Stable modeling of value at risk
The value-at-risk (VAR) measurements are widely applied to estimate exposure to market risks. The traditional approaches to VAR computations-the variance-covariance method, historical simulation, Monte Carlo simulation, and stress-testing-do not provide satisfactory evaluation of possible losses, In this paper, we analyze the use of stable Paretian distributions in VAR modeling. (C) 2001 Elsevier Science Ltd. All rights reserved.
value-at-risk market risks stable paretian distributions var computations