Liquidity-Based Estimation of Spot Volatility Under Microstructure Noise

47 Pages Posted: 5 Apr 2008 Last revised: 19 Jan 2010

Date Written: November 1, 2009

Abstract

Recent literature on realized volatility suggests that the observed price process of an asset may be decomposed into two parts: the unobservable, efficient price process and microstructure noise. In this article we present a methodology to sequentially estimate spot volatility from noisy data by separating these components. We use different liquidity-based measures, traded volume and quoted spread, for the noise variance of single price observations. Nonlinear Kalman filters provide us with sequential estimates of the unobservable price process and its parameters. Our approach is implemented in a continuous-discrete state space model to cope with irregular trading frequencies.

Keywords: Volatility Estimation, Realized Volatility, Bayesian Parameter Estimation, Non-linear Kalman Filter, High Frequency Data, Market Microstructure

JEL Classification: C22, C53

Suggested Citation

Grothe, Oliver and Müller, Christoph, Liquidity-Based Estimation of Spot Volatility Under Microstructure Noise (November 1, 2009). Available at SSRN: https://ssrn.com/abstract=1116753 or http://dx.doi.org/10.2139/ssrn.1116753

Oliver Grothe

KIT ( email )

Kaiserstraße 12
Karlsruhe, Baden Württemberg 76131
Germany

Christoph Müller (Contact Author)

University of Cologne ( email )

Meister-Ekkehart-Strasse 11
50923 Cologne, 50937
Germany
+49 (0) 221-470-7704 (Phone)

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
358
Abstract Views
1,836
rank
117,957
PlumX Metrics