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The main goal of this paper is an application of the Bayesian inference in Value at Risk (VaR) prediction. As a VaR forecasts we use quantiles of the predictive densities obtained from AR(1)-GARCH(1,1) models (Osiewalski and Pipień 1999, 2003), with α-Stable or Skewed-t conditional distributions; Pipień (2005). From the definition, the predictive distribution yields probabilistic and easy to interpret information about ex ante uncertainty of forecasted variables. The predictive density combines the sampling assumptions of considered model, with uncertainty about model parameters. As a result, Value at Risk taken from predictive distributions should yield a flexible tool of risk measuring.(fragment of text)
Twórcy
autor
- Cracow University of Economics, Poland
Bibliografia
- Best P. (2000) Wartość narażona na ryzyko, Oficyna Ekonomiczna ABC, Kraków.
- Hendricks D., Hirtle B. (1997) Bank Capital Requirements for Market Risk: The Internal Model Approach, Federal Reserve Bank of New York Review.
- Jajuga K., Kuziak K., Papla D., Rokita P. (2001) Ryzyko wybranych instrumentów polskiego rynku finansowego, Rynek Terminowy 11, 133-140.
- Jorion P. (1996) Value-at-Risk, McGraw Hill, New York.
- Kupiec P. (1995) Techniques for Verifying the Accuracy of Risk Management Models, Journal of Derivatives 2, 173-184.
- Lopez J.A. (1999) Methods for Evaluating Value-at-Risk Estimates, Federal Reserve Bank of San Francisco Economic Review, 3-17.
- Osiewalski J., Pipień M. (1999) Bayesian Forecasting of Foreign Exchange Rates Using GARCH Models with Skewed-t Conditional Distributions, 25-th International Conference MACROMODELS'98, (ed.) Władysław Welfe, Łódź, 195-218.
- Osiewalski J., Pipień M. (2003) Univariate GARCH processes with asymmetries and GARCH-In-Mean effects: Bayesian analysis and direct option pricing, Przegląd Statystyczny 50, 5-29.
- Pipień (2005) Value at Risk Estimates and Capital Requirements for Market Risk Obtained From GARCH Predictive Densities, Acta Universitatis Lodziensis Folia Oeconomica 190, Łódź, 213-227.
- Sarma M., Thomas S., Shah A. (2003) Selection of VaR Models, Journal of Forecasting 22, 337-358.
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Bibliografia
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bwmeta1.element.ekon-element-000171295071