A Predictive Stock Market Technical Analysis Using Fuzzy Logic

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

doi:10.5539/cis.v7n3p1

Acheme David Ijegwa, Olusola Olasunkanmi Isaac + Show 2 more

Open Access

https://doi.org/10.5539/cis.v7n3p1

Copy DOI

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.

Highlights

1.1 Problem StatementThe stock market is one of the most attractive places for investment, especially for traders as it provides a good market place for both long term and short term investment for profit making
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 defined
The result from the fuzzy inference system implemented in the MATLAB is given in Figures 2 to 6

Summary

Introduction

The stock market is one of the most attractive places for investment, especially for traders as it provides a good market place for both long term and short term investment for profit making. It is important for companies, because this is one of their primary sources to raise money. The stock market is a popular investments destination owing to its high expected profit. The recent experienced showed that the higher the expected profit, the higher the risk implication. (Kou, Chen, & Hwang, 2001; Vincent & Bamiro, 2013) numerous investigations gave rise to different decision support systems for the sake of providing the investors with an optimal prediction. The information includes financial historical information, real time information and economical information opined that in order to successfully trade in the financial markets, it is important to develop models where one can identify different states of the market so as to modify one’s actions (Jan, Uzay, & Willien, 2004)

Methods

Results

Discussion

Conclusion