Machine Learning Strategies for Nifty50 Index Trading Optimization

The dynamic nature of financial markets, especially Nifty50 trading, requires advanced predictive models for effective decision-making and risk management. Recent advancements in machine learning have led to robust models for handling financial data complexities and market volatility. This review explores a number of machine learning algorithms ensemble methods, and deep learning models. Key stages such as data pre-processing, feature selection, and model training are analyzed, with a focus on integrating the India VIX index and financial indicators to improve accuracy. Comparative performance analysis using metrics like accuracy, sensitivity, MAPE, RMSE, and F1-Score is presented. The paper concludes with insights on how these advancements can enhance prediction precision, risk management, and trading outcomes.