Exploration of rotation strategy for value premium of stock market

Deng Yiv Chiu, Hsiao Ching Lee, Cheng Yi Shiu

Research output: Contribution to journalArticlepeer-review


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 languageEnglish
Pages (from-to)267-272
Number of pages6
JournalICIC Express Letters
Issue number1
StatePublished - Jan 2011


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


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