High Frequency Multiplicative Component GARCH

30 Pages Posted: 7 Nov 2008

See all articles by Robert F. Engle

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)

Magdalena Sokalska

City University of New York

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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 stochastic 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 different specifications. Apart from building a new model, we obtain several interesting forecasting 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.

Keywords: Volatility, ARCH, Intra-day Returns

Suggested Citation

Engle, Robert F. and Sokalska, Magdalena, High Frequency Multiplicative Component GARCH (August 2005). NYU Working Paper No. SC-CFE-05-05. Available at SSRN: https://ssrn.com/abstract=1297097

Robert F. Engle (Contact Author)

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

269 Mercer Street
New York, NY 10003
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New York University (NYU) - Department of Finance

Stern School of Business
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New York, NY 10012-1126
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National Bureau of Economic Research (NBER)

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Cambridge, MA 02138
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Magdalena Sokalska

City University of New York ( email )

Flushing, NY 11367
United States
718 997 5450 (Phone)

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