Equity Style Timing Using Support Vector Regressions

22 Pages Posted: 13 Jan 2005

See all articles by Georgi Nalbantov

Georgi Nalbantov

ERIM, Erasmus University Rotterdam

Rob Bauer

Maastricht University

Ida Sprinkhuizen-Kuyper

IKAT, Universiteit Maastricht

Date Written: September 2004


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 we examine whether the short-term variation in the U.S. size and value premium is predictable. We document style-timing strategies 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. Our findings indicate that both premiums are predictable under fair levels of transaction costs and various forecasting horizons.

Keywords: Stock returns, style timing, Support Vector Regression

JEL Classification: C51, C52, C53, G11, G12, G15, G19

Suggested Citation

Nalbantov, Georgi and Bauer, Rob and Sprinkhuizen-Kuyper, Ida, Equity Style Timing Using Support Vector Regressions (September 2004). Available at SSRN: https://ssrn.com/abstract=564502 or http://dx.doi.org/10.2139/ssrn.564502

Georgi Nalbantov (Contact Author)

ERIM, Erasmus University Rotterdam ( email )

p.a. Tinbergen Institute, H16-06
P.O. Box 1738
3000 DR Rotterdam

HOME PAGE: http://www.few.eur.nl/few/people/nalbantov/

Rob Bauer

Maastricht University ( email )

P.O. Box 616
Maastricht, 6200 MD
+31 43 3883871 (Phone)

Ida Sprinkhuizen-Kuyper

IKAT, Universiteit Maastricht ( email )

P.O. Box 616
Maastricht, 6200MD

HOME PAGE: http://www.cs.unimaas.nl/~kuyper/

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