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Equity style timing using support vector regressions

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  • Georgi Nalbantov
  • Rob Bauer
  • Ida Sprinkhuizen-Kuyper

Abstract

The disappointing performance of value and small cap strategies shows that style consistency may not provide the long-term benefits often assumed in the literature. In this study it is examined whether the short-term variation in the US size and value premium is predictable. Style-timing strategies are documented based on technical and (macro-) economic predictors using a recently developed artificial intelligence tool called Support Vector Regressions (SVR). SVR are known for their ability to tackle the standard problem of overfitting, especially in multivariate settings. The findings indicate that both premiums are predictable under fair levels of transaction costs and various forecasting horizons.

Suggested Citation

  • Georgi Nalbantov & Rob Bauer & Ida Sprinkhuizen-Kuyper, 2006. "Equity style timing using support vector regressions," Applied Financial Economics, Taylor & Francis Journals, vol. 16(15), pages 1095-1111.
    • Handle: RePEc:taf:apfiec:v:16:y:2006:i:15:p:1095-1111
    DOI: 10.1080/09603100500426556
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    4. I-Cheng Yeh & Tzu-Kuang Hsu, 2011. "Growth Value Two-Factor Model," Journal of Asset Management, Palgrave Macmillan, vol. 11(6), pages 435-451, February.
    5. Kathryn Holmes & Robert Faff & Iain Clacher, 2010. "Style analysis and dominant index timing: an application to Australian multi-sector managed funds," Applied Financial Economics, Taylor & Francis Journals, vol. 20(4), pages 293-301.

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