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- W4200578081 abstract "AbstractAlgorithmic Trading is becoming ever increasing field. We implemented various machine learning methods to predict stock price direction in the following paper. Technical Indicators are taken as features and models are trained upon them. Stock price direction forecasting helps us to choose from daily trading techniques and increases the probability of having massive profits while maintaining low-risk profile. In our research extreme gradient boosting (XGBoost) technique has given the highest accuracy, i.e. 73.1% and have outperformed other machine learning techniques used. Our Proposed model outperforms existing models in literature and adds forecasting on day-by-day basis.KeywordsTradingXGBoostEquity marketsAlgorithmic modelMachine learning for financeNSENIFTY50" @default.
- W4200578081 created "2021-12-31" @default.
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- W4200578081 date "2021-12-17" @default.
- W4200578081 modified "2023-09-25" @default.
- W4200578081 title "Extreme Gradient Boosting for Predicting Stock Price Direction in Context of Indian Equity Markets" @default.
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- W4200578081 doi "https://doi.org/10.1007/978-981-16-6369-7_28" @default.
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