摘要：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 BaumWelch
algorithm to obtain the iterative solution results. Using the solved matrix
into the back test program, the results show that the strategy returns well.
关键词：HMM; association analysis; Pearson correlation coeffi cient; BaumWelch
algorithm; apriori
