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.

Education:

Ph.D. in Finance, University of Florida (2018-Present)
B.S. in Mathematics & Economics, New York University Abu Dhabi (2014-2018)

Research Interests:
Financial Intermediation, Banking, Investments, Mutual Funds, ETFs

Skills:
Machine Learning, Natural Language Processing, Textual Analysis

Python, SAS, Stata 

Curriculum Vitae (PDF) [Updated: 19 Apr 2024]

The Long and Short of U.S. Bank Regulations:
From the Great Depression to the 2023 Bank Failures

Job Market Paper

Presentations (* scheduled):  Frontier Risks, Financial Innovation and Prudential Regulation of Banks (J. Fin. Intermediation-CFAR-UNC-Gothenburg Conference)*, Eastern Finance Association, Southwestern Finance Association, International Symposium for Finance, Banking and Insurance (3rd ISFBI)*, University of Florida (Warrington College of Business), Issues in Financial Markets and Banking (IFMB) Conference 

Seminars (* scheduled): Louisiana State University (E. J. Ourso College of Business), Monash University (Monash Business School), Université du Québec à Montréal (ESG UQAM), University of Technology Sydney (UTS Business School)

Abstract: Leveraging a unique century-long dataset of U.S. bank balance sheets and stock prices, I uncover a dichotomy of how bank regulation impacts financial intermediaries in the short and long run. I introduce a novel Bank Regulation Index (BRI) based on historical newspaper articles. In the short term, regulations are costly and perceived as bad news by stock market investors, while a Machine Learning analysis of news texts reveals that deregulations consistently get positive media coverage. Despite such short-term costs, aggregate and bank-level evidence demonstrate that regulations make banks safer and more profitable in the long term. I show that the BRI predicts future banking crises over and above well-established predictors such as credit growth, mostly due to gauging deregulations 5-10 years before crises. Decomposing the BRI into intuitive topics using the LDA algorithm reveals that Lending regulations matter the most for crisis predictability. Finally, using Earnings Calls transcripts, I measure bank-level exposure to Lending regulation - by applying LDA trained on the Federal Register - and show that it produces sizeable alphas. A long-short portfolio of the least and most exposed banks generates a monthly return of 0.84% and an alpha of up to 0.75%.

The Glass-Steagall Act and Bank Stock Market Speculation

with Gustavo Cortes & Marc Weidenmier

Presentations (incl. scheduled, * co-author presentations): Federal Reserve Monetary and Financial History Workshop  (Federal Reserve Bank of St. Louis), International Macro History Online Seminar (IMHOS),  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. 

Partisanship in Mutual Fund Portfolios

Presentation(s):  University of Florida (Warrington College of Business), Financial Management Association 2021, American Finance Association 2022 (Poster Session)

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). 

Active-Passive Investor Migration

with Mark Flannery & Simon Taipliadis

Presentation(s): University of Florida (Feb 2023)

This work-in-progress is explores the migration of investors from actively managed funds  to passive alternatives such as Index Funds and Exchange-Traded Funds.

Instructor:

Equity and Capital Markets (Fall 2021) 

Teaching Assistant:

Equity and Capital Markets (Spring 2021)

Capital Structure and Risk Management (Fall 2020)

Financial Management (Spring 2020)