Herding behavior is a term used to describe how a group of investors will imitate one another in order to make judgments and take action. The CSAD model developed by Chang et al. (2000) is used in this study to investigate herding behavior in the Vietnamese stock market. The empirical findings demonstrate the presence of a herding tendency in this market. The market return is further separated into subgroups to show that herd behavior manifests under various market situations. The findings show that when markets start to fluctuate, investors have a larger tendency to follow the crowd (the market is going up or going down, or the market has an extremely high return or extremely low return). The impact of the Singapore stock market on the Vietnam stock market is then evaluated. This empirical finding may be used by investors to develop investment plans and broaden their prospects for profit.

<p>Nowaday, Corporate Socially Responsible (CSR) mutual funds are becoming a popular investment option for investors. However, no any research confirms whether CSR Mutual fund activity is better than market index or not. Besides, we should have one method can help con sequently investors in making the decision to select appropriate investment funds. In this study, we measure the financial performance of a sample of 15 CSR mutual funds in the world, with the monthly return over the period 2008-2013, then we propose the dession table. We first use the measures to evaluate the performance of mutual funds such as Alpha (α), Sharpe Ratio (SR), and Information Ratio (IR). And then, we use the obtained decision table to evaluate the predictability by each measure. The results indicate that only 3 of the 15 CSR mutual funds achieve good performance results based on the statistical significance of the two measures Sharpe Ratio and Information Ratio. In addition, the IR is suggested to evaluate and make investment decisions in the future and it also is the best one among the three measures. The decision table suggest investors a measure forecast accuracy way.</p>