Causality effects in return volatility measures with random times

We provide a structural approach to identify instantaneous causality effects between quote-to-quote durations and stock price volatility. So far, in the literature, instantaneous causality effects have either been excluded or cannot be identified separately from Granger type causality effects. By giving explicit moment conditions for observed returns over (random) duration intervals, we are able to identify the instantaneous causality effect where news events drive both surprises in durations and surprises in volatilities. We conclude that instantaneous volatility forecasts for, e.g., IBM stock returns must be decreased by as much as 40% when not havingseen the next quote before its (conditionally) median time. For less liquidly traded stocks at NYSE this e®ect is even stronger. Also, instantaneous volatilities are found to be much higherthan indicated by standard volatility assessment procedures. Finally, the documented causality effect has significant impact on statistical inference for tick-by-tick data.

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