Heterogeneous Information Arrivals and Return Volatility Dynamics: Uncovering the Long-Run in High Frequency Returns




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    • Andersen is from the J.L. Kellogg Graduate School of Management of Northwestern University. Bollerslev is from the University of Virginia and is a research associate at the National Bureau of Economic Research. We gratefully acknowledge the financial support provided by a research grant from the Institute for Quantitative Research in Finance (the Q-Group). Special thanks are due to Olsen and Associates for making the intradaily exchange rate quotes and Reuter's News Tape available. We have received valuable comments from Wake Epps, Clive W.J. Granger, Stephen F. Gray, J. Huston McCulloch, as well as seminar participants at the December 1996 Triangle Econometrics Workshop, the 1997 AFA Meetings in New Orleans, Academia Sinica, the Wharton School, USC, and Georgetown and York universities. We remain fully responsible for the content.


Recent empirical evidence suggests that the interdaily volatility clustering for most speculative returns are best characterized by a slowly mean-reverting fractionally integrated process. Meanwhile, much shorter lived volatility dynamics are typically observed with high frequency intradaily returns. The present article demonstrates, that by interpreting the volatility as a mixture of numerous heterogeneous short-run information arrivals, the observed volatility process may exhibit long-run dependence. As such, the long-memory characteristics constitute an intrinsic feature of the return generating process, rather than the manifestation of occasional structural shifts. These ideas are confirmed by our analysis of a one-year time series of five-minute Deutschemark-U.S. Dollar exchange rates.