On a Class of Alpha-stable Distributions and Its Applications in Estimating Market Risk
On a Class of Alpha-stable Distributions and Its Applications in Estimating Market Risk
Author(s): Daniel Traian Pele, Vasile Nicolae StanciulescuSubject(s): Economy, Financial Markets
Published by: EDITURA ASE
Keywords: stable distribution; Value at Risk; Tail Value at Risk; Solvency II;
Summary/Abstract: This paper uses a straightforward application of alpha-stable distributions for Romanian Stock Market, showing how a relatively simple implementation in the real world of a complex mathematical tool can be much more reliable in risk management than the classical Gaussian or log-normal distributions. In this paper we use a SAS macro for estimating the parameters of an alpha-stable distribution, using the time-series regression method from Kogon and Williams (1998). Using the Fast Fourier Transform, we estimate the probability density function, the cumulative distribution function and consequently, the VaR (99.5%) and TVaR (99%). For numerical illustration we are using daily logreturns of the BET Index; the measures of market risk, estimated on rolling windows using alpha-stable distributions and Gaussian distribution, are then compared to the actual logreturns of the BET Index. Numerical experiments show that using alpha-stable distributions for estimating VaR and TVaR can be a better alternative for managing the risk of financial assets
Journal: The Review of Finance and Banking
- Issue Year: 7/2015
- Issue No: 2
- Page Range: 7-15
- Page Count: 9
- Language: English