1
-
2
of
2
results (0.57 seconds)
Sort By:
-
Approximating the Effects of Parameter Uncertainty on Value at Risk Estimates
(15), and (16), we write (6) as ∂VaR(θS) ∂θSi ≈ (17) − h f S˜r∗ [ r∗∑ j=o T−1 ({ P ′N ( T (fX) ) ... offset by the marginal cost of further reduction. 17 7 Conclusion We derived a first order approximation ...- Authors: Jacques Rioux, Steven Major, Donald Erdman
- Date: Nov 2010
- Competency: External Forces & Industry Knowledge>Actuarial methods in business operations
- Topics: Finance & Investments>Risk measurement - Finance & Investments; Finance & Investments>Value at risk - Finance & Investments
-
Toward a Unified Approach to Fitting Loss Models
following cubic functions provide a good approximation. 17 10% : 0.9289p3 − 2.6822p2 + 2.5761p+ 0.4011 5% ... simplicity and favors the lognormal model. Figures 17 and 18 below provide p−p plots for the two additional ...- Authors: Stuart Klugman, Jacques Rioux
- Date: Jan 2003
- Competency: Results-Oriented Solutions; Technical Skills & Analytical Problem Solving
- Publication Name: Actuarial Research Clearing House
- Topics: Modeling & Statistical Methods