It has been recently shown that rough volatility models, where the volatility is driven by a
fractional Brownian motion with small Hurst parameter, provide very relevant dynamics in …

We show that multigrid ideas can be used to reduce the computational complexity of
estimating an expected value arising from a stochastic differential equation using Monte …

Praise for The Volatility Surface" I'm thrilled by the appearance of Jim Gatheral's new book
The Volatility Surface. The literature on stochastic volatility is vast, but difficult to penetrate …

Building upon the ideas introduced in their previous book, Derivatives in Financial Markets
with Stochastic Volatility, the authors study the pricing and hedging of financial derivatives …

Using an Euler discretization to simulate a mean-reverting CEV process gives rise to the
problem that while the process itself is guaranteed to be nonnegative, the discretization is …

Tap into the power of the most popular stochastic volatility model for pricing equity
derivatives Since its introduction in 1993, the Heston model has become a popular model for …

The role of characteristic functions in finance has been strongly amplified by the
development of the general option pricing formula by Carr and Madan. As these functions …

This book covers foreign exchange options from the point of view of the finance practitioner.
It contains everything a quant or trader working in a bank or hedge fund would need to know …

The use of the Heston model is still challenging because it has a closed formula only when
the parameters are constant [S. Heston, Rev. Financ. Stud., 6 (1993), pp. 327–343] or …

Numerical integration methods for stochastic volatility models in financial markets are
discussed. We concentrate on two classes of stochastic volatility models where the volatility …