Estimating the Spot Covariation of Asset Prices – Statistical Theory and Empirical Evidence

42 Pages Posted: 8 Oct 2014 Last revised: 3 Nov 2016

See all articles by Markus Bibinger

Markus Bibinger

University of Mannheim

Nikolaus Hautsch

University of Vienna - Department of Statistics and Operations Research

Peter Malec

University of Cambridge - Faculty of Economics

Markus Reiss

Humboldt University of Berlin

Multiple version iconThere are 2 versions of this paper

Date Written: October 2016

Abstract

We propose a new estimator for the spot covariance matrix of a multi-dimensional continuous semi-martingale log asset price process which is subject to noise and non-synchronous observations. The estimator is constructed based on a local average of block-wise para- metric spectral covariance estimates. The latter originate from a local method of moments (LMM) which recently has been introduced by Bibinger et al. (2014). We prove consistency and a point-wise stable central limit theorem for the proposed spot covariance estimator in a very general setup with stochastic volatilities, leverage and for general noise distributions. Moreover, we extend the LMM estimator to be robust against autocorrelated noise and propose a method to adaptively infer the autocorrelations from the data. Based on simulations we provide empirical guidance on the optimal implementation of the estimator and apply it to high-frequency data of a cross-section of NASDAQ blue chip stocks. Employing the estimator to estimate spot covariances, correlations and volatilities in normal but also unusual periods yields novel insights into intraday covariance and correlation dynamics. We show that intraday (co-)variations (i) follow underlying periodicity patterns, (ii) reveal substantial intraday variability associated with (co-)variation risk, (iii) are strongly serially correlated, and (iv) can increase strongly and nearly instantaneously if new information arrives.

Keywords: local method of moments, spot covariance, smoothing, intraday (co-)variation risk

JEL Classification: C58, C14, C32

Suggested Citation

Bibinger, Markus and Hautsch, Nikolaus and Malec, Peter and Reiss, Markus, Estimating the Spot Covariation of Asset Prices – Statistical Theory and Empirical Evidence (October 2016). Available at SSRN: https://ssrn.com/abstract=2506586 or http://dx.doi.org/10.2139/ssrn.2506586

Markus Bibinger

University of Mannheim ( email )

Mannheim, 68131
Germany

Nikolaus Hautsch

University of Vienna - Department of Statistics and Operations Research ( email )

Kolingasse 14
Vienna, A-1090
Austria

Peter Malec (Contact Author)

University of Cambridge - Faculty of Economics ( email )

Sidgwick Avenue
Cambridge, CB3 9DD
United Kingdom

Markus Reiss

Humboldt University of Berlin ( email )

Berlin, 10099
Germany

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