| Digital transformation is an inevitable choice in line with the current development of digital economy and the trend of national policies.By utilizing the new generation of digital technologies such as big data,blockchain,cloud computing,artificial intelligence and financial technology,enterprises apply digital technologies to various production and business activities and actively carry out digital transformation,which can enhance enterprise value creation,reduce enterprise risks and bring digital dividends to enterprises.The digital transformation makes the business work digitized and changes the reference method of project decision-making.Project risk management has gradually changed from "human control" to "intelligent control",and adopting intelligent risk management method has become the only way for the development.At the same time,the research has gradually introduced the method of intelligent decision,and introduced big data and other technologies to identify risks.Project management should adapt to the needs of the background of digital transformation,drive the transformation and upgrading of project risk management,data-driven management,and improve the quality of risk management.When companies invest idle funds accumulated in the process of production and operation in the stock market,they should not only strive for high yields,but also avoid high risks.The risk of stock price crash is the key to the success of such projects.If the risk of stock price crash occurs,it may lead to the failure of investment projects.Therefore,it is very important for enterprises to avoid the stocks with high risk of stock crash when they carry out risk management of investment projects.Firstly,this paper reviews the existing research,identifies the relevant factors that will have an impact on the stock price crash risk,selects the basic index system from the four aspects of the company’s financial index,non-financial index,macro factor and the degree of digital transformation,builds the forecast index system,and uses XGBoost feature engineering to screen the importance of each index.And 55 indicators are selected to build the prediction model.Secondly,the random forest,support vector machine and XGBoost models are used to predict the crash risk,so as to avoid the risk of investment projects.The XGBoost machine learning model has a relatively high accuracy in predicting the crash risk.On this basis,the introduction of digital evaluation index further improves the accuracy of prediction,and proves that the more digital a company is,the better its ability to avoid a share price crash.Finally,the risk prediction method proposed in this paper is applied to M Company’s investment project "Steady Treasure",and compared with the traditional risk prediction method adopted in this project and the market yield of the same period,it is finally found that the forecast method proposed in this paper can improve the overall return rate of the project in the actual investment project,and the return rate is higher than the result obtained by the traditional analysis method.And more than 3% higher than the market.Through the research,the following conclusions are drawn:(1)From the comparison of the results of the "Steady Treasure" project,it can be seen that the prediction index system and risk prediction model constructed in this paper perform well in predicting the risk of stock price crash and have certain practical value.(2)Combined with the background of digital transformation,"Wenjianbao" project applies digitalization to project management,makes full use of emerging technologies,enhances the value of data,and provides new ideas and methods for enterprises to carry out risk management of investment projects.(3)Put forward suggestions on the digital transformation of enterprise project management,create a new platform of project management,establish the awareness of digital transformation and strengthen the internal training of digital talents. |
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