vector auto-regression model

The volatility of financial returns plays an important role in many empirical applications, such as portfolio allocation, risk management and derivative pricing. The purpose of this research is to explain the relationship between undesirable risk and desirable risk in predicting market return volatility. The research is descriptive in nature and applied in purpose. The statistical population of the study is the companies listed in Tehran Stock Exchange and the target sample of the companies listed in the cement industry from which the required research data can be extracted. The research period is from 1392 to 1397. This research has a theoretical model and the self-regression model was used to test the hypotheses. In the cement industry, according to the t-statistic and its coefficient of determination, it is clear that the predictor of market yield fluctuations correlates with undesirable and desirable risk. Also, the adjusted coefficient of determination is 51%, which indicates this effect.

In this study trading patterns and constituents of trading performances of individual and institutional investors have been investigated weekly، using an Auto Regressive model and a Grinblatt & Titman portfolio performance measure during 2008 to the end of 2012. The results show that while individual investors have a herding behavior، institutional investors take contrarian trading strategies. Evidences suggest that adopting the contrarian trading strategy by institutional investors resulted in better trading performance during most trading intervals، and the total net cash gains of this group has been achieved through a scheduled market timing. However، a poor stock selection has influenced part of the cash gain. On the other hand، adhering to the herding behavior by individual investors has resulted to a poor trading performance. Also، unsatisfactory market timing has undone the cash gains of a clever stock selection.