Volatility dynamics around information : empirical evidence from the euro/dollar currency market/

Abstract

Roughly all the previous empirical research, focusing on the information effects on volatility, has investigated the volatility dynamics during and after the release of public information. Researchers use ARCH-type or realized volatility models and they proxy public information by market news announcements. So far, studies focusing on the effect of noise or technical trading on volatility have been limited to theoretical results without any empirical evidence. Technical trading is trading based on technical signals. As a consequence, the aim of this dissertation is to answer to the following question: how does foreign exchange volatility behave, in the very short term, around public information and technical signals ? To answer to this question we study the volatility dynamics before, during and after public news announcements and technical chart pattern signals. In order to meet this objective, we implement different methodologies specific to the different chapters of the dissertation. Each chapter tries to answer to a sub-question emerging from the main question of the thesis. This thesis contributes to the empirical finance literature on intradaily exchange rate volatility as follows. First we present evidence that volatility increases in the pre-announcement period of scheduled news. Second, we show that foreign exchange dealers quoting activity reacts to news announcements and it conveys useful information. The third contribution consists in presenting a new approach to recognize technical chart patterns from a time series, and shedding light on the predictive success of the technical chart signals. Finally, the last contribution consists in the finding that technical signals, considered by economists as "noise", have a significant effect on volatility.(IAG 3)--UCL, 200