wavelet analysis of stock returns and total index with moving average of stock returns and total index

This research aims to investigate and analyze the behavior patterns of stock market fluctuations so that appropriate strategies with varying time horizons can be determined based on the characteristics extracted from different time layers and the level of economic activity measured by the investors. this research investigates and analyses stock market fluctuations in different periods by applying discrete wavelet transformation with maximum overlap in matlab software. for this purpose, the variances of effective indicators are compared and analyzed during 2011-2023. this research shows that the wavelet variance of the stock return is more than the moving average of the stock return. according to the movement scales of each stock return and the moving average of the stock returns during the long-term scales, the wavelet variance is less and the comovement is less. still, during the short-term time scales, the comovement is greater, and the variance of the wavelet return is greater among them. the variance of the moving average of the total index is greater than that of the total index. according to the movement scales, each of the total index and the moving average of the total index has less wavelet variance and less comovement during the long-term scales. still, the commitment has increased during the short-term time scales, and the wavelet return variance is higher.