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Essays in Financial Economics by Reza Shabani a Dissertation

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Essays in Financial Economics by Reza Shabani a Dissertation Essays in Financial Economics by Reza Shabani A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Economics in the GRADUATE DIVISION of the UNIVERSITY OF CALIFORNIA, BERKELEY Committee in charge: Professor Adam Szeidl, Chair Professor Robert Anderson Professor Ulrike Malmendier Professor Martin Lettau Spring 2012 Essays in Financial Economics Copyright 2012 by Reza Shabani 1 Abstract Essays in Financial Economics by Reza Shabani Doctor of Philosophy in Economics University of California, Berkeley Professor Adam Szeidl, Chair This dissertation is comprised of two chapters, each of which contributes to the …eld of …nancial economics, particularly in the areas of behavioral and household …nance. "Corporate News, Asset Prices, and the Media" examines investor reaction to stale information using a novel data set containing a time-stamped transcript of the …nancial news network CNBC. I measure changes in stock price and trading volume at the precise time that a company is mentioned on CNBC in the 24 hours following a corporate news event, and …nd strong evidence that some investors react to stale news. There is a signi…cant increase in stock price at the precise time that a company is mentioned on CNBC following a positive news event. Surprisingly, there is also a signi…cant increase in stock price at the precise time that a company is mentioned on CNBC following a negative news event. This puzzle is not explained using observable di¤erences between positive and negative news events or their subsequent mentions. Evidence using cross-sectional variation in the number of positive and negative words suggests that media attention can in‡ate asset prices in the presence of short-sale constraints as investors with the most optimistic valuations are able to buy while those with the most pessimistic valuations are unable to sell short. "Outstanding Debt and the Household Portfolio," co-authored with my classmate Thomas A. Becker, alters a simple portfolio choice model to allow households to retire outstanding debt and realize a risk-free rate of return equal to the interest rate on that debt. Using the Survey of Consumer Finances we …nd that households with mortgage debt are 10 percent less likely to own stocks and 37 percent less likely to own bonds compared to similar households with no outstanding mortgage debt. To show that our results are not driven by irrational behavior amongst a subset of households, we construct two proxy variables for …nancial naivete. Finally we calculate the costs of non-optimal investment decisions in the presence of various forms of household debt including mortgages, home equity loans and credit card debt. We …nd that 26 percent of households should forego equity market participation on account of the high interest rates that they pay on their debt. i To my father, Mohammad ii Contents List of Figures iv List of Tables v Acknowledgements vi Introduction 1 1 Corporate News, Asset Prices, and the Media 3 1.1 Methodology and Data Sources . 7 1.1.1 Newnews ............................. 8 1.1.2 Stalenews............................. 9 1.1.3 Market reaction . 11 1.1.4 Event classi…cation . 12 1.2 News Generating Process . 12 1.2.1 News events and mentions . 13 1.2.2 Level of news coverage . 14 1.2.3 Clustering of mentions . 15 1.2.4 Sample restrictions . 15 1.3 Market Reaction to News Events and Mentions . 16 1.3.1 Price response following news events . 16 1.3.2 Market reaction to stale news . 17 1.3.3 Price response by time to mention . 21 1.3.4 Least squares regressions . 22 1.4 Determinants of Price Response to CNBC Mentions . 24 1.4.1 Di¤erences between positive and negative news . 24 1.4.2 Short-sale constraints and attention . 26 1.4.3 Individual and institutional investors . 28 1.4.4 Cross-sectional regressions . 29 1.4.5 Price momentum and reversal . 34 1.5 Conclusions ................................ 34 iii Bibliography 36 2 Outstanding Debt and the Household Portfolio 39 2.1 Portfolio Choice and Mortgage Debt . 43 2.1.1 Implications for asset market participation . 45 2.1.2 Implications for portfolio shares . 47 2.2 DataSources ............................... 50 2.3 Regression Analysis . 53 2.3.1 Empirical model and results . 53 2.3.2 Portfolio share . 62 2.3.3 Endogeneity............................ 64 2.4 Welfare Implications of Debt Retirement . 69 2.4.1 Credit cards and other sources of debt . 69 2.4.2 Costs of non-optimal bond market participation . 71 2.5 Conclusions ................................ 74 Bibliography 76 A CNBC Transcript Data 79 A.1 CNBCRecordings ............................ 79 A.2 Mapping Company Names to Securities . 80 A.3 Content Analysis of CNBC Mentions . 81 A.4 Analyst Classi…cation . 83 A.4.1 Earnings announcements . 83 A.4.2 Company-issued-guidelines . 84 B Household Portfolio Assumptions 85 B.1 Assumptions of Portfolio Choice Model . 85 B.2 Construction of After-Tax Interest Rates . 86 iv List of Figures 1.1 Market reaction for ADC Telecom following new news and stale news 5 1.2 Number of news events and subsequent mentions by time of day . 10 1.3 Price response following news events . 17 1.4 Market reaction to CNBC mentions for positive news . 18 1.5 Market reaction to CNBC mentions for negative news . 19 1.6 Price response to CNBC mentions for positive, expected and negative news.................................... 20 1.7 Price response to CNBC mentions for positive news by time to mention 21 2.1 Ratios of U.S. mortgage debt to income and assets 1985-2008Q3 . 41 2.2 Timeline of cash ‡ows from repayment of mortgage debt . 44 2.3 Bene…t to stock market participation for non-participants . 46 2.4 Life-cycle evolution of portfolio shares . 49 2.5 Annual aggregate costs of non-optimal bond market participation . 73 v List of Tables 1.1 Summary statistics for news events and mentions . 14 1.2 Price response to new news and stale news . 23 1.3 Characteristics of news events and subsequent mentions . 25 1.4 Trades and volume for events and mentions by trade size . 28 1.5 Cross-sectional regressions for price response to CNBC mentions . 31 1.6 Price momentum and reversal . 33 2.1 Characteristics of debt held by U.S. households . 40 2.2 Portfolio equity share by mortgage class . 50 2.3 Summary statistics from the Survey of Consumer Finances . 51 2.4 Equity and bond participation logit regressions . 55 2.5 Di¤erences in e¤ect of mortgage debt on stock and bond ownership . 59 2.6 Population-weighted equity and bond participation logit regressions . 60 2.7 Conditional OLS and tobit regressions of portfolio shares . 63 2.8 Regressions of equity and bond ownership controlling for …nancial naivete 66 2.9 Fixed-e¤ects logit regressions using Panel Survey of Income Dynamics 68 2.10 Stock and bond holdings by debt characteristics . 70 2.11 Annual costs of non-optimal bond market participation . 72 A.1 Dates of missing transcript data . 80 A.2 Loughran-McDonald and General Inquirer dictionaries . 82 vi Acknowledgments Without a doubt the past six years at Berkeley have been the most challenging and most rewarding of my life. For this, I owe an enormous amount of gratitude to my advisors, colleagues, friends and family. At Berkeley, I had the opportunity to learn from and collaborate with many re- markable economists. I thank my dissertation chair, Adam Szeidl, for his support, mentorship, and guidance throughout my time at Berkeley. Adam was an amazing teacher and an enlightened advisor. Whether it was providing me with …nancial sup- port or traveling from Europe on a number of occasions to attend key seminars, he always demonstrated the utmost dedication towards the progression of my research and my abilities as a scholar. I thank my dissertation committee members Robert An- derson, Ulrike Malmendier and Martin Lettau for their outstanding mentorship and their many insightful contributions to my research. Ulrike also chaired my qualifying exam along with Raj Chetty, Nancy Wallace and Alexei Tchistyi, all of whom pro- vided thoughtful comments and helpful suggestions. I’ve also bene…ted enormously from regular conversations with David Card, Stefano DellaVigna, Shachar Kariv and Terry Odean. Beginning in my fourth year, I’ve been fortunate enough to work with Wells Fargo & Co. on a retirement contribution tool as part of the Haas@Work program. The project was not only a perfect match for my interests in behavioral and household …nance, but also resulted in the launch of an actual product that has the potential to help thousands of people plan for their retirement. I thank Adam Berman for his guidance and support throughout the Haas@Work program. I especially thank Je¤ Street and Amir Zelazny from Wells Fargo Retail Retirement for their visionary work and steadfast dedication towards this endeavor. It has been an absolute pleasure to collaborate with such outstanding people on an extraordinary project. I also acknowledge those who have made my journey possible. I am forever in- debted to Carlos Dobkin, whose mentorship during my time as an undergraduate at UCSC had an enormous impact on my life and my decision to pursue a doctorate degree. I gratefully acknowledge …nancial support from the Coleman Fung Risk Man- agement Research Center, which enabled me to make great strides on a number of my research projects. I also thank the Paul and Daisy Soros Fellowship for New Ameri- cans. In addition to …nancial support, the fellowship a¤orded me the opportunity to meet many remarkable young men and women, each of whom embodies the American dream.
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