Risk analysis based on stochastic dynamical systems theory

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The present study focuses to the problem of project value evaluation with risk in a framework of stochastic dynamical systems theory. The results obtained in this work are as follows :(1) We have shown that the risk-sensitive value measure related to utility indifference pricing which is regarded as a sort of expected invariance for stochastic systems has many superior properties.(2) We have examined that a random NPV moments probit model derived from a simplification of the risk-sensitive value measure is suited to practical use through the application to a project value evaluation problem of thermal power plant.(3) As some issues related to the theme of the present research, we have formulated a symplectic numerical scheme for stochastic Hamiltonian dynamical systems and investigated electric power market prices and the long-term reliability of power system quantitatively.