Title :
An Association Rule Mining Based Stock Market Recommender System
Author :
Paranjape-Voditel, Preeti ; Deshpande, Umesh
Author_Institution :
Dept. of Comput. Applic., Shri Ramdeobaba Kamla Nehru Eng. Coll., Nagpur, India
Abstract :
We propose an Association Rule Mining (ARM) based Recommender system for the stock markets. Normally technical and fundamental analyses are a basis of prediction of stock price. Several systems exist for monitoring and prediction of stock prices. But these deal with individual stocks. They do not give the inter-relationship between stocks or their relationship with the stock market INDEX. Our method uses ARM, fuzzy ARM, weighted fuzzy ARM, ARM with time lags, fuzzy ARM with time lags and weighted fuzzy ARM with time lags to predict relationships between stocks, which is used as the basis for portfolio management and in recommendations for mutual funds.
Keywords :
data mining; fuzzy set theory; pricing; recommender systems; stock markets; association rule mining; mutual funds; portfolio management; stock market INDEX; stock market recommender system; stock price prediction; time lags; weighted fuzzy ARM; Association rules; Itemsets; Portfolios; Recommender systems; Steel; Stock markets; fuzzy ARM; fuzzy time lagged ARM; recommender system; time lags; weighted fuzzy ARM; weighted fuzzy time-lagged ARM;
Conference_Titel :
Emerging Applications of Information Technology (EAIT), 2011 Second International Conference on
Conference_Location :
Kolkata
Print_ISBN :
978-1-4244-9683-9
DOI :
10.1109/EAIT.2011.90