Mr. Rashid Hafeez Khokhar Profile

Rashid Hafeez Khokhar

at Univ Technology Malaysia

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Proceedings Article | 28 March 2005 Paper

Predictive fuzzy reasoning method for time series stock market data mining

Rashid Khokhar, Mohd Noor Md Sap

Proceedings Volume 5812, (2005) https://doi.org/10.1117/12.603089

KEYWORDS: Fuzzy logic, Silver, Data mining, Mining, Data modeling, Composites, Distance measurement, Evolutionary algorithms, Performance modeling, Analytical research

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Data mining is able to uncover hidden patterns and predict future trends and behaviors in financial markets. In this research we approach quantitative time series stock selection as a data mining problem. We present another modification of extraction of weighted fuzzy production rules (WFPRs) from fuzzy decision tree by using proposed similarity-based fuzzy reasoning method called predictive reasoning (PR) method. In proposed predictive reasoning method weight parameter can be assigned to each proposition in the antecedent of a fuzzy production rule (FPR) and certainty factor (CF) to each rule. Certainty factors are calculated by using some important variables like effect of other companies, effect of other local stock market, effect of overall world situation, and effect of political situation from stock market. The predictive FDT has been tested using three data sets including KLSE, NYSE and LSE. The experimental results show that WFPRs rules have high learning accuracy and also better predictive accuracy of stock market time series data.

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