A Combination of Hidden Markov Model and Association Analysis for Stock Market Sector Rotation

• Autores: Jiao Chen, Chi Xie, Zhijian Zeng
• Localización: Revista de Cercetare si Interventie Sociala, ISSN-e 1584-5397, Vol. 63, 2018, págs. 149-165
• Idioma: inglés
• Enlaces
  • Texto completo (pdf)
• Resumen

  • The use of Hidden Markov Model in stock market sector rotation is not investigated in the past. In this research, we consider an industry sector index portfolio based on the Shenwan fi rst-class classifi cation and propose state transition matrix for investment. In particular, we design an correlation analysis strategy that initialized state probability transition matrix Additionally, we design the observation state sequence which consisting of a series of stocks. Using Pearson’s Correlation Coeffi cient to screen out the 10 stocks with the highest correlation in each industry sector. We put these parameters into the HMM and use the Baum- Welch algorithm to obtain the iterative solution results. Using the solved matrix into the back test program, the results show that the strategy returns well.