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Forecasting Equicorrelation

Adam Clements, Christopher Coleman-Fenn and Daniel Smith ()

No 72, NCER Working Paper Series from National Centre for Econometric Research

Abstract: We study the out-of-sample forecasting performance of several time-series models of equicorrelation, which is the average pairwise correlation between a number of assets. Building on the existing Dynamic Conditional Correlation and Linear Dynamic Equicorrelation models, we propose a model that uses proxies for equicorrelation based on high-frequency intraday data, and the level of equicorrelation implied by options prices. Using state-of-the-art statistical evaluation technology, we find that the use of both realized and implied equicorrelations outperform models that use daily data alone. However, the out-of-sample forecasting benefits of implied equicorrelation disappear when used in conjunction with the realized measures.

Keywords: Equicorrelation; Implied Correlation; Multivariate GARCH; DCC (search for similar items in EconPapers)
JEL-codes: C32 C53 G17 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ets and nep-for
Date: 2011-04-01, Revised 2011-08-29
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