MODELS AND METHODS OF OPTION VALUE ASSESSMENT AND THE IMPLIED VOLATILITY 

Ovechkin Roman Mikhaylovich, Postgraduate student, Penza State University (40 Krasnaya street, Penza,
Russia), nifect@gmail.ru
Finogeev Aleksey Germanovich, Doctor of engineering sciences, professor, sub-department of computer aided design, Penza State University (40 Krasnaya street, Penza, Russia), finogeev@sura.ru 

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Background. Effective means of solving problems of management in financial and credit institutions are automated decision support systems, which are the base of the expert technology ideology. Of particular interest is the process of automating analytical processing of banking information in terms of optimizing the
management of credit risk by trading in derivative financial products - credit derivatives. The major factor in trading of the derivatives is hedging (insurance) price or currency risk in time or getting speculative profit from price changes of the underlying asset. Volatility that means statistical measure of the tendency of price variability
of a financial product should be considered as the major financial indicator of risk management. The purpose of this work is the development and implementation of models and methods of assessment of additional values for such derivative types as "option", "estimated value of the option" and "implied volatility" for automated monitoring and decision support in the field of stock trading of credit derivatives and securities for minimizing credit risks of financial institutions.
Materials and methods. The paper describes the models and analytical methods for calculating the values of "recommended price" and "implied volatility" for derivative financial products like "option" for assessment of their value in monitoring the stock market so that to support decision-making in the field of trade credit derivatives. The improved Black – Sholes formula and the algorithm for finding the implied volatility through numerical methods are used for assessing the value of the options.
Results. The results of the theoretical researches are aimed at creating new approaches to monitoring and automated decision support for credit risk management of medium and large commercial banks in the field of derivative financial products trading that will improve the quality and reliability of management decisions. Analysing banking activities in the field of risk management through trading of credit derivatives and other securities there was used a formalized approach to the modeling and assessment of market conditions, models and calculation methods of derivative financial instruments in decision support systems.
Conclusions. The developed models and analytical methods for calculating such values as "recommended price" and "implied volatility" for derivative financial products like "option", in contrast to existing models use a combination of the Black – Scholes formula, the binomial tree and the numerical bisectional search method that allows accuracy and computational complexity in solving the problem. The optimal accuracy of the analytical data in real time is provided due to the automated selection of the number of steps in the construction of the binomial tree and the number of bisectional search iterations. 

monitoring, decision support system, user interface, hedging, credit derivative. 

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