Analyzing the Causal Relations between Trading Volume and Stock Returns and between Trading Volume and Return Volatility in Tehran Stock Exchange
Publish place: Iranian Journal of Finance، Vol: 2، Issue: 4
Publish Year: 1397
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_IJFIFSA-2-4_002
تاریخ نمایه سازی: 24 فروردین 1401
Abstract:
Identifying the causal relations between trading volume and stock returns and between trading volume and return volatility plays a vital role in identifying profitable investment opportunities. In this study, the Granger causality test was conducted to analyze the causal relationships between the mentioned variables in Tehran Stock Exchange. Consequently, the Vector Auto Regression (VAR) model was employed to determine the conditional mean equations of returns and volume. Moreover, the bivariate Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model was used to model the conditional variance equation, stating the relationship between volume and return volatility. According to the results, no bilateral causal relationship can be ascertained between returns, volume, and return volatility. In other words, return and return volatility could barely predict volume; therefore, volume cannot be the Granger causality of the other two variables. However, stock returns were found to have an important role in determining the volume. Likewise, return volatility can be used to predict volume accurately. In fact, stock returns and the return volatility were both the Granger causalities of the volume.
Keywords:
Stock Returns , Volume of trade , Return Volatility , Causal Relationships , Vector Auto Regression model , Granger causality , GARCH
Authors
Mohammad Reza Rostami
Assistant Prof., Department of Finance, Faculty of management, Alzahra University, Tehran, Iran.
Peyman Alipour
MSc., Department of Finance, Faculty of Management, University of Tehran, Tehran, Iran.
Adel Behzadi
Ph.D. Candidate, Department of Finance, Faculty of Management, University of Tehran, Tehran, Iran.
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