Discovering Pattern Associations in Hang Seng Index Constituent Stocks


  •  Kim Man Lui    
  •  Lun Hu    
  •  Keith C.C. Chan    

Abstract

The problem of finding patterns in financial time series has been tackled by systematic observations, statistical analysis or the use of artificial intelligence techniques. However, the techniques are more on the discovering of patterns in data rather than understanding association relationships between the discovered patterns. As time series patterns often overlap with each other, discovering pattern associations is a challenging problem. To tackle this problem, we propose a method to determine whether or not association relationship exist between price patterns in financial time series. We tested the technique on stock data collected from the Hong Kong stock market in 2008. The results reveal that there is statistical evidence of association relationships between patterns on some of the Hang Seng composite stocks while there is no evidence of such relationship with the Hang Seng Index (HSI). We conclude that the price behavior of the stocks that comprises the HSI is much easier to be understood than of their index.

 



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