Enhanced Accuracy of Stock Market Prediction with ANN Algorithm

This study investigates how well Artificial Neural Network (ANN) algorithms can forecast stock market results in the face of volatile and dynamic financial markets.ANN models are taught to predict future stock values by combining historical data with factors including news, market fluctuations, company financials, and sentiment on social media.The analytical comparison shows that ANN-based techniques perform better in terms of resilience and prediction accuracy than traditional models.Sensitivity analysis delves deeper into the ways that hidden layers, neurons, and input features affect prediction accuracy.The findings highlight how ANN algorithms may improve stock market projections, enabling wise financial choices and possibly increasing returns.To fully utilize the potential of ANN algorithms in this field, more research is advised.