Two Essays in Financial Economics Restricted; Files Only

Wang, Zhenping (Summer 2018)

Permanent URL: https://etd.library.emory.edu/concern/etds/cf95jb53r?locale=en
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Abstract

This dissertation explores new aspects of two empirical issues in financial economics: earnings predictability and informed trading. In the first essay (“Forecasting earnings from early announcers: a latent factor approach”), I propose a new method to predict non-announcing firms' earnings news using the cross section of all available early announcers' earnings news, the number of which can be as large as thousands. The method assumes common latent factors driving the earnings news of non-announcing firms and early announcers and thus efficiently reduces the dimension of announced earnings. Empirical tests show that the extracted measure strongly predicts the earnings surprise and the earnings announcement return with both statistical and economic significance. A long-short trading strategy based on the extracted information realizes a 10% alpha annually, indicating a delayed reaction of investors. The return predictability is stronger for small firms or firms with less investor attention. Controlling a series of documented information channels has little impact on the predictive power of this extracted measure. In the second essay (“Option trading leverage and stock returns”), I construct a new measure to capture informed trading in the equity option market. Informed investors choose optimal leverage as a function of risk and cost. In the option market, they establish the chosen exposure using options of low leverage which are more liquid. On the other hand, noise traders prefer options of high leverage which have more lottery-like payoff. Thus, I examine the volume-weighted average of option leverage named Option Trading Leverage Ratio (OTLR). Portfolios with the lowest OTLR underperform portfolios with the highest OTLR by 1.28% monthly or 15% annually. The predictive relationship between OTLR and earnings-related information indicates that better skills in processing public information contribute to the advantage of informed option investors. Empirical findings are consistent with low OTLR capturing negative informed option trading due to the short-sale constraints of the stock market.

Table of Contents

Table of Contents

                Page

First Essay: 

Forecasting Earnings from Early Announcers: A Latent Factor Approach

1. Introduction                                          2

2. Methodology                                                    7                                                             

3. Data and summary statistics                            11                                                            

4. Empirical tests                                                14                                                            

5. Conclusion                                                      22

                                                                

Second Essay: 

Option Trading Leverage and Stock Returns

1. Introduction                                                   24                                                             

2. Data and variables                                          30                                                            

3. Option trading leverage ratio and stock returns 38                                                                   

4. Option trading leverage ratio and earnings        45                                                                   

5. Conclusions                                                    48                                                                   

References                                                         50                                                                   

Tables                                                                56                                                                   

Figures                                                              85                                                                   

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