Three Essays in Financial Economics Open Access
Noh, Joonki (2015)
Published
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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