Value Evaluation Of Biomedical Enterprises Based On Random Forest Algorithm

With the continuous improvement of people’s living standards,biopharmaceuticals have gained widespread attention because of their role in protecting people’s health,and the capital market has become increasingly active regarding the M&A and restructuring of these enterprises.Biopharmaceutical enterprises are increasingly demanding in the selection of valuation methods for biopharmaceutical enterprises due to their long R&D cycles,high technology content,large capital requirements and policy influence,etc.How to However,the traditional enterprise value assessment methods have been challenged in evaluating such enterprises.Therefore,it has become a critical and urgent issue to analyze the shortcomings of traditional methods and explore new value assessment methods for biopharmaceutical enterprises.This thesis summarizes and analyzes the current situation of the application of value assessment techniques for biopharmaceutical enterprises,and concludes that the existing traditional enterprise value assessment methods have certain shortcomings,and it becomes a need to explore other feasible methods.This thesis tries to assess the value of biopharmaceutical enterprises based on the characteristics of biopharmaceutical enterprises using a random forest model,which is based on the cart regression tree in decision trees,and the model is constructed by randomly selecting not only the samples but also the features on the basis of self-help aggregation,the model is evaluated by inputting relevant index data,and the final output result is the enterprise value assessed by the model after the model training procedure.In this thesis,by collecting the financial statement data of about 400 listed biopharmaceutical companies in Guotaian 2021,we study the financial factors affecting the value of biopharmaceutical companies,quantify their characteristic factors and conduct modeling,and use the trained random forest model to empirically analyze the value assessment of biopharmaceutical companies,and compare the results of the random forest model with the market value of companies.The results of the study and analysis lead to the following conclusions: the use of random forest model for assessing the value of biopharmaceutical enterprises solves the problems of many influencing factors and large uncertainties in the valuation of biopharmaceutical enterprises,and its results have high accuracy and are not easily affected by outliers,and the stability of the model is also high,and the random forest model performs better in terms of results compared with traditional valuation methods.Taking listed biopharmaceutical companies as the entry point,this thesis assesses the value of listed biopharmaceutical companies according to their characteristics,which is conducive to improving the market valuation system of listed biopharmaceutical companies and promoting the healthy development of the listed biopharmaceutical industry.In addition,the technical ideas derived from the empirical study of enterprise value assessment in the biopharmaceutical industry in this thesis can also provide references for assessing enterprise value in other industries.