Decimalization, Realized Volatility, and Market Microstructure Noise

Abstract

This paper studies empirically the effect of decimalization on volatility and market microstructure noise. We apply several non-parametric estimators in order to accurately measure volatility and market microstructure noise variance before and after the final stage of decimalization which, on the NYSE, took place in January, 2001. We find that decimalization decreased observed volatility by decreasing noise variance and, consequently, increased the significance of the true signal especially in the trade price data for the high-activity stocks. In general, however, most of the found increase in the signal-to-noise ratio is explainable by confounding and random effects. We also find that although allowing for dependent noise can matter pointwisely, it does not appear to be critical in our case where the estimates are averaged over time and across stocks. For that same reason rare random jumps are not critical either. It is more important to choose a proper data type and prefilter the data carefully.JEL Classification: C14, C19.

Extreme Volatilities, Financial Crises and L-Moment Estimations of Tail Indexes

“…Focusing this time on recent high frequency estimators of Realized Volatility (Cf. Zhang et al, 2005;Aït-Sahalia et al, 2005 andZhang, 2006;Vuorenmaa, 2008;Barndorff-Nielsen et al, 2008;Andersen et al, 2009-b;Corsi et al, 2009;Mancini, 2009;Saichev et al, 2009 and, and on other conditional low-frequency alternatives (Engle, 2002;Engle and Gallo, 2006;Engle and Rangle, 2008), it would also be of interest to replicate our studies and compare these estimators on a Tail-index basis (see Vuorenmaa, 2008). Another direction would be to consider, as in Bali and Weinbaum (2007) or in Jalal and Rockinger (2008), a conditional approach for the modelled volatility.…”

Extreme Volatilities, Financial Crises and L-Moment Estimations of Tail-Indexes

“…-Please, insert Table somewhere here -In the vein of Gonzalez-Rivera et al (2004), a natural expansion of this article will be to extend the studies to a basket of individual stocks in a true Reality Check framework (White, 2000), to preserve our results from datasnooping (see also Hansen, 2005 (Engle, 2002;Engle and Gallo, 2006;Engle and Rangle, 2008), it would also be of interest to replicate our studies and compare these estimators on a Tail-index basis (see Vuorenmaa, 2008). Another direction would be to consider, as in Bali and Weinbaum (2007) or in Jalal and Rockinger (2008), a conditional approach for the modelled volatility.…”