Estimating, Filtering and Forecasting Realized Betas

Claudio Morana

ICER Working Papers - Applied Mathematics Series from ICER - International Centre for Economic Research

Abstract: A strategy for estimating, ?filtering and forecasting time-varying factor betas is proposed. The approach is based on the multivariate realized regression principle, an omnibus noise ?filter and an adaptive long memory forecasting model. While the multivariate realized regression approach allows for an accurate estimation of the betas also when more than a (non-orthogonal) risk factor affects stock returns, the omnibus noise ?filter and adaptive long memory forecasting model, by accounting for the time series properties of factor betas, allow for accurate estimation and forecasting.

Keywords: realized regression; factor betas; long memory; structural change; forecasting; noise ?ltering. (search for similar items in EconPapers)
JEL-codes: C22 C53 G12 (search for similar items in EconPapers)
Pages: 37 pages
Date: 2007-03
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Citations: View citations in EconPapers (1)

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