Uncovering Long-Run Economic Relationships in High-Frequency Financial Data

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9730440 Bollerslev This project enhances the ability of researchers to extract useful information about important economic phenomena from high-frequency financial data. The increased availability of intraday financial data has spurred a tremendous growth in empirical research on the cross-sectional and intertemporal dependencies across financial instruments and markets. However, only recently has it become clear that the analysis of such high-frequency data necessitates the introduction of novel modeling paradigms relative to the standard methodologies employed at the daily and lower frequencies. The reliance on conventional time series techniques invariably results in the intraday-specific features dominating the inferred statistical properties of the observed high-frequency data, whereas any evidence concerning longer-run dependencies tend to be distorted or disappear altogether. These facts have effectively divorced the empirical studies of high-frequency data from the remainder the literature, and a near dichotomy has arisen between so-called microstructure studies and the more mainstream empirical literature in asset pricing finance. This project bridges this gap by developing new econometric time series models and tools and using these to improve our understanding of the type of information that induces dramatic price responses, and the forces shaping the intensity of price movements and their relation to underlying market microstructure. The empirical research is based on a long time span of intradaily exchange and interest rates. It provides a direct window to the market expectations and the importance of macroeconomic announcements across different policy regimes. The project also develops new and more accurate risk measurements based on high-frequency data and these should have immediate practical implications for the management and monitoring of financial market risks. The general results of the project should be of relevant to applied macroeconomists, time series econo metricians, financial researchers, regulators, and practitioners alike. ??