High Frequency Multiplicative Component GARCH

29 Pages Posted: 3 Nov 2008

See all articles by Magdalena E. Sokalska

Magdalena E. Sokalska

affiliation not provided to SSRN

Ananda Chanda

Morgan Stanley

Robert F. Engle

New York University - Leonard N. Stern School of Business - Department of Economics; New York University (NYU) - Department of Finance; National Bureau of Economic Research (NBER)

Multiple version iconThere are 2 versions of this paper

Date Written: August 2005

Abstract

This paper proposes a new way of modeling and forecasting intraday returns. We decompose the volatility of high frequency asset returns into components that may be easily interpreted and estimated. The conditional variance is expressed as a product of daily, diurnal and sto-chastic intraday volatility components. This model is applied to a comprehensive sample consisting of 10-minute returns on more than 2500 US equities. We apply a number of dif-ferent specifications. Apart from building a new model, we obtain several interesting fore-casting results. In particular, it turns out that forecasts obtained from the pooled cross section of companies seem to outperform the corresponding forecasts from company-by-company estimation.

Suggested Citation

E. Sokalska, Magdalena and Chanda, Ananda and Engle, Robert F., High Frequency Multiplicative Component GARCH (August 2005). NYU Working Paper No. . Available at SSRN: https://ssrn.com/abstract=1293633

Magdalena E. Sokalska (Contact Author)

affiliation not provided to SSRN

No Address Available

Ananda Chanda

Morgan Stanley ( email )

1585 Broadway
New York, NY 10036
United States
(212) 761-4000 (Phone)

Robert F. Engle

New York University - Leonard N. Stern School of Business - Department of Economics ( email )

269 Mercer Street
New York, NY 10003
United States

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)

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Cambridge, MA 02138
United States

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