It is often argued that Quasi-Monte Carlo Methods (QMC ) only work for problems of low effective dimension that encompass most of financial problems. We will show here some evidence that, with the Sobol construction, they can be suited for problems with high effective dimension in the truncation...

The aim of this work is to understand and measure to what extent equity options price credit risk. With the exception of Toft and Prucyk (1997), which is a dated work based on the simplistic assumption of a reference company issuing perpetual debt, all the work in the literature which try to...

There is an inaccurate formula in Huang et al. (1996) [Huang J., M. Subrahmanyam, and G. Yu (1996) Pricing and Hedging American Options: A Recursive Integration Method. Review of Financial Studies 9 (1):277–300]. In fact, a substantial term is missing in their equation (14) for computing the...

The two main issues for managing wrong way risk (WWR) for the credit valuation adjustment (CVA, i.e. WW-CVA) are calibration and hedging. Hence we start from a novel model-free worst-case approach based on static hedging of counterparty exposure with liquid options. We say "start from" because...

Hedging at-the-money digital options near maturity, remains a challenge in quantitative finance. In the present work, we carry out a hedging strategy by means of a bull spread. We study the probability of super- and sub-hedge the digital option and minimize the probability of a sub-hedge...

In this article we propose an efficient Monte Carlo scheme for simulating the stochastic volatility model of Heston (1993) enhanced by a non-parametric local volatility component. This hybrid model combines the main advantages of the Heston model and the local volatility model introduced by...

Chen and Shen (2003) argue that it is possible to improve the Least Squares Monte Carlo Method (LSMC) of Longstaff and Schwartz (2001) to value American options by removing the least squares regression module. This would make not only faster but also more accurate. We demonstrate, using a large...