Abstract
Local volatility models usually capture the surface of implied volatilities more accurately than other approaches, such as stochastic volatility models. We present the results of application of Monte Carlo (MC) and quasi-Monte Carlo (QMC) methods for derivative pricing and risk analysis based on Hyperbolic Local Volatility Model. In high-dimensional integration QMC shows a superior performance over MC if the effective dimension of an integrand is not too large. In application to derivative pricing and computation of Greeks, effective dimensions depend on path discretization algorithms. The results presented for the Asian option show the superior performance of the QMC methods, especially for the Brownian Bridge discretization scheme.
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