Prediction of Stock and Stock Price Index Movement using Protractible Fuzzy Particle Swarm Optimization
B. Sharmila1, R. Khanchana2
1B Sharmila M.Sc., M. Phil, (Phd) Scholar, has Good Interest in Share Market / Mutual Funds and Investments.
2R. Khanchana, Asst. Professor, Sri Ramakrishna College of Arts & Science for Women, Coimbatore.

Manuscript received on 01 April 2019 | Revised Manuscript received on 06 May 2019 | Manuscript published on 30 May 2019 | PP: 1005-1009 | Volume-8 Issue-1, May 2019 | Retrieval Number: A1110058119/19©BEIESP
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Abstract: Prediction in stock marketing is very important for analyzing the economic growth. Huge investors success is depending on the prediction of future market, where the forecasting is based on economic factors, technical factors and fundamental factors. Different countries depend on different factors, but India depends on all the three factors. Predicting the problem will give the major solution to the success. This paper focus to provide a solution by proposing a fuzzy logic based particle swarm optimization algorithm for predicting the movement of stock and price index of stock for the selected Indian based stock market companies, namely CNX Nifty, S&P BSE Sensex, Infosys, and Reliance. Performance metrics considered are sensitivity, specificity, precision, recall, accuracy and f-measure. The results show that the proposed algorithm outperforms the existing algorithms in all the terms.
Keywords: Prediction, Stock, Price, Index, Fuzzy

Scope of the Article:
Discrete Optimization