RNNs and LSTMs Based Synchronization Analysis of Indian Stock Market

By use of recurrence plots (RP) and cross recurrence quantification analysis (CRQA) model nonlinear correlation in stocks used Cross Recurrence Plot (CRP) data converted into a time-series data because RNN and LSTM can be used in this research which can be used for both regression and classification in stock market price prediction. RNN and LSTM model used as compare to other models because it is better for sequential data and non-linear dynamics, and it predicts stock prices with high accuracy. Using given dataset which contain 20 highly capitalized Indian market stocks spanning 21 years this model got highest accuracy of 0.98 and F1 score of 0.83 as compare to existing model used till now in this work, results method can accurately forecast stock price synchronization, providing useful information for creating trading plans and risk management instruments.