Abstract
AbstractStock forecasting is a non-linear financial time series forecasting problem. Stock index contains tremendous noise and is affected by numerous factors. Fuzzy time series takes advantage of such problems. In this paper, a novel model based on the fuzzy frequent pattern tree (FFPT) is proposed to forecast short-term trends of stock markets. Fuzzy frequent pattern tree is a combination of fuzzy set theory and frequent pattern tree. Frequent pattern tree is a highly compressed data structure store the information of association rules to be mined. In this paper, an FFPT is built using fuzzy stock time series. Then we forecast short-term trends by a new method called FFPT-Search. And stock data from several famous stock markets is picked up to evaluate the effectiveness of our model. Computational results indicate it works well.Keywordsstock forecastingfuzzy frequent pattern treefuzzy time seriesassociation rulesdata mining
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