We study the impact of volatility on intraday serial correlation, at time scales of less than 20 minutes, exploiting a data set with all transactions on SPX500 futures from 1993 to 2001. We show that, while realized volatility and intraday serial correlation are linked, this relation is driven by unexpected volatility only, that is by the fraction of volatility that cannot be forecasted by a linear model. The impact of predictable volatility is instead found to be negative (LeBaron effect). Our results are robust to microstructure noise, and they confirm the leading economic theories on price formation.
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Article provided by Taylor and Francis Journals in its journal Quantitative Finance.