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High-Frequency Lead-Lag Effects and Cross-Asset Linkages: A Multi-Asset Lagged Adjustment Model

Buccheri, G., Corsi, F. ORCID: 0000-0003-2683-4479 and Peluso, S. (2020). High-Frequency Lead-Lag Effects and Cross-Asset Linkages: A Multi-Asset Lagged Adjustment Model. Journal of Business & Economic Statistics, doi: 10.1080/07350015.2019.1697699

Abstract

Motivated by the empirical evidence of high-frequency lead-lag effects and cross-asset linkages, we introduce a multi-asset price formation model which generalizes standard univariate microstructure models of lagged price adjustment. Econometric inference on such model provides: (i) a unified statistical test for the presence of lead-lag correlations in the latent price process and for the existence of a multi-asset price formation mechanism; (ii) separate estimation of contemporaneous and lagged dependencies; (iii) an unbiased estimator of the integrated covariance of the efficient martingale price process that is robust to microstructure noise, asynchronous trading, and lead-lag dependencies. Through an extensive simulation study, we compare the proposed estimator to alternative approaches and show its advantages in recovering the true lead-lag structure of the latent price process. Our application to a set of NYSE stocks provides empirical evidence for the existence of a multi-asset price formation mechanism and sheds light on its market microstructure determinants. Supplementary materials for this article are available online.

Publication Type: Article
Additional Information: This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Business and Economic Statistics on 6 Jan 2020, available online: http://www.tandfonline.com/10.1080/07350015.2019.1697699
Publisher Keywords: Asynchronous trading, Cross-asset trading, Granger causality, Microstructure noise, Price discovery
Subjects: H Social Sciences > HB Economic Theory
H Social Sciences > HG Finance
Departments: School of Arts & Social Sciences > Economics
URI: https://openaccess.city.ac.uk/id/eprint/23591
[img] Text - Accepted Version
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