Stock Market Price Prediction using Neural Prophet with Deep Neural Network

This paper proposes a novel approach for stock market price prediction leveraging a hybrid model that combines Neural Prophet with a Deep Neural Network (DNN). The integration aims to capture both time-series dependencies and complex non-linear patterns inherent in stock market data, which are crucial for accurate forecasting. Experimental results demonstrate improved predictive accuracy compared to traditional methods, offering a valuable tool for financial analysis and investment strategies in real-world scenarios.