices and balance sheet data. The regulation significantly reduced banks' idiosyncratic volatility by one-fourth relative to the median. Banks impacted by the Act improved their stability, as shown by equity ratios and distance-to-default measures. These banks also paid higher dividend yields and extended more bank credit, possibly mitigating the credit crunch of the Great Depression. Our findings demonstrate that the Act reduced risk for commercial banks by limiting their ability to speculate in risky assets.
Presentation(s): FMA (2021), AFA 2022 (Student Poster), University of Florida (Feb 2021)
Abstract: Partisan bias in fund portfolios is the effect of fund manager’s political affiliation on portfolio allocation decisions. I study two potential manifestations of this bias: biased expectations where managers become optimistic (pessimistic) when their party comes in (goes out of) the government, and in-group favoritism where managers choose higher holdings of politically aligned firms. I find strong evidence for the biased expectations channel, using recent data that includes the effects of the 2020 Presidential election. However, contrary to past literature, I find no evidence for in-group favoritism. I also document a partisan bias in holdings of stocks exposed to politicized topics (COVID-19 and Brexit). The COVID-19 result does not carry over to earlier pandemics (H1N1, Ebola and Zika).
WORK IN PROGRESS
Equity and Capital Markets (Fall 2021)
Equity and Capital Markets (Spring 2021)
Capital Structure and Risk Management (Fall 2020)
Financial Management (Spring 2020)
Predictability Without Accuracy? Diversity, Consistency, and Earnings Predictability
by Vidhi Chhaochharia, Alok Kumar and Shiyi Zhang
Florida Finance Conference (Oct 2022)