Frequency analysis of stock return rates in the Iranian capital market Based on the wavelet approach

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Article Type:
Research/Original Article (دارای رتبه معتبر)
Abstract:

Studying and analyzing the behavior of fluctuations in the return of securities requires the discovery of a behavioral pattern of stock returns that Based on this model, shareholders are able to choose the best stocks by evaluating their stocks and other stocks in the market, and as a result, they can decide to keep, sell or replace the stocks. The main purpose of this study is to study and analyze the behavioral patterns of stock market fluctuations to show different characteristics of different layers, appropriate strategies with different horizons and evaluate the level of economic activity of investors. In this research, using discrete wavelet transform with maximum overlap in MATLAB software, stock market fluctuations in different time periods are examined and analyzed; For this purpose, Return variances of effective stock market indices during the years 2011-2020 are compared and analyzed.The results of the research showed that the wavelet variance of the total index is lower in different scales compared to the wavelet variance of the cash return index,also the wavelet variance of the stock return is more than the moving average of the stock return. According to the movement scales of each of the stock returns and the moving average of the stock returns during the long-term scales,the wavelet variance was less and the co-movement was less, but during the short-term time scales, the co-movement increased and the variance of the wavelet return was higher among them. In the end, it was suggested that investors formulate their investment strategies in a dynamic and intelligent manner according to the analysis of the behavior of the fluctuations of total indices, price and cash yield and their moving average in different time layers.

Language:
Persian
Published:
Financial Knowledge of Securities Analysis, Volume:16 Issue: 58, 2023
Pages:
106 to 123
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