Kozhukhivska O.A.

Optimization of Reinsurance Strategies Using DSS

The basic purpose of the work is a study of existing approaches to reinsurance directed towards modeling of distribution and minimization of risk for an insurance portfolio, and forming a strategy for its optimal reinsurance using developed decision support system. A method for a search of optimal reinsurance strategy is proposed. For this purpose statistical models were selected that correspond to the structure and volume of portfolio losses as well as the number of these losses. The simulation model for the total insurance losses is developed.

Probabilistic Modeling of Operational Actuarial Risks

Insurance companies are functioning in conditions of uncertainties of various types and nature what results in respective financial risks. All these reasons lead to the problem of timely recognition and development of mechanisms for the risks management. To solve the problem appropriate mathematical models are developed to describe the risks, and methodologies proposed for their practical application. The sources of the insurance fraud are detected and respective risk classification is presented.

Forecasting Volatility of Financial Processes with Alternative Models

An analysis of modern approaches to modeling of conditional variance for nonstationary heteroscedastic processes is performed. A stochastic volatility model structure is proposed for multidimensional case and the methodology is considered for its parameter estimation with the use of Markov chain Monte Carlo technique. The use of this approach provides a possibility for parameter estimation of linear and nonlinear models in conditions of stochastic disturbance influence with various distributions of random variables.