HIGH FREQUENCY MULTIPLICATIVE COMPONENT GARCH
Magdalena E. Sokalska,
Ananda Chanda () and
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Ananda Chanda: Finance New York University
No 409, Computing in Economics and Finance 2005 from Society for Computational Economics
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 groups of companies seem to outperform the corresponding forecasts from company-by-company estimation.
Keywords: ARCH; Intra-day Returns; Volatility (search for similar items in EconPapers)
JEL-codes: C22 C53 G15 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ets, nep-fin and nep-for
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Persistent link: https://EconPapers.repec.org/RePEc:sce:scecf5:409
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