Portfolio Movement,Performance Test and Prediction of Institutional Investors under Multi-Constraints Relaxation
With the reform measures being implemented successively and the investment environment being optimized constantly in our capital market,this paper studies whether the performance of insti-tutional investors has being improved synchronously and how to predict it.We firstly use the classic portfolio selection model as benchmark model,and give the mathematical connotation of the effective frontier movement while the effective securities increase in two cases,which provides a theoretical expla-nation for portfolio optimization.Then we choose the open-ended funds as samples,test the statistical significance of their performance by using the data of weekly Sharpe ratio,and predict their performance by using the bidirectional gated recurrent unit model.Some conclusions are drawn as following.In theory,as the effective securities increasing,the effective frontier necessarily moves to the left and the optimal portfolio should continue to improve.However,in reality,there is not any obvious statistical evidence proving that the performance of institutional investors has sustained upward trend during the survey period,or has any long-term or short-term autocorrelation,which is robust across the test of different market cycles,modalities,and sample groups.The prediction model based on deep learning method has better performance than the traditional machine learning methods.