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Assessing the Performance of Different Volatility Estimators: A Monte Carlo Analysis

Applied Mathematical Finance, Volume 19, Issue 6, 2012, 535-552

23 Pages Posted: 10 Jan 2012 Last revised: 11 Mar 2013

Álvaro Cartea

University of Oxford; University of Oxford - Oxford-Man Institute of Quantitative Finance

Dimitris Karyampas

Bocconi University

Date Written: January 10, 2012

Abstract

We test the performance of different volatility estimators that have recently been proposed in the literature and which have been designed to deal with problems arising when ultra high-frequency data are employed: microstructure noise and price discontinuities. Our goal is to provide an extensive simulation analysis for different levels of noise and frequency of jumps to compare the performance of the proposed volatility estimators. We conclude that the MLE-F, a two-step parametric volatility estimator proposed by Cartea and Karyampas (2010), outperforms most of the well known high-frequency volatility estimators when different assumptions about the path properties of stock dynamics are used.

Keywords: volatility, high-frequency data, jumps, microstructure noise

JEL Classification: C53, G12, G14, C22

Suggested Citation

Cartea, Álvaro and Karyampas, Dimitris, Assessing the Performance of Different Volatility Estimators: A Monte Carlo Analysis (January 10, 2012). Applied Mathematical Finance, Volume 19, Issue 6, 2012, 535-552. Available at SSRN: https://ssrn.com/abstract=1982463

Álvaro Cartea (Contact Author)

University of Oxford ( email )

Mansfield Road
Oxford, Oxfordshire OX1 4AU
United Kingdom

University of Oxford - Oxford-Man Institute of Quantitative Finance ( email )

Eagle House
Walton Well Road
Oxford, Oxfordshire OX2 6ED
United Kingdom

Dimitris Karyampas

Bocconi University ( email )

Via Sarfatti, 25
Milan, MI 20136
Italy

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