Research On Valuation Optimization Of Artificial Intelligence Listed Companies Based On B-S Model

Artificial intelligence,or AI for short,has set off the wave of the fourth industrial revolution and becomes a new engine to accelerate economic and social development.Major economies around the world continue to strengthen the deployment of artificial intelligence industry,striving to grasp the dominant power in the new generation of technological revolution.China has also elevated AI to national strategic level,and strives to propel the deep convergence of AI industry with the real economy.The prosperous development of AI industry has also attracted much attention from the academic and capital markets,and it has become imperative to accurately assess the value of AI listed companies.However,as a high-tech industry,the value characteristics of AI have a large gap with traditional industries,such as the value is holistic and implicit,and intangible assets have a large impact on the value of the company,etc,so the traditional valuation method cannot assess the value of AI listed companies exactly.For this reason,this paper attempts to explore the valuation optimization problem of AI listed companies.Firstly,this paper analyzes the applicability of each common valuation model to the value assessment of AI listed companies by combining the development status and value characteristics of AI industry,and finds that the B-S model can effectively fit the value characteristics of AI listed companies.Then,to address the application difficulties of the original B-S model,this paper constructs an optimized B-S model from three perspectives: firstly,the EVA-mutation level method is introduced to measure the current value of the parameter underlying assets,EVA index can reflect the value characteristics of AI listed companies by adjusting accounting accounts,and the mutation level method can objectively calculate the weights of financial and non-financial factors;secondly,the dividend rate and transaction costs are introduced to make the model assumptions more consistent with the actual situation.Third,the introduction of fuzzy mathematics transforms the uncertain parameters in the model from fixed values to interval values,which breaks the limitation of rigidity in the selection of model parameters and enables the B-S model to be more comprehensively and accurately applied to the valuation study of AI listed companies.Finally,this paper selects the industry-leading AI listed company,Thunder,as a case company,and applies the optimized B-S model to value the company,and compares the traditional valuation results to verify the applicability of the optimized BS model constructed in this paper to the valuation of AI listed companies.Through theoretical research and case study,this paper systematically analyzes the current situation and difficulties of valuation of AI listed companies,and constructs a more convincing optimized B-S valuation model based on the B-S model,which enriches the valuation research of AI listed companies to a certain extent and also provides a new decision basis for company operators and market investors.