University of Isfahan Journal of Asset Management and Financing 2383-1189 4 4 2016 12 21 Surveying the Relation among Volume, Stock Return and Return Volatility in the Tehran Stock Exchange: A Wavelet Analysis Surveying the Relation among Volume, Stock Return and Return Volatility in the Tehran Stock Exchange: A Wavelet Analysis 99 114 21115 10.22108/amf.2016.21115 FA Ebrahim Abbasi Management Dept., Faculty of Social Sciences and Economics, University of Al-Zahra, Tehran, Iran. Leyla Dehghan Nayeri Management Dept., Faculty of Social Sciences and Economics, University of Al-Zahra, Tehran, Iran. Nazila Poordadash Mehrabani Faculty of Social Sciences and Economics, University of Al-Zahra, Tehran, Iran. Journal Article 2015 02 15 Although many studies have tried to construct a theoretical or empirical structure of relation among trading volume, stock return and return volatility in financial markets, there still is not a general consensus about it. This study discovers latent information in variables time series for 96 months (April 2007- March 2015). To do so, related time series decomposed by using the maximum overlap discrete wavelet transform and wavelet coefficients has calculated. Then the relation between the series is examined by Granger causality test. The main feature of this research is to investigate the relation between variables at different time intervals. The results show that during the 2007 to 2015, the relation between variables in different time intervals varies. As in some periods, the Granger causality test confirms the causal relation between time series, while in some other time periods it does not support the existence of such relation.  Although many studies have tried to construct a theoretical or empirical structure of relation among trading volume, stock return and return volatility in financial markets, there still is not a general consensus about it. This study discovers latent information in variables time series for 96 months (April 2007- March 2015). To do so, related time series decomposed by using the maximum overlap discrete wavelet transform and wavelet coefficients has calculated. Then the relation between the series is examined by Granger causality test. The main feature of this research is to investigate the relation between variables at different time intervals. The results show that during the 2007 to 2015, the relation between variables in different time intervals varies. As in some periods, the Granger causality test confirms the causal relation between time series, while in some other time periods it does not support the existence of such relation.  https://amf.ui.ac.ir/article_21115_75f6a78d68c5a899c88b4cfaa5a594e5.pdf