Investigating the Crisis Forecasting Ability of the Cumulative Residual Entropy Measure by using Logistic Map Simulation Data and Tehran Stock Exchange Overall Index

The importance of forecasting in investment discussions has led to the use of a wide range of methods in various sciences to predict future trends and prices. Crisis forecasting has also become more prominent in recent years. Further investigation of the dynamics of complex systems is required to determine what changes in system dynamics occur during a crisis. This research has investigated the crisis forecasting ability of cumulative residual entropy measure in Tehran Stock Exchange (as a complex system). In this study, crisis simulation data generated by logistic map have been used to examine the ability of the proposed measure theoretically. In the practical case, the data of the overall index of Tehran Stock Exchange from October 2010 to September 2019 has been used. The results showed that the proposed measure can forecast the crisis