Title :
Financial Asset Price Forecasting Based on Intertransaction Association Rules Mining
Author :
Li Ping ; Xing Wenjing ; Guangdong, Huang
Author_Institution :
Sch. of Econ. & Manage., Beihang Univ., Beijing, China
Abstract :
It has been widely accepted that association rules mining, the task of searching for correlations between items in a database, can discover useful rules in stock analysis. Previous studies mainly emphasize on mining intratransaction associations. In this paper, we introduce the concept of intertransaction and the FITI algorithm so that we can effectively forecast the price changes in Chinese capital markets, then we compare FITI with EH-Apriori, and demonstrate the advantages of FITI over EH-Apriori. At the end of this paper, we apply the algorithm to a dataset of Chinese asset indices and the results indicate the usefulness of intertransaction association rules in price prediction.
Keywords :
data mining; financial data processing; pricing; share prices; stock markets; Chinese asset index; Chinese capital market; EH-Apriori; financial asset price forecasting; intertransaction association rule mining; price change forecasting; price prediction; rule discovery; stock analysis; Association rules; Copper; Exchange rates; Indexes; Itemsets; Data mining; EH-Apriori algorithm; FITI algorithm; Intertransaction association rules; Price forcasting;
Conference_Titel :
E-Business and E-Government (ICEE), 2010 International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-0-7695-3997-3
DOI :
10.1109/ICEE.2010.361
