Asian Social Science; Vol. 11, No. 24; 2015 ISSN 1911-2017 E-ISSN 1911-2025 Published by Canadian Center of Science and Education 139 Trading Volume and Stock Returns Volatility: Evidence from Industrial Firms of Oman Hazem Al Samman 1 & Mohamed Khaled Al-Jafari 2 1 College of Commerce and Business, Department of Accounting and Finance, Dhofar University, Dhofar, Sultanate of Oman 2 College of Business Administration, Department of Accounting and Finance, Prince Mohammad Bin Fahd University, Al Khobar, Kingdom of Saudi Arabia Correspondence: Mohamed Khaled Al-Jafari, College of Business Administration, Department of Accounting and Finance, Prince Mohammad Bin Fahd University, P. O. Box 1664, Al Khobar 31952, Kingdom of Saudi Arabia. Tel: 966-53-005-2740. E-mail: aljafarimohamedkhaled@yahoo.com Received: April 28, 2015 Accepted: July 13, 2015 Online Published: August 18, 2015 doi:10.5539/ass.v11n24p139 URL: http://dx.doi.org/10.5539/ass.v11n24p139 Abstract This study analyzes the relationship between trading volume and stock return volatility for industrial firms listed on Muscat securities market. Several tests were utilized to include: Brailsford model, vector autoregressive model (VAR), and the pairwise Granger causality test. The empirical results provide evidence of a significant positive effect for return volatility on trading volume. Likewise, the VAR model provides evidence of a significant positive effect of trading volume on stock returns. On the other hand, the pairwise Granger causality test reveals that trading volume Granger-cause stock return. The previous findings are inconsistent with the weak-form of the efficient market hypothesis. Keywords: trading volume, stock return volatility, vector autoregressive model, pairwise Granger causality test, weak-form efficiency, Muscat securities market 1. Introduction There is a considerable amount of research that investigated the relationship between trading volume and stock returns. In a simple term, trading volume can be referred to as the amount of security or securities (even the entire market) that were bought and sold during a given trading day. Accordingly, many practitioners and academicians in the investment field consider trading volume as an important technical indicator utilized to measure the strength of the market. On the other hand, the efficient market hypothesis assumes that investigating this relationship will not help investors in achieving abnormal rate of return. Fama (1970) states that current stock prices reflect all security market information including the historical sequence of prices, rates of return, and trading volume. Therefore, it will be futile to use any trading rules to make a purchasing or selling decision based on past rate of return, trading volume or any past market data. Results from previous studies related to this issue are abundant and mixed. However, most of them regardless of the econometrical models they used, found a relation between trading volume and market return such as in Osborne (1959), Ying (1966), Morgan (1976), Epps & Epps (1976), Westerfield (1977), Rutledge (1984), Saatcioglu & Starks (1998), and Mahajan & Singh (2009). On the other hand, a very few studies found some conflicting results about this relationship such as in Granger & Morgenstern (1963), James & Edmister (1983), Rogalski (1978), and Harris & Raviv (1993). The aims of this paper are two-fold. First, it analyzes the relationship between trading volume, and stock return volatility for industrial companies listed on Muscat stock market. It is worth mentioning that there are a scarcity in the literature regarding the behavior of Omani financial market including the relation between trading volume and stock return volatility. Moreover, Oman is rapidly growing emerging market; therefore, this study will be beneficial to investors by giving them a brief preview to the structure of the Omani stock market if they are interested in entering such an emerging market. In addition, the study concentrates on examining only one sector, the industrial sector, instead of including all sectors. We believe that the characteristics of different sectors may have influence on the results. Therefore, this study limited itself to the industrial sector only to avoid biasness.