The purpose of this paper is to study the relationship between trading volume and unconditional price volatility on the Tunisian Stock Market in order to provide an empirical support to either the hypothesis of the strategic asymmetric information models or the hypothesis of competitive asymmetric information Models. More specifically, it aims to test the volume-volatility relationship and identify the component of trading volume (number of transactions or trade size) that explains more price volatility and drives this relationship. Our empirical tests are based on daily and intraday data related to the 43 most active and dynamic listed stocks on the Tunisian Stock Market from 02 January 2008 to 29 June 2012 for the daily analysis and from 03 October 2011 to 28 September 2012 for the intraday data. Our empirical analysis reveals several results. First, we confirm the strong positive contemporaneous relationship between trading volume and unconditional price volatility similarly to the Mixture of Distribution Hypothesis (MDH). Second, we show that whatever the frequency of used data, daily or intraday, the number of transactions is much more significant than the trade size in the explanation of the volatility and seems to be the dominant factor that drives the positive volume-volatility relationship. Third, we find that trade size has no explanatory power of the volatility beyond that the number of transactions and the positivity of the volume-volatility relationship reflects simply the positive relationship between number of transactions and volatility. Overall, our empirical results support the hypothesis of the strategic models and challenge the hypothesis of competitive models.Keywords: trading volume, unconditional volatility, number of transactions, trade size, volme-volatility relationship, information flow, mixture of distribution hypothesis, competitive asymmetric information models, strategic asymmetric information models

This research is a feedback to Wang (2015) suggesting that realized returns should be used in conjunction with ICCs to make more robust inferences about expected returns. We examine the validity of six firm-specific ICCs along with a synthetic one, in the Tunisian context, according to their feasibility and their correlation with realized return. The examined estimators are calculated according to three types of earnings forecasts: smoothing, random walk and cross-section. These estimators represent three main valuation approaches: Present Value of Expected Dividend (PVED), Residual Income Valuation Model (RIV) and Abnormal Earnings Growth (AEG). Our results confirm the assertions of Gerakos and Gramacy (2013) on random walk forecasts" good performance as well as those of Li and Mohanram (2014) on the poor quality of Hou et al. (2012)"s cross-section forecasts. Furthermore, dividend seems best reflecting Tunisian stock market expectations concerning future revenues which would be generated by the valuated asset. These findings bring into question the relevance of new accounting valuation approaches which are anchored rather on equity book value (RIV) and on earnings forecasts (AEG).