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State Space Models for Dynamic Style Analysis of Portfolios

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  • Pizzinga, Adrian
  • Fernandes, Cristiano

Abstract

This paper presents a framework and methods for the estimation of linear and non-linear state space (SS) models, occasionally subject to restrictions, to construct and estimate several models for style analysis with time varying exposures. The study is conducted by applying these models to an artificial portfolio and to return series of Brazilian investment funds. The results confirm the belief that dynamic allocations in a portfolio are a more realistic assumption for investment funds management.

Suggested Citation

  • Pizzinga, Adrian & Fernandes, Cristiano, 2006. "State Space Models for Dynamic Style Analysis of Portfolios," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 26(1), May.
    • Handle: RePEc:sbe:breart:v:26:y:2006:i:1:a:2497
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    1. Laurens Swinkels & Pieter Van Der Sluis, 2006. "Return-based style analysis with time-varying exposures," The European Journal of Finance, Taylor & Francis Journals, vol. 12(6-7), pages 529-552.
    2. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    3. ter Horst, Jenke R. & Nijman, Theo E. & de Roon, Frans A., 2004. "Evaluating style analysis," Journal of Empirical Finance, Elsevier, vol. 11(1), pages 29-53, January.
    4. Doran, Howard E, 1992. "Constraining Kalman Filter and Smoothing Estimates to Satisfy Time-Varying Restrictions," The Review of Economics and Statistics, MIT Press, vol. 74(3), pages 568-572, August.
    5. Fuhrer, Jeffrey C, 1992. "Inferring Changes in Expectation Behavior over Time: An Application of Nonlinear Time-Varying-Parameters Estimation," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 169-177, April.
    6. Ter Horst, J.R. & Nijman, T.E. & de Roon, F.A., 2004. "Evaluating style analysis," Other publications TiSEM 8a501733-7a06-4399-8a43-0, Tilburg University, School of Economics and Management.
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    1. Adrian Pizzinga, 2010. "Constrained Kalman Filtering: Additional Results," International Statistical Review, International Statistical Institute, vol. 78(2), pages 189-208, August.
    2. Pizzinga, Adrian, 2009. "Further investigation into restricted Kalman filtering," Statistics & Probability Letters, Elsevier, vol. 79(2), pages 264-269, January.

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