A credit risk management problem for insurance investment companies is considered. An approach based on regression analysis with the use of CVaR estimate is proposed.
An estimate and a confidence interval are constructed for the Baxter parameter of a pseudo-Gaussian random process with the help of the Levi-Baxter-Gladyshev theorem for weighted variations. An essential advantage of the proposed estimation method is that it estimates a process not from its realizations but from its observations at discrete moments of time.In this article, pseudo-Gaussian random processes are considered [1]. The processes of this class that is a generalization of the class of Gaussian processes occur in statistical physics, radio engineering, radiology, and other applications of the theory of random processes.We will consider random processes x ( ) t , t Î[ , ] 0 1 , of the following form. We assume that h ( ), [ , ] t t Î 0 1 , is a Gaussian process with its correlation function r t s ( , ) , that E t h ( ) = 0, that z ( ), [ , ] t t Î 0 1 , is a sub-Gaussian process generated by a function B t s ( , ) [2], that h z and are independent, and that
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