Stock Market Prediction Using Fuzzy Logic and Technical Indicators: A Case Study of Indian Banks

This study presents a decision support system for stock market investors that combines technical analysis with fuzzy logic. The system utilizes four essential technical indicators—Moving Average Convergence/Divergence (MACD), Relative Strength Index (RSI), Stochastic Oscillator (SO), and On-Balance...

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Bibliographic Details
Published in:International journal for research in applied science and engineering technology 2024-09, Vol.12 (9), p.33-37
Main Author: Yandamuri, Dr. Swathi
Format: Article
Language:English
Online Access:Get full text
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Summary:This study presents a decision support system for stock market investors that combines technical analysis with fuzzy logic. The system utilizes four essential technical indicators—Moving Average Convergence/Divergence (MACD), Relative Strength Index (RSI), Stochastic Oscillator (SO), and On-Balance Volume (OBV)—to predict future price movements. These indicators are mapped as inputs into a fuzzy inference system, where fuzzy rules and membership functions are applied to generate trading recommendations, categorized as Bullish, Neutral, or Bearish. Experiments using MATLAB with data from 10 Indian banks demonstrate that the system effectively predicts stock movements and improves investment decisions when integrated with additional market information and investor insights
ISSN:2321-9653
2321-9653
DOI:10.22214/ijraset.2024.64130