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Introduction
----------------

This code simulates commodity spot prices using the Clewlow and Strickland one factor daily spot model using a Monte Carlo approach. The derived stochastic differential equations (SDEs) are solved using several finite difference schemes.

The paper detailing the equations is available online in ref 1 below.

The example requires a commodity forward curve and assumes a one factor...



Simulates the wall effect in a gaseous thermal neutron detector with a gaseous neutron converter (He-3) using the Monte Carlo method. Based on the gap thickness (in m) and the partial pressure of helium-3 (in bar), this program computes the...



Compute European call option price using the Heston model and a conditional Monte-Carlo method

[call_prices, std_errs] = Heston(S0, r, V0, eta, theta, kappa, strike, T, M, N)



Simulation model to accompany the article, "Monte-Carlo Simulation in MATLAB Using Copulas" in the November 2003 issue of MATLAB News&Notes. The function METAPOP runs the metapopulation simulation model described in the article.



A Monte-Carlo simulation meant to calculate the position of micronsized particles in an optical trap (seen as an harmonic potential). It returns the position in meters. Bead radius, corner frequency/ trapping stiffness, sampling frequency and...



The bootstrap is a way of estimating the variability of a statistic from a single data set by resampling it independently and with equal probabilities (Monte Carlo resampling). Allows the estimation of measures where the underlying distribution is...



The bootstrap is a way of estimating the variability of a statistic from a single data set by resampling it independently and with equal probabilities (Monte Carlo resampling). Allows the estimation of measures where the underlying distribution is...



The bootstrap is a way of estimating the variability of a statistic from a single data set by resampling it independently and with equal probabilities (Monte Carlo resampling). Allows the estimation of measures where the underlying distribution is...



The bootstrap is a way of estimating the variability of a statistic from a single data set by resampling it independently and with equal probabilities (Monte Carlo resampling). Allows the estimation of measures where the underlying distribution is...



The bootstrap is a way of estimating the variability of a statistic from a single data set by resampling it independently and with equal probabilities (Monte Carlo resampling). Allows the estimation of measures where the underlying distribution is...



this file showing how the Randomization in Monte-carlo method can get PI value (constant value)



SPSens is a complete software package written in C that estimates parameter sensitivities for stochastic models of chemical and biochemical reaction networks using Monte Carlo (MC) stochastic simulations. It is possible to estimate sensitivities...



3-in-1: .NET, COM and XML Web service Components for pricing option and futures contracts using Monte Carlo and Finite Difference techniques. General Monte Carlo pricing framework: wide range of contracts, price, interest and vol models. Price...



Price option and futures contracts using Monte Carlo and Finite Difference techniques. General MC pricing framework: wide range of contracts, price, interest and vol models. Prices European, Asian, American, Lookback, Bermuda and Binary Options...



HapCluster is a software package for linkage disequilibrium mapping.

It is based on a Bayesian Markov-chain Monte Carlo (MCMC) method for fine-scale linkage-disequilibrium gene mapping using high-density marker maps.



Computes BER v EbNo curve for convolutional encoding / soft decision Viterbi decoding scheme assuming BPSK.

Brute force Monte Carlo approach is unsatisfactory (takes too long) to find the BER curve.

The computation uses a...



In Evolutionary Multiobjective Optimization (EMO), an algorithm produces a set of points in the performance space as an estimation of the Pareto front. A quantitive measure is desired to estimate the closeness of the estimated data points to the...



JDprice.m : Compute European call option price using a Log-Uniform Jump-Diffusion model.
Algorithm used: Monte Carlo with antithetic and control variates techniques.

JDimpv : Compute the implied volatilities from the market values...



Applying the inverse transform method to the normal distribution entails evaluation of the inverse normal. This is the Beasley-Springer-Moro algorithm for approximating the inverse normal.

Input: u, a sacalar or matrix with elements...



As a coursework, we are required to price a double barriers knock-in binary put option. We used finite difference method in 24 ways and multinomial lattice in 12 ways. We also implemented analytic and Markov chain method. At the end, we compared...