Statistical Causes for the Epps Effect in Microstructure Noise

Abstract

We present two statistical causes for the distortion of correlations on high-frequency financial data. We demonstrate that the asynchrony of trades as well as the decimalization of stock prices has a large impact on the decline of the correlation coefficients towards smaller return intervals (Epps effect). These distortions depend on the properties of the time series and are of purely statistical origin. We are able to present parameter-free compensation methods, which we validate in a model setup. Furthermore, the compensation methods are applied to high-frequency empirical data from the NYSE's TAQ database. A major fraction of the Epps effect can be compensated. The contribution of the presented causes is particularly high for stocks that are traded at low prices.

Fourier instantaneous estimators and the Epps effect

“…Other avenues for future research involve obtaining a better understanding of the instantaneous Epps effect so that a correction for asynchrony may be applied at various time-scales, such as the correction by Chang et al [28] and Münnix et al [29], but for the case of the instantaneous correlation. Another potentially interesting area may be to apply the instantaneous correlation estimates into clustering algorithms such as the Agglomerative Super-Paramagnetic Clustering algorithm [42] to see if the variation in the intraday correlation dynamics result in different market states compared to the static viewpoint traditionally used.…”

“…This downward bias in the Epps effect is caused by the fact that the underlying co-variation is extracted when the asynchronous observations overlap [ 29 ]. There are several methods to correct for this in the case of integrated covariances such as using the Hayashi-Yoshida estimator [ 7 ], directly accounting for the non-overlapping effects at a particular time-scale [ 28 , 29 ], or simply investigating larger time-scales [ 24 ]. In the case of the instantaneous estimates, it is not clear how the first two correction methods can be applied.…”

“…Here we are interested in comparing the Malliavin-Mancino [9] and the Cuchiero-Teichmann [14] Fourier instantaneous estimators and understanding the impact of their cutting frequencies to gain insight into the impact of the Epps effect [21] on the instantaneous estimators. The Epps effect is the decay of correlations as the sampling intervals decrease and there is an abundance of literature investigating the causes (see [22][23][24][25][26]) and corrections (see [7,[27][28][29][30]), but all in the case of the integrated correlation. To the best of my knowledge, apart from the work by Mattiussi and Iori [31], the impact on the instantaneous correlation caused by the Epps effect has not been explored.…”

A Simple Microstructure Return Model Explaining Microstructure Noise and Epps Effects

“…Figure A1 illustrates the accuracy of the power law approximation (A.5) transposed in the main text as expression (12). One can observe a relative error of no more than 1.4% even for m = 1.…”

“…However, there is still no theoretical model that can account simultaneously for the four mentioned stylized facts (see however Ref. [12] which emphasizes that the asynchrony of trades as well as the decimalization of stock prices are large contributors to the Epps effect. This paper also contains a review of previous papers attempting to explain the Epps effect).…”