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Title: A fuzzy logic model to forecast momentum in stock markets

Authors: G.P. Pandey; Sanjay Sharma

Addresses: Department of Applied Mathematics, Bhilai Institute of Technology, Durg, India ' Department of Applied Mathematics, Bhilai Institute of Technology, Durg, India

Abstract: Trend identification is a visual process where we can draw and see the trend line, then suggest the trend. But to make the system understand this trend is very tough. Using fuzzy logic first we try to make the system understand the actual trend and verify with what we can see and then we go on for forecasting the future trend. Fuzzy membership functions are the key elements while creating any fuzzy system. For generating these membership functions, usually two sources are used, i.e., expert knowledge and real time data. Expert knowledge may not be available all the time, but the probability of getting real time data is more. Here we have tried to develop a method by which fuzzification of real time data can be done and then identification of the trend can be done using those fuzzy values after which forecasting of the short term trend can be done. The type of real time data used here is the daily values of NIFTY 50 index used in National Stock Exchange of India for stock futures trading.

Keywords: forecasting; fuzzy logic; NIFTY 50; stock markets; stock market momentum; short term trends; futures trading; India.

DOI: 10.1504/IJFCM.2016.077881

International Journal of Fuzzy Computation and Modelling, 2016 Vol.2 No.1, pp.61 - 75

Accepted: 14 Feb 2016
Published online: 20 Jul 2016 *

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