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- W4383756060 abstract "Use of machine learning for equity price prediction is a novel and famous research area. Equity returns can beat the inflation and tax rate which leads to the best choice of investment, but the equity market is highly volatile and risky. Algo-trading strategies using machine learning algorithms are being widely implemented for prediction and pattern identifications. Different strategies and different algorithms are still in its infancy for algo-trading due to market volatility. We have proposed a novel fuzzy-genetic machine learning algorithm with a blend of machine learning algorithm for predictions, fuzzy for classification and genetic algorithm for optimization for equity market prediction. So, we have initiated an experimental plan to implement fuzzy-genetic machine learning for few stocks average price addressing limitations of existing strategies. For the predictions and pattern identifications, we are going to apply fuzzy-genetic machine learning algorithms. In future work, we have planned to use moving average convergence/divergence method and relative strength index strategy results to train the proposed evolutionary model." @default.
- W4383756060 created "2023-07-11" @default.
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- W4383756060 date "2023-01-01" @default.
- W4383756060 modified "2023-09-27" @default.
- W4383756060 title "Equity Market Price Prediction Using Fuzzy-Genetic Machine Learning Algorithms" @default.
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- W4383756060 doi "https://doi.org/10.1007/978-981-99-2468-4_1" @default.
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