Quasi–Monte Carlo methods have become an increasingly popular alternative to Monte
Carlo methods over the last two decades. Their successful implementation on practical …

The stochastic differential equations for affine jump diffusion models do not yield exact
solutions that can be directly simulated. Discretization methods can be used for simulating …

Stochastic volatility models are increasingly important in practical derivatives pricing
applications, yet relatively little work has been undertaken in the development of practical …

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 cryptocurrency market is volatile, non-stationary and non-continuous. Together with
liquid derivatives markets, this poses a unique opportunity to study risk management …

Generating sample paths of stochastic differential equations (SDE) using the Monte Carlo
method finds wide applications in financial engineering. Discretization is a popular …

The stochastic alpha-beta-rho (SABR) model becomes popular in the financial industry
because it is capable of providing good fits to various types of implied volatility curves …

We derive analytic series representations for European option prices in polynomial
stochastic volatility models. This includes the Jacobi, Heston, Stein–Stein, and Hull–White …

We propose an accurate method for pricing arithmetic Asian options on the discrete or
continuous average in a general model setting by means of a lower bound approximation. In …