The Monte Carlo simulation estimates the probability of different outcomes in a process that cannot easily be predicted because of the potential for random variables.

Monte Carlo integration – the process of numerically estimating the mean of a probability distribution by averaging samples – is used in financial risk analysis, drug development, supply chain ...

Monte Carlo methods and Markov Chain algorithms have long been central to computational science, forming the backbone of numerical simulation in a variety of disciplines. These techniques employ ...

There are two flavors of QMC, (a) variational Monte Carlo (VMC) and (b) projector Monte Carlo (PMC). VMC starts by proposing a functional form for the wavefunction and then optimizes the parameters of ...

The Monte Carlo pathwise sensitivities approach is well established for smooth payoff functions. In this work, we present a new Monte Carlo algorithm that is able to calculate the pathwise ...

We consider the pricing of a special kind of option, the so-called autocallable, which may terminate prior to maturity due to a barrier condition on one or several underlyings. Standard Monte Carlo ...

The Monte Carlo method is a type of algorithm that reveals a distribution by randomly sampling its elements again and again. For example, say there are 40 red marbles, 20 green marbles, 25 orange ...

Learn how Value at Risk (VaR) predicts possible investment losses and explore three key methods for calculating VaR: ...