Estimating the spot covariation of asset prices – statistical theory and empirical evidence

  • 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 parametric spectral covariance estimates. The latter originate from a local method of moments (LMM) which recently has been introduced by Bibinger et al. (2014). We extend the LMM estimator to allow for autocorrelated noise and propose a method to adaptively infer the autocorrelations from the data. We prove the consistency and asymptotic normality of the proposed spot covariance estimator. Based on extensive 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 betas in normal but also extreme-event 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.

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Metadaten
Author:Markus Bibinger, Nikolaus HautschORCiDGND, Peter MalecGND, Markus Reiß
URN:urn:nbn:de:hebis:30:3-351099
URL:http://ssrn.com/abstract=2507714
DOI:https://doi.org/10.2139/ssrn.2507714
Parent Title (English):Center for Financial Studies (Frankfurt am Main): CFS working paper series ; No. 477
Series (Serial Number):CFS working paper series (477)
Publisher:Center for Financial Studies
Place of publication:Frankfurt, M.
Document Type:Working Paper
Language:English
Year of Completion:2014
Year of first Publication:2014
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2014/10/20
Tag:intraday (co-)variation risk; local method of moments; smoothing; spot covariance
Issue:October 2014
Page Number:56
HeBIS-PPN:351157131
Institutes:Wirtschaftswissenschaften / Wirtschaftswissenschaften
Wissenschaftliche Zentren und koordinierte Programme / Center for Financial Studies (CFS)
Dewey Decimal Classification:3 Sozialwissenschaften / 33 Wirtschaft / 330 Wirtschaft
JEL-Classification:C Mathematical and Quantitative Methods / C1 Econometric and Statistical Methods: General / C14 Semiparametric and Nonparametric Methods
C Mathematical and Quantitative Methods / C3 Multiple or Simultaneous Equation Models / C32 Time-Series Models; Dynamic Quantile Regressions (Updated!)
Sammlungen:Universitätspublikationen
Licence (German):License LogoDeutsches Urheberrecht