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This paper presents a duration dependent model for analyzing the evolution of credit ratings. It considers the backward recurrence process to tackle the time of permanence problem in the rating classes. In this way it is possible to manage the duration effects, which represent one of the most important features in rating dynamics. Furthermore, the paper shows how it is possible to compute the cost of capital that an organization is required to pay for the capital used in financing its activities. A real data application using Standard & Poor’s historical database is provided.

The paper introduces the multiple criteria decision making method using one of basic problems of linear programming as its computational principle; thus, the algorithm is based on the assignment problem enabling the assignment of alternatives and rank. The known basic algorithm of the assignment method is described and some modifications are proposed that take into account differences among criterial values or some stochastic elements. Finally, the article offers some practical application in investment decision making process in the field of capital market with shares funds.

We present a novel approach to the study the dynamics of stock market correlations. This is achieved through an innovative visualization tool that allows an investigation of the structure and dynamics of the market, through the study of correlations. This is based on the Stock Market Holography (SMH) method recently introduced. This qualitative measure is complemented by the use of the eigenvalue entropy measure, to quantify how the information in the market changes in time. Using this innovative approach, we analyzed data from the New York Stock Exchange (NYSE), and the Tel Aviv Stock Exchange (TASE), for daily trading data for the time period of 2000–2009. This paper covers these new concepts for the study of financial markets in terms of structure and information as reflected by the changes in correlations over time.

The paper deals with the methodology of computer modeling and simulation of complex markets with electricity and related products. The methodology is presented using a particular configuration of Central European markets with decentralized trading and international electricity transfers. The modeling approach is based on pure computer numerical solution in discrete state space determined by problems on which the modeled players are expected to decide—price offered for electricity supplied to various markets, breakdown of total power generation into individual commodities (yearly band, monthly band, spinning reserve) and setting bids in auctions for cross-border profiles. Similar approach to decision-making is adopted on the buyer’s side. Buyers are expected to strive to contract power supplies in the way that is most advantageous for them. The generated state space is then analyzed using concepts of mathematical game theory. In this way, we obtain a prediction of probable decisions of modeled player s in their market competition. Finally, we present a simplified power system forecast for Central Europe for year 2009.

This paper deals with a methodology of computer modeling and simulation of market competitive situations using game theory. The situations are thematically focused mostly to models of commodity markets but the applications of the methodology can be wider. This methodology covers the whole modeling work, including a primary specification of a problem, making an abstract model, making a simulation model, design of a state space of the problem and the simulator itself. As a whole, the methodology represents a complete framework for implementation of computer models of commodity markets suitable for their further analysis and prediction of their future evolution. The main contribution of the paper consists in the algorithmic implementation of computer processing of large strategic game.