In this report, we investigate a two-sample procedure for detecting distributional changes in stock returns using a modified energy statistic (EMIC) proposed by Njuki and Ning [2025]. The method compares two adjacent segments of a time series to assess whether they originate from the same underlying distribution. The finite sample properties of the proposed method are conducted to compare its powers and applications. Since the energy-based tests are sensitive to differences in location, scale, skewness, and tail behavior, the proposed approach on modified energy statistics provides a flexible nonparametric framework for identifying potential change-points in financial return data