MONTE CARLO SIMULATION OF MULTIFOCAL STOCHASTIC SCANNING SYSTEM

Monte Carlo Simulation of Stochastic Processes

For all cases I present both simulations the risk-neutral and the real one. Risk-neutral simulations are used for derivatives pricing, whereas real simulations are used in other applications like: (a) value at risk; (b) hedging; and, (c) in some real options applications, e.g., to find out the option exercise probability and the waiting expected time before the option exercise (see the Timing s...

Stochastic Simulation,monte Carlo Methods and Applications1

Stochastic Programming by Monte Carlo Simulation Methods

We consider in this paper stochastic programming problems which can be formulated as an optimization problem of an expected value function subject to deterministic constraints. We discuss a Monte Carlo simulation approach based on sample average approximations to a numerical solution of such problems. In particular, we give a survey of a statistical inference of the sample average estimators of...

Efficient Monte Carlo Simulation with Stochastic Volatility

Monte Carlo simulation is a powerful aid in many fields. In this thesis it is used for pricing of financial derivatives. Achieving accurate results with Monte Carlo is rather timeconsuming due to its slow convergence. However, there are ways to improve the accuracy of each simulation, for instance by reducing the inevitable discretization bias. In our financial context, this concerns the discre...

Stochastic Simulation and Monte Carlo Methods

In these lecture notes we will work through three different computational problems from different application areas. We will simulate the irregular motion of a particle in an environment of smaller solvent molecules, we will study a biochemical control network and we will compute a numerical approximation to a high dimensional integral. Even though these three problems are different, and the wa...