Discrete-time Volatility Forecasting with Persistent Leverage Effect and the Link with Continuous-time Volatility Modeling

34 Pages Posted: 17 Dec 2008 Last revised: 6 Apr 2010

See all articles by Fulvio Corsi

Fulvio Corsi

University of Pisa - Department of Economics

Roberto Renò

ESSEC Business School

Date Written: April 2, 2010

Abstract

We first propose a reduced-form model in discrete time for S&P500 volatility showing that the forecasting performance of a volatility model can be significantly improved by introducing a persistent leverage effect with a long-range dependence similar to that of volatility itself. We also find a strongly significant positive impact of lagged jumps on volatility, which however is absorbed more quickly.

We then estimate continuous-time stochastic volatility models which are able to reproduce the statistical features captured by the reduced-form model. We show that a single-factor model driven by a fractional Brownian motion is unable to reproduce the volatility dynamics observed in the data, while a multi-factor Markovian model is able to reproduce the persistence of both volatility and leverage effect.

The impact of jumps can instead be associated with a common jump component in price and volatility. These findings cast serious doubts on the need of modeling volatility with a genuine long memory component, while reinforcing the view of volatility being generated by the superposition of multiple factors.

Keywords: Volatility Forecasting, High Frequency Data, Leverage Effect, Jumps, Fractional Brownian Motion, Multifactor Models

JEL Classification: C13, C22, C51, C53

Suggested Citation

Corsi, Fulvio and Renò, Roberto, Discrete-time Volatility Forecasting with Persistent Leverage Effect and the Link with Continuous-time Volatility Modeling (April 2, 2010). Available at SSRN: https://ssrn.com/abstract=1316953 or http://dx.doi.org/10.2139/ssrn.1316953

Fulvio Corsi (Contact Author)

University of Pisa - Department of Economics ( email )

via Ridolfi 10
I-56100 Pisa, PI 56100
Italy

HOME PAGE: http://people.unipi.it/fulvio_corsi/

Roberto Renò

ESSEC Business School ( email )

3 Avenue Bernard Hirsch
CS 50105 CERGY
CERGY, CERGY PONTOISE CEDEX 95021
France

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
546
Abstract Views
2,178
Rank
93,307
PlumX Metrics