A Simple Approximate Long-Memory Model of Realized Volatility

Posted: 23 Mar 2009

See all articles by Fulvio Corsi

Fulvio Corsi

University of Pisa - Department of Economics; City University London

Date Written: Spring 2009


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: C13, C22, C51, C53, high-frequency data, long-memory models, realized volatility, volatility forecast

Suggested Citation

Corsi, Fulvio, A Simple Approximate Long-Memory Model of Realized Volatility (Spring 2009). Journal of Financial Econometrics, Vol. 7, Issue 2, pp. 174-196, 2009, Available at SSRN: https://ssrn.com/abstract=1365738 or http://dx.doi.org/nbp001

Fulvio Corsi (Contact Author)

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City University London ( email )

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