S. Mundia

PREDICTING CLOSING STOCK RETURNS USING SEQUENTIAL ARTIFICIAL NEURAL NETWORK

Financial time series exhibit complex characteristics, including volatility, nonlinearity, and temporal dependencies, which make accurate forecasting challenging. This study investigated the use of a dynamic Long Short-Term Memory (LSTM) neural network to forecast stock prices and market direction. Augmented Dickey-Ful...