Research On Investment Valuation Based On Real Option Theory And Recurrent Neural Network

Owing to the accelerated expansion of the economy,the discrepancy between the deficient throughput of highways and the burgeoning demand for mobility is becoming increasingly conspicuous,and the reconstruction and expansion projects of old highways are becoming more and more important.In order to make the investment decision of this kind of project meet the requirements of economic benefits,it is necessary to evaluate the value of the project.However,the traditional discounted cash flow method can not fully consider the value of uncertainty contained in such projects,such as construction cost,construction period,diversion effect,macro-economy,increasing toll period,vehicle toll collection standards,opportunity costs and other factors.In view of these uncertainties,investors can increase the value of the project through strict cost control,improving organizational management capabilities,strict progress management,communication with government departments and other measures.In order to consider the uncertainty contained in the highway expansion project more comprehensively and evaluate the project value scientifically and reasonably,the investment valuation method based on real option theory and LSTM recurrent neural network has been studied,and its effectiveness has been verified through case analysis.On the basis of recognizing the uncertainty value of highway reconstruction and expansion projects,this thesis applies the real options theory to construct the valuation model.Furthermore,the LSTM is introduced with reference to the real option parameters to construct the valuation model.In the case analysis,three valuation methods are compared: the traditional financial analysis method,the real option valuation method and the LSTM valuation method.The practice proves that the real option method and LSTM valuation method can effectively support investment decisions.After verification by case analysis,the valuation method constructed in this thesis can provide an effective reference for highway reconstruction and expansion projects,and further promote the optimization and upgrading of highway infrastructure.