Abstract: Symbolic time series analysis method is introduced into the analysis of the characteristics of return change from the angle of large scale.The method of determining the principal return change patterns and forecasting return levels is proposed.Firstly,the return series is transformed into symbolic series.Different words in symbolic series represent different return change pattern.The principal return change patterns can be determined according to symbolic series histogram.Then,on condition that the return levels of the former several time points are determined,according to the probability distribution of various return change patterns,the probability of different return levels of the next one or several time points can be deduced to realize the forecasting of return levels.The return series of six indexes which are Shanghai composite stock,Shenzhen component stock,Shanghai industrial stock,Shanghai commercial stock,Shanghai property stock and Shanghai utility stock are analyzed.The principal return change patterns of each index are determined and the return levels based on the principal return change patterns are forecasted to prove the effectiveness and feasibility of the method.

Key words: symbolic time series analysis, histogram, return, principal pattern, forecasting