Exploration of rotation strategy for value premium of stock market

Deng Yiv Chiu; Hsiao Ching Lee; Cheng Yi Shiu

Exploration of rotation strategy for value premium of stock market

Deng Yiv Chiu, Hsiao Ching Lee, Cheng Yi Shiu

Department of Finance

Research output: Contribution to journal › Article › peer-review

Abstract

We propose a hybrid AI approach to explore rotation strategy for value premium of S&P 500 Barra value index and S&P 500 Barra growth index with GA-SVR approach. We utilize genetic algorithm to locate the approximate optimal combination of technical variables and economics variables. Then the property of nonlinearity and high dimensionality of the support vector regression is employed to decide the preference of value stocks or growth stocks. The empirical results show that the proposed approach outperforms the benchmark strategies.

Original language	English
Pages (from-to)	267-272
Number of pages	6
Journal	ICIC Express Letters
Volume	5
Issue number	1
State	Published - Jan 2011

Keywords

Genetic algorithm
Passive-value-minus-growth strategy
S&P 500 index
Support vector regression

Cite this

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title = "Exploration of rotation strategy for value premium of stock market",

abstract = "We propose a hybrid AI approach to explore rotation strategy for value premium of S&P 500 Barra value index and S&P 500 Barra growth index with GA-SVR approach. We utilize genetic algorithm to locate the approximate optimal combination of technical variables and economics variables. Then the property of nonlinearity and high dimensionality of the support vector regression is employed to decide the preference of value stocks or growth stocks. The empirical results show that the proposed approach outperforms the benchmark strategies.",

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AB - We propose a hybrid AI approach to explore rotation strategy for value premium of S&P 500 Barra value index and S&P 500 Barra growth index with GA-SVR approach. We utilize genetic algorithm to locate the approximate optimal combination of technical variables and economics variables. Then the property of nonlinearity and high dimensionality of the support vector regression is employed to decide the preference of value stocks or growth stocks. The empirical results show that the proposed approach outperforms the benchmark strategies.

KW - Genetic algorithm

KW - Passive-value-minus-growth strategy

KW - S&P 500 index

KW - Support vector regression

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Exploration of rotation strategy for value premium of stock market

Abstract

Keywords

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