**6. Conclusions**

This paper examines EMH and tests the news impact on stock returns by employing monthly data for 15 international equity markets. A simple way to test market efficiency is by examining the dependency of return series. By focusing on the univariate correlation analysis of stock returns, the statistics sugges<sup>t</sup> that the null for the absence of correlations up to 12 months is rejected for 13 out of 15 markets; the exceptions are the U.S. and Canada. However, tests of the absence of autocorrelations of absolute values of stock returns are uniformly rejected for all markets under investigation.

We also test whether the news variables have significant effects on the stock returns. By using EPU indices as news variables, this study concludes that stock returns are negatively correlated with EPU in the current period, but are positively correlated in the following two periods, and the estimated coefficients are statistically significant in the majority of cases. This finding reflects a pattern of behavior among investors whose fears about the market, following bad news and the accompanying uncertainty, prompt them to sell off their stocks. This sell-off results in a fall in prices. However, rational traders may take advantage of declining prices and place orders, causing a bounce back in prices in the following two months. This phenomenon produces positive relations between stock returns and lagged news; this group of investors will receive uncertainty premiums, regardless of whether the news originates from a local market or the global market.

In placing the EPU innovations in the variance equation, the evidence consistently shows a predictive power in projecting stock volatility, not only using local news but also global lagged news. The only exception to this finding is the Chinese market, where we are unable to find a significant effect of EPU innovation in predicting variance. In sum, the evidence drawn from this study concretely shows that the news is significant in predicting future stock returns, which allows us to reject the EMH.

Since this study focuses on the time series dynamics to examine the EMH, the impact of accounting information on stock prices has been excluded from this study, but will be considered in future study by factoring in the quality of financial reporting along the line of Ohlson (1995); Glezakos et al. (2012) and Jianu et al. (2014).

**Funding:** This research was partly funded by the Marshal M. Austin Endowed Chair established in March 1996, Le Bow College of Business, Drexel University.

**Conflicts of Interest:** The author declares no conflicts of interest.
