Abstract

http://ssrn.com/abstract=1982463
 
 

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


Álvaro Cartea


University College London

Dimitris Karyampas


UBS AG

January 10, 2012

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

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.

Number of Pages in PDF File: 23

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

JEL Classification: C53, G12, G14, C22

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Date posted: January 10, 2012 ; Last revised: March 11, 2013

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: http://ssrn.com/abstract=1982463

Contact Information

Álvaro Cartea (Contact Author)
University College London ( email )
Gower Street
London, WC1E 6BT
United Kingdom
HOME PAGE: http://www.cartea.net
Dimitris Karyampas
UBS AG ( email )
100 Liverpool Str
London, EC2M 2RH
United Kingdom
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