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Identification of Factor Models for Forecasting Returns

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  • Manfred Deistler

Abstract

A data-driven approach for forecasting returns of asset prices is introduced. Special emphasis is given to data-driven specification and to dimension reduction. Specification is performed by a modified AIC, BIC-based An-algorithm. Quasi-static principal component analysis, quasi-static factor models with idiosyncratic errors and reduced rank regression are considered. The forecasting results obtained are compared. Copyright 2005, Oxford University Press.

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  • Manfred Deistler, 2005. "Identification of Factor Models for Forecasting Returns," Journal of Financial Econometrics, Oxford University Press, vol. 3(2), pages 256-281.
    • Handle: RePEc:oup:jfinec:v:3:y:2005:i:2:p:256-281
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbi011
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    Cited by:

    1. Buncic, Daniel & Stern, Cord, 2019. "Forecast ranked tailored equity portfolios," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    2. Focardi, Sergio M. & Fabozzi, Frank J. & Mitov, Ivan K., 2016. "A new approach to statistical arbitrage: Strategies based on dynamic factor models of prices and their performance," Journal of Banking & Finance, Elsevier, vol. 65(C), pages 134-155.

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