
doi: 10.2139/ssrn.1460747
This paper analyzed the investors’ trading in Chinese financial market from a behavioral perspective, which demonstrated how investors’ trading strategies affect abnormal returns of securities. In the analysis, we classified total trading into individual investors’ trading and institutional investors’ trading. By constructing the trading intensities measures, we justified individual investors are contrarian when buying or selling securities and institutional investors may engage in positive feedback trading strategies. The predictive powers of the trading strategies were also justified in the paper, and the information contained in trading measures may be more than those in abnormal returns and volumes. Furthermore, we also analyzed the interactions between individual investors and institutional investors and their effects on securities’ returns and emphasized the importance of institutional investors in this process. Another point analyzed in this paper is about the responses of individuals and institutional investors to the announcement of analysts’ recommendations. We found that institutional investors may use the information about the changes of analysts’ recommendations when compared to the behaviors of individual investors.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
