Equity style timing using support vector regressions
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.
Volume (Year): 16 (2006)
Issue (Month): 15 ()
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- André Lucas & Ronald van Dijk & Teun Kloek, 2001.
"Stock Selection, Style Rotation, and Risk,"
Tinbergen Institute Discussion Papers
01-021/2, Tinbergen Institute.
- Lo, Andrew W. (Andrew Wen-Chuan) & MacKinlay, Archie Craig, 1955-, 1989.
"Data-snooping biases in tests of financial asset pricing models,"
3020-89., Massachusetts Institute of Technology (MIT), Sloan School of Management.
- Lo, Andrew W & MacKinlay, A Craig, 1990. "Data-Snooping Biases in Tests of Financial Asset Pricing Models," Review of Financial Studies, Society for Financial Studies, vol. 3(3), pages 431-67.
- Andrew W. Lo & A. Craig MacKinlay, 1989. "Data-Snooping Biases in Tests of Financial Asset Pricing Models," NBER Working Papers 3001, National Bureau of Economic Research, Inc.
- T. C. Mills & J. V. Jordanov, 2003. "The size effect and the random walk hypothesis: evidence from the London Stock Exchange using Markov Chains," Applied Financial Economics, Taylor & Francis Journals, vol. 13(11), pages 807-815.
- Bossaerts, Peter & Hillion, Pierre, 1999. "Implementing Statistical Criteria to Select Return Forecasting Models: What Do We Learn?," Review of Financial Studies, Society for Financial Studies, vol. 12(2), pages 405-28.
- Said Elfakhani, 2000. "Short positions, size effect, and the liquidity hypothesis: implications for stock performance," Applied Financial Economics, Taylor & Francis Journals, vol. 10(1), pages 105-116.
- Johnathan Mun & Richard Kish & Geraldo Vasconcellos, 2001. "The contrarian investment strategy: additional evidence," Applied Financial Economics, Taylor & Francis Journals, vol. 11(6), pages 619-640.
- Ki-Yeol Kwon & Richard Kish, 2002. "Technical trading strategies and return predictability: NYSE," Applied Financial Economics, Taylor & Francis Journals, vol. 12(9), pages 639-653.
- Bauer, Rob & Derwall, Jeroen & Molenaar, Roderick, 2004. "The real-time predictability of the size and value premium in Japan," Pacific-Basin Finance Journal, Elsevier, vol. 12(5), pages 503-523, November.
- Pesaran, M Hashem & Timmermann, Allan, 1995. " Predictability of Stock Returns: Robustness and Economic Significance," Journal of Finance, American Finance Association, vol. 50(4), pages 1201-28, September.
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