On the Risk Management with Application of Econophysics Analysis in Central Banks and Financial Institutions
The purpose of this research article is to discover how the econophysics analysis can complement the econometrics models in application to the risk management in the central banks and financial institutions, operating within the nonlinear dynamical financial system. We consider the modern risk management models and show the appropriate techniques to calculate the various existing risks in the finances. We make a few comments on the possible limitations in the models of statistical modeling of volatility such as the Autoregressive Conditional Heteroskedasticity (GARCH) model, because of the nonlinearities appearance in the nonlinear dynamical financial systems. We propose that the various types of nonlinearities, which can originate in the financial and economical systems, have to be taken to the detailed consideration during the Cost of Capital calculation in the finances and economics. We propose the new theory of nonlinear dynamic volatilities and the new nonlinear dynamic chaos (NDC) volatility model for the statistical modeling of financial volatility with the aim to determine the Value at Risk.
|Date of creation:||Nov 2012|
|Date of revision:|
|Publication status:||Published in The Financial Times, The Bodley Head and The Random House first annual essay competition in London in the UK in 2012|
|Contact details of provider:|| Web page: http://arxiv.org/|
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- Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
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- Dimitri O. Ledenyov & Viktor O. Ledenyov, 2012. "On the new central bank strategy toward monetary and financial instabilities management in finances: Econophysical analysis of nonlinear dynamical financial systems," Papers 1211.1897, arXiv.org.
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