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Three Essays in Financial Economics

Noh, Joonki (2015)
Dissertation (158 pages)
Committee Chair / Thesis Advisers: Chordia, Tarun; Jegadeesh, Narasimhan
Committee Members: Shanken, Jay ; Rajgopal, Shivaram ; Barillas, Francisco
Research Fields: Economics, Finance; Business Administration, General; Business Administration, Banking
Keywords: Industry network; Information flow; Financial market; Testing asset pricing models; Risk-return tradeoff; Individual stocks; CEO; Facial expression; Market reaction
Program: Laney Graduate School, Business
Permanent url: http://pid.emory.edu/ark:/25593/pqv9z

Abstract

This dissertation covers the information dissemination in financial markets and the risk-return relationship in the cross-section of stocks. The first essay explores the information diffusion to equity markets in the framework of networks. I investigate whether the number of connections that an industry has in the network of inter-industry trade affects the speed of information flow to the industry. I find that the information flows more slowly to central industries from their related (=customer and supplier) industries than to peripheral industries from their related industries. The strong return predictability to central industries from related industries leads to highly profitable trading strategies whose risk-adjusted returns are 7.0% to 7.9% per annum. To explain this finding, I argue that investors who invest in central industries need to process more complicated information about related industries, slowing down the information flow to central industries. I find evidence that the sell-side analysts of central industries also face more complicated information about related industries, slowing down their processing new information about related industries. The network framework helps to identify an unknown and unique anomaly and to better understand potential sources of anomalies. The second essay develops an IV methodology to test asset pricing models using individual stocks as test assets. We obtain consistent estimates of risk premiums, and simulation indicates that the associated tests are well specified in small samples. When testing three asset pricing models known to be successful in the literature when they were tested with characteristics-sorted portfolios as test assets, we find weak evidence that their factor risks are reliably priced in the cross-section. The third essay investigates whether the facial expressions in CEOs' televised interviews can convey information about firms to investors and whether investors understand and react to it. We find evidence that negative facial expressions are correlated with CARs and turnover over the next one to two days after air dates. We also find that negative facial expressions are associated with firms' one-quarter-ahead earnings. Taken together, it presents the first evidence in financial economics that CEOs' facial expressions in their televised interviews can be a channel through which value-relevant information is disseminated.

Table of Contents

Industry Networks and the Speed of Information Flow ................................................1
Introduction ......................................................................................................................2
Related Literature .............................................................................................................7
Methodology, Data, and Preliminary Analyses ...............................................................9
Methodology for the Industry Network ........................................................................9
Other Data Sources and Variables ..............................................................................12
Preliminary Analyses..................................................................................................14
Empirical Results ...........................................................................................................16
Return Cross-predictability ........................................................................................17
Quantifying the Economic Magnitudes ......................................................................19
Potential Economic Mechanism .................................................................................21
Distinction from Existing Anomalies .........................................................................25
Change in Institutional Co-ownership ........................................................................29
Conclusions ....................................................................................................................30
Technical Appendix .......................................................................................................32
Details on Constructing the Industry Network ...........................................................32
Empirical Tests of Asset Pricing Models with Individual Stocks ................................33
Introduction ....................................................................................................................34
Methodology ..................................................................................................................36
Small Sample Properties ................................................................................................42
Return Generating Processes ......................................................................................42
Simulation Experiments: Parameters and Methodology ............................................43
EIV Bias .....................................................................................................................45
Small Sample Distribution of the Test Statistic .........................................................47
Empirical Results ...........................................................................................................47
Data.............................................................................................................................47
CAPM and Fama-French Three-factor Model ...........................................................48
Production-based Asset Pricing Model ......................................................................52
Liquidity-adjusted CAPM ..........................................................................................55
Strength of Instruments ..............................................................................................59
Conclusion ......................................................................................................................61
Technical Appendix .......................................................................................................63
Proofs of Propositions ...............................................................................................63
Simulation Parameters ................................................................................................73
Innovations in Illiquidity Costs ..................................................................................74
Proof of Proposition 3 ................................................................................................75
Information in CEO's Facial Expressions: A First Look ............................................76
Introduction ....................................................................................................................77
Quantifying Emotions based on Facial Expressions ......................................................79
Video Sample Selection .................................................................................................81
Empirical Results ...........................................................................................................82
Preliminary Results ....................................................................................................82
Facial Expressions and Cumulative Abnormal Returns .............................................85
Facial Expressions and Cumulative Abnormal Turnover ..........................................88
Facial Expressions and Future Earnings.....................................................................90
Discussions .................................................................................................................91
Conclusion ......................................................................................................................92
Technical Appendix .......................................................................................................93
Variable Definition .....................................................................................................93
Links to Sample Videos..............................................................................................95
Screenshots from the Videos with the Most Extreme Facial Expression Scores .......96
Appendices .........................................................................................................................99
Tables .............................................................................................................................99
Figures ..........................................................................................................................133
References ........................................................................................................................140

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