Forecasting Stock Price Synchronization in the Indian Market using Recurrent Neural Networks and Long Short-Term Memory
Our research presents a new approach for forecasting the synchronization of stock prices using machine learning and non-linear time-series analysis. By transforming Cross Recurrence Plot (CRP) data into a time-series format, we enable the use of Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) networks for predicting stock price synchronization through both regression and classification.