Research On Optimal Portfolio Based On Graph Neural Network

With the improvement of the national economic level,stock investment has gradually entered the public eye.As we all know,stock investment has great risks,and the yet to be perfected regulatory system,investors’ herd mentality and malicious behavior will increase the risk of the market.Therefore,for investors,what they are most concerned about is how to determine investment risks and how to make investment portfolios to obtain maximum returns when avoiding risks.Harry Markowitz first proposed the portfolio idea in the 1950 s and proposed the mean-variance model.This theoretical model lays the foundation for the subsequent research on portfolio problems.In order to obtain an investment portfolio model that is more in line with the Chinese market,and combine scientific methods to provide investors with a reasonable investment portfolio faster and more accurately,this paper,on the basis of the classic mean variance model,combines the current situation of my country’s investment market and the investment situation of Chinese investors.The needs are mainly studied in the following aspects:(1)Based on the classical mean-variance model,a practical concept of optimal investment portfolio is proposed.By predicting the variance of future returns,and then using the mean variance theory to calculate the risk of future investment,the portfolio with the smallest risk is obtained as the optimal portfolio.(2)Based on the concept of the optimal investment portfolio,the statistical method GARCH model and the machine learning method LSTM model are used to construct the investment portfolio.Firstly,the data in the selected stock pool is forecasted for the return variance,and on this basis,the optimal portfolio is constructed by calculating the portfolio with the smallest return variance.(3)Based on the concept of optimal investment portfolio,a graph convolutional neural network model is used to predict the return variance of stocks in the stock pool and construct an investment portfolio.First of all,by selecting 22 stocks in the main three regional sectors from the stock pool of the Shanghai Stock Exchange 50 according to the regional sectors,after constructing the graph,they are put into the model to predict the bear market,bull market and the yield variance of the shock range.The optimal weights are used to construct the optimal portfolio with the smallest return variance.The research shows that the optimal investment portfolio constructed by the GCN model,the optimal investment portfolio constructed by the GARCH model and the optimal investment portfolio constructed by the LSTM model can well resist the risks of the market,and can guarantee considerable returns in the bull market.In a bear market,you can achieve good returns,and when the stock market fluctuates,all three can achieve positive returns.Comparing the three models,the optimal portfolio constructed by GCN is better,no matter in bear market,bull market and shock range.Compared with the investment portfolio constructed by GARCH model and LSTM model,the optimal investment portfolio constructed by GCN model has better anti-risk ability and better economic benefits.