approach of maximal overlap discrete wavelet transforms to stock return inthe iran capital market

The primary objective of this study is to determine the genuine and dynamic relationship between returns and stock market fluctuations across various time horizons. the key outcomes of this study aim to assess the predictive power of re turns and stock market fluctuations in determining investors' level of economic activity. accurately measuring these relationships assists investors in predicting future stock market movements and developing, planning, and implementing their investment strategies within each time horizon. in this research, the maximal overlap discrete wavelet transform has been employed to examine the relationships between industry-specific return fluctuations and the main stock indices within different time horizons from 2011 to 2020. the results indicate that the wavelet variance of return varies among different industries. the return of investment companies exhibits similarity to the banking industry's investment return across various time scales. furthermore, the variance of the total index is lower across different time scales compared to the value of the cash index.