Journal of Financial Econometrics Advance Access originally published online on February 19, 2009
Journal of Financial Econometrics 2009 7(2):174-196; doi:10.1093/jjfinec/nbp001
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A Simple Approximate Long-Memory Model of Realized Volatility
University of Lugano and Swiss Finance Institute
Address correspondence to Fulvio Corsi, Institute of Finance, University of Lugano, Via Buffi 13, CH-6904, Lugano, Switzerland, or e-mail: fulvio.corsi{at}lu.unisi.ch
JEL Classification: C13, C22, C51, C53
| Abstract |
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The paper proposes an additive cascade model of volatility components defined over different time periods. This volatility cascade leads to a simple AR-type model in the realized volatility with the feature of considering different volatility components realized over different time horizons and thus termed Heterogeneous Autoregressive model of Realized Volatility (HAR-RV). In spite of the simplicity of its structure and the absence of true long-memory properties, simulation results show that the HAR-RV model successfully achieves the purpose of reproducing the main empirical features of financial returns (long memory, fat tails, and self-similarity) in a very tractable and parsimonious way. Moreover, empirical results show remarkably good forecasting performance.
KEYWORDS: high-frequency data, long-memory models, realized volatility, volatility forecast
Earlier versions of this paper were circulated and cited under the title "A Simple Long Memory Model of Realized Volatility." The author would like to thank René Garcia (the editor), the associate editor, an anonymous referee, Francesco Audrino, Giovanni Barone-Adesi, Tim Bollerslev, Michel Dacorogna, Patrick Gagliardini, Ramazan Gençay, Giampiero Gallo, Paul Lynch, Loriano Mancini, Ulrich Müller, Roberto Renò, Adrian Trapletti, Fabio Trojani, and Gilles Zumbach for helpful comments and insightful discussions.
Received July 7, 2008; revised December 31, 2008; accepted January 14, 2009
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