12.1 INTRODUCTION

The relation (interrelation) between the flow of information and market uncertainty has been an important topic for research over the last half of the 20th century. More specifically, the dynamics between the flow of information and market uncertainty has been the key factor that impacts security price formation, price discovery, market participant behavior (price reaction or overreaction), and overall market stability. Nowadays, researchers agree that variation in the frequency of information arrivals drives volatility and volatility clustering of security prices (Ross, 1989; Jones, Kaul, and Lipson, 1994; Ané; and Geman, 2000). High-frequency data availability and recent advances in modeling of heteroskedastic time-series data enable empirical researchers to address the most puzzling and intriguing feature of price volatility; namely, its strong persistence (Goodhart and O'Hara, 1997).1 Goodhart and O'Hara (1997) point out that, since the Generalized Autoregressive Conditional Heteroskedasticity ((G)ARCH) processes of Engle (1982) and Bollerslev (1986) are naturally motivated by time-varying features and, most importantly, by temporal dependences in the information arrival process, these models provide an explanation of how such temporal dependence occurs.

GARCH-type empirical models do not, however, provide a theoretical explanation of why volatility persists or if any, what the exact impact of information flow is on volatility. An appealing answer to these ...

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