1. Introduction

Credit Metrics is a methodology of estimating possible changes in value of the portfolio of exposures provided by J.P.Morgan [3]. The type of risk under the consideration is the one caused by the change in a credit rating of the issuer of the financial instrument. Since the subject of the interest is the whole portfolio value, the joint behavior of the exposures must be analyzed and properly modelled. Conventional  Credit Metrics' approach is based on the assumption that asset returns of each issuer company is univariate Normally distributed and their joint behavior is modelled by multivariate Gaussian distribution. Being relatively easy to apply, given assumption underestimates possible risks due to inability of the model to properly describe the dependence structure between companies' asset returns. Within the frame of the Credit Metrics' Asset value model, the main objective of the project is to capture the dependence structure in a portfolio of bonds issued by Lukoil, Gazprom and Norilsk Nickel by means of Copula functions. Copula functions are powerful tools that were discovered by Sklar back in 1959, but found their application in finance only by the late 90s of the last century. Copulas are used in modelling a multivariate distributions given margins, and are useful in separating the information about margins from their dependence structure [2]. Before getting started with portfolio analysis, this paper gives a general overview of Copula theory, conventional dependence measures and method of pair-copula construction.