Research On The Risk Decision Based On Bayesian Network And Options Game

Project decision is often and widely used in organizations,because of Economy Globalization,dynamic characteristics of competition and increasing speed of technology innovation,project decision in such highly turbulence environment is of uncertainty and complexity,that's why the research on investment risk analysis and decision system has important realistic value.A risk analysis method based on Bayesian network and option game is proposed to quantitatively project risk,used D-S technology for data integration . Unlike the traditional methods,at first this paper introduced the options game theory , analyzed the basic ideas and specific steps of the options game. When analyzed the risk by options game theory, at the investment activities, irreversible, uncertainties and competitive of investment opportunities are summarized into the same analysis framework of system. Then we introduced the fundamental of the Bayesian Network model, the currency method of establishing the model and some particular algorithm, setting up the risk of a decision-making process by the Bayesian network .In the theory of incomplete markets, interesting connections between Black-Scholes models and game theory have been analyzed and the necessary and sufficient conditions on the existence of Nash equilibrium has been built as well in the paper. At the same time, an option games analysis framework of the strategic investment decision of new product is provided with first-mover and second-mover's advantage considered. The optimal output and the time of equilibrium investment under duopoly have been studied. Decision rules and conditions in equilibrium strategy investment have been analyzed.In addition, take the project investment for example; this paper makes use of the Bayesian networks which can realize risk control of ongoing investment. Moreover,with real option theory,the paper realized dynamic benefit and risk evaluation,built static selection and dynamic analysis of project investment. Meantime, results above have been verified by a Matlab numerical example.At last, the paper concluded the advantages and disadvantages in the study, and presented a newest idea and a useful trial to research optimal of risk investment strategy.