Some Result for the Mathematical Expectation and Standard Deviation in a Non-Stationary Marcovian Distribution of Lin and Yang Modified Model

Abstract

The purpose of research and making credit risk models is focused on the creating of valuating techniques of forecast losses in value as a result of their exposure to the credit market. Put in simple words, they aim to build predictive models of potential losses within a predetermined time period. These losses are mostly of monetary values created by lending in the form of loan. The entirety of the loan portfolio is realized by individual loans disbursed by FI-s. So, a loan portfolio is truly an amount in cash value, but simultaneously this portfolio is also a set in the number of borrowers. In this way, it can be considered equally important both "definitions" of the loan portfolio; (i) monetary value and (ii) the number of loans. The treatment of loan portfolio in number of borrowers and treatment of periodic classification process as a random process of homogeneous Markov chain type created the premise for further development of non-stationary marcovian probabilities.In this article we are presenting some interesting result and conclusions about mathematical expectation with t- steps and dispersion with t- steps of Lin and Yang modified distributions. Also, important results and of practical utility are considered by us, the case of the mathematical expectation with one-step and one-step dispersion with which we have presented below as results of general confirmations.