Hamideh Nasabzadeh; Mona Hesari
Abstract
This study introduces a hybrid trading strategy combining fuzzified Moving Average (Fuzzy MA) and Relative Strength Index (Fuzzy RSI) indicators for binary options in the Japanese financial market, demonstrating enhanced adaptability and profitability. Using fuzzy logic and Genetic Algorithms for parameter ...
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This study introduces a hybrid trading strategy combining fuzzified Moving Average (Fuzzy MA) and Relative Strength Index (Fuzzy RSI) indicators for binary options in the Japanese financial market, demonstrating enhanced adaptability and profitability. Using fuzzy logic and Genetic Algorithms for parameter optimization, the strategy aims to maximize profit while fairly evaluating different methods through multiple performance metrics, including the Sharpe ratio and drawdown. By adapting traditional indicators to capture the inherent uncertainty and volatility of the market, the research focuses on the EUR/USD currency pair. Three approaches are investigated: Fuzzy MA, Fuzzy RSI, and the combined Fuzzy MA+RSI strategy. Results show that the combined strategy significantly outperforms individual fuzzy indicators, offering superior adaptability and profitability across volatile market conditions. This study contributes to the field of binary options trading by showcasing the potential of fuzzy logic and optimization techniques, highlighting the importance of considering a range of performance metrics for a comprehensive evaluation of trading strategies.