A Multiple Indicators Model for Volatility Using Intra-Daily Data

28 Pages Posted: 5 Dec 2003 Last revised: 25 Aug 2010

See all articles by Giampiero M. Gallo

Giampiero M. Gallo

Corte dei Conti - Italian Court of Audits; University of Bologna - Rimini Center for Economic Analysis (RCEA); Universita' di Firenze - Dipartimento di Statistica, Informatica, Applicazioni "G.Parenti"

Robert F. Engle

New York University (NYU) - Department of Finance; National Bureau of Economic Research (NBER); New York University (NYU) - Volatility and Risk Institute

Multiple version iconThere are 2 versions of this paper

Date Written: November 2003

Abstract

Many ways exist to measure and model financial asset volatility. In principle, as the frequency of the data increases, the quality of forecasts should improve. Yet, there is no consensus about a true' or best' measure of volatility. In this paper we propose to jointly consider absolute daily returns, daily high-low range and daily realized volatility to develop a forecasting model based on their conditional dynamics. As all are non-negative series, we develop a multiplicative error model that is consistent and asymptotically normal under a wide range of specifications for the error density function. The estimation results show significant interactions between the indicators. We also show that one-month-ahead forecasts match well (both in and out of sample) the market-based volatility measure provided by an average of implied volatilities of index options as measured by VIX.

Suggested Citation

Gallo, Giampiero M. and Engle, Robert F., A Multiple Indicators Model for Volatility Using Intra-Daily Data (November 2003). NBER Working Paper No. w10117, Available at SSRN: https://ssrn.com/abstract=471467

Giampiero M. Gallo

Corte dei Conti - Italian Court of Audits ( email )

viale Mazzini
Roma, Roma 00195
Italy

University of Bologna - Rimini Center for Economic Analysis (RCEA) ( email )

Via Patara, 3
Rimini (RN), RN 47900
Italy

Universita' di Firenze - Dipartimento di Statistica, Informatica, Applicazioni "G.Parenti" ( email )

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Florence, 50134
Italy
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Robert F. Engle (Contact Author)

New York University (NYU) - Department of Finance

Stern School of Business
44 West 4th Street
New York, NY 10012-1126
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

New York University (NYU) - Volatility and Risk Institute ( email )

44 West 4th Street
New York, NY 10012
United States

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