Y. Lai (Canada) and K.S. Tan (Canada & PRC)
Portfolio Value-at-Risk; Options; Monte Carlo and Quasi Monte Carlo simulation methods; Multivariate Student-t distributions; Multivariate normal distributions.
This paper considers Monte Carlo and quasi-Monte Carlo simulations of Value-at-Risk for portfolios with nonlinear relations to the market risk factors. The loss function is ap proximated by the delta-gamma-theta or quadratic method. Under the assumptions of multivariate normal and multi variate Student t distributions for the changes of the risk factors, the coverage probabilities related to Value-at-Risk are transformed into integral representations. By compar ing the relative magnitude of the estimated variance, the test results demonstrate that the lattice rule based quasi Monte Carlo method significantly outperforms the pseudo random number based Monte Carlo method.
Important Links:
Go Back
