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A multivariate dichotomic approach for tactical asset allocation

Author

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  • Mathieu Roberge

    (Caisse de dépôt et palcement du Québec, Investment Policy Research)

  • Cécile Le Moigne

Abstract

This paper revisits the problem of tactical asset allocation which consists in predicting which of bonds or stocks will perform better over the next period. A multivariate dichotomic framework is presented to address this problem. The model correctly predicts 62.5 per cent of the out-of-sample months and leads to a better economic performance than the results obtained by more classical methods such as linear and logistic regression or discriminant analysis. Moreover, an investment strategy based on the prediction from the model dominates more naive strategies that every month invest 60 per cent in stocks and 40 per cent bonds or 100 per cent in stocks.

Suggested Citation

  • Mathieu Roberge & Cécile Le Moigne, 2005. "A multivariate dichotomic approach for tactical asset allocation," Journal of Asset Management, Palgrave Macmillan, vol. 6(3), pages 206-218, October.
    • Handle: RePEc:pal:assmgt:v:6:y:2005:i:3:d:10.1057_palgrave.jam.2240176
    DOI: 10.1057/palgrave.jam.2240176
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