Statistics and Data Science Seminar
Prof. Dacheng Xiu
University of Chicago
Econometric analysis of multivariate realised QML: estimation of the covariation of equity prices under asynchronous trading
Abstract: Estimating the covariance between assets using high frequency data is challenging due to market
microstructure effects and asynchronous trading. In this paper we develop a multivariate realised
quasi-likelihood (QML) approach, carrying out inference as if the observations arise from an asynchronously
observed vector scaled Brownian model observed with error. Under stochastic volatility
the resulting realised QML estimator is positive semi-definite, uses all available data, is consistent and
asymptotically mixed normal. The quasi-likelihood is computed using a Kalman filter and optimised
using a relatively simple EM algorithm which scales well with the number of assets. We derive the
theoretical properties of the estimator and prove that it achieves the efficient rate of convergence. The
estimator is also analysed using Monte Carlo methods and applied to equity data with varying levels
of liquidity.
Wednesday April 30, 2014 at 4:00 PM in SEO 636