Testing for Market Microstructure Effects in Intraday Volatility: a Reassessment of the Tokyo FX Experiment

28 Pages Posted: 29 Jun 2000 Last revised: 10 Oct 2010

See all articles by Torben G. Andersen

Torben G. Andersen

Northwestern University - Kellogg School of Management; National Bureau of Economic Research (NBER); Aarhus University - CREATES

Tim Bollerslev

Duke University - Finance; Duke University - Department of Economics; National Bureau of Economic Research (NBER)

Ashish Das

affiliation not provided to SSRN

Date Written: July 1998

Abstract

This paper develops mew robust inference procedures for analyzing the intraday return volatility patterns that constitute a focal point of much market microstructure theory. Our empirical analysis is motivated by the recent lifting of trading restrictions in the interbank foreign exchange (FX) market for Japanese banks during the Tokyo lunch period. Ito, Lyons, and Melvin (1998) (ILM) argue that this deregulation resulted in a highly significant shift in the volatility pattern across the entire Japanese trading day, indicating that private information is an important component of the price formation process in the FX market. In contrast, our robust analysis finds no evidence for any discernible change in the pattern outside of the Tokyo lunch period. Moreover, we document that the standard variance-ratio methodology inference in this high-frequency data context.

Suggested Citation

Andersen, Torben G. and Bollerslev, Tim and Das, Ashish, Testing for Market Microstructure Effects in Intraday Volatility: a Reassessment of the Tokyo FX Experiment (July 1998). NBER Working Paper No. w6666. Available at SSRN: https://ssrn.com/abstract=226358

Torben G. Andersen (Contact Author)

Northwestern University - Kellogg School of Management ( email )

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Aarhus University - CREATES ( email )

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Tim Bollerslev

Duke University - Finance ( email )

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Duke University - Department of Economics

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National Bureau of Economic Research (NBER)

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Ashish Das

affiliation not provided to SSRN

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