Objective and Dynamic Entropy Method for Benchmark Regression

In the context of benchmark regression, we propose an objective and dynamic extension of the conventional entropy method. To ensure the robustness of the regression outcomes, we employ a vertical and horizontal weighting approach to recalibrate the weight of each fundamental index. This method considers the magnitude of the original data information of the evaluated object, captures the nuances of the evaluated object based on the original time series three-dimensional data, and enables objective evaluation across different objects and time periods, thereby eliminating subjective biases.