A Predictive Stock Market Technical Analysis Using Fuzzy Logic

Acheme David Ijegwa, Vincent Olufunke Rebecca, Folorunso Olusegun, Olusola Olasunkanmi Isaac

Abstract


Decision making process in stock trading is a complex one. There are numbers of technical indicators that are used by traders to study trends of the market and make buying and selling decisions based on their observations. This research seeks to deploy fuzzy inference to stock market, with four indicators used in technical analysis to aid in the decision making process in order to deal with probability. The four technical indicators are the Moving Average Convergence/Divergence (MACD), Relative Strength Index (RSI), Stochastic Oscillator (SO) and On-Balance Volume (OBV). The fuzzy rules are a combination of the trading rules for each of the indicators used as the input variables of the fuzzy system and for all the four technical indicators used, the membership functions were also defined. The result is a recommendation to buy, sell or hold. Data were collected for two Nigerian banks for testing and evaluation of the system. The technical indicators were then computed for each data and from the computed technical indicators; experiment was carried out for two months. The system generated satisfactory recommendation as when to buy, sell or hold, when the output is compared with actual data collected from the Nigerian Stock Exchange. The system can therefore act as an effective model for traders in the stock market when there is a combination of the recommendation with the individual’s trading skills.


Full Text: PDF DOI: 10.5539/cis.v7n3p1

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This work is licensed under a Creative Commons Attribution 3.0 License.

Computer and Information Science   ISSN 1913-8989 (Print)   ISSN 1913-8997 (Online)
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