Date of Award:

12-2008

Document Type:

Dissertation

Degree Name:

Doctor of Philosophy (PhD)

Department:

Economics and Finance

Department name when degree awarded

Economics

Committee Chair(s)

Terry Glover

Committee

Terry Glover

Committee

Basudeb Biswas

Committee

Christopher Fawson

Committee

Dwight Israelsen

Committee

Austin Kwag

Abstract

This dissertation includes two different groups of objects in macroeconomics and financial economics. In macroeconomics, the aggregate investment fluctuation and its relation to an individual firm's behavior have been extensively studied for the past three decades. Most studies on the interdependence behavior of firms' investment focus on the key issue of separating a firm's reaction to others' behavior from reaction to common shocks. However, few researchers have addressed the issue of isolating this endogenous effect from a statistical and econometrical approach. The first essay starts with a comprehensive review of the investment fluctuation and firms' interdependence behavior, followed by an econometric model of lumpy investments and an analysis of the binary choice behavior of firms' investments. The last part of the first essay investigates the unique characteristics of the Italian economy and discusses the economic policy implications of our research findings.

We ask a similar question in the field of financial economics: Where does stock market volatility come from? The literature on the sources of such volatility is abundant. As a result of the availability of high-frequency financial data, attention has been increasingly directed at the modeling of intraday volatility of asset prices and returns. However, no empirical research of intraday volatility analysis has been applied at both a single stock level and industry level in the food industry.

The second essay is aimed at filling this gap by modeling and testing intraday volatility of asset prices and returns. It starts with a modified High Frequency Multiplicative Components GARCH (Generalized Autoregressive Conditional Heteroscedasticity) model, which breaks daily volatility into three parts: daily volatility, deterministic intraday volatility, and stochastic intraday volatility. Then we apply this econometric model to a single firm as well as the whole food industry using the Trade and Quote Data and Center for Research in Security Prices data. This study finds that there is little connection between the intraday return and overnight return. There exists, however, strong evidence that the food recall announcements have negative impacts on asset returns of the associated publicly traded firms.

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