Carlo Gavazzi Relays

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)*******************************************************************************INPUTS: S0 - Current price of the underlying...

This GUI accepts the various constants needed to run a Black-Scholes calculation for pricing several European options:Put, Call, Straddle, Strangle, Bull Spread, Bear Spread, ButterflyIt plots the pricing surface for the appropriate option and then runs a number of Monte Carlo simulations (d

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.MATLABdlT«'s Statistics Toolboxd-OC?D? includes a variety of...


Platforms: Matlab

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 between 0 and 1Output: x, an approximation for the inverse normal...


Platforms: Matlab

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 these four methods and Monte Carlo method.In this...


Platforms: Matlab

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 number of sampled points can be varied. It is small...


Platforms: Matlab

A zip file containing the examples that were used in the webinar: "Teaching and Research of Computational Finance with MATLAB"Including:* GUI for pricing an options via CRR tree* Script for priocing via Finitie differences* GUI for pricing via the Monte Carlo method of Longstaff and Schwartz*...


Platforms: Matlab

Online Simulation of Brownian motion in 2d, 3d. Stock Simulation with EWMA, GARCH(1,1). One factor equilibrium interest rate model simulations, estimation and residual testing using Euler's appr. Monte Carlo option pricing with stochastic interest rates.


Platforms: Matlab

Chi-square tests of homogeneity and independence.Computes the P-value for I x J - table row/col independence.Ref.: DeltaProt toolbox at http://services.cbu.uib.no/software/deltaprot/Input:X: data matrix (I x J -table) of the observed frequency cells.method: 'RC': Read-Cressie power divergence...


Platforms: Matlab

Returns a matrix of iid random numbers distributed according to the one-parameter Mittag-Leffler distribution with index (or exponent) beta and scale parameter gamma_t. The size of the returned matrix is the same as that of the input matrices beta and gamma_t, that must match. Alternatively, if...


Platforms: Matlab

Function PAGE computes the value of Page test statistic for layout matrix x, with subjects in rows and treatments in columns. Midranks are calculated with Matlab's TIEDRANKS.Function MCPAGE computes the value of Page test statistic for layout x and B random within-subject permutations of x,...


Platforms: Matlab

The script gf_mmc_driver.m runs multiple independent instances of a MMC method in parallel with MATLAB's Distributed Computing Toolbox. The outer loop in script gf_mmc_driver.m represents the basic MMC iteration, which initializes and runs a Markov chain and performs a Berg update. In each of the...


Platforms: Matlab

A collection of M-Files that provide a succesful implementation of the difficult problem of numerical computation of multivariate normal probabilities. This is very useful for the distributed detection with nuisance parameters and in classical multivariate problems. Two methods are used for which...


Platforms: Matlab

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 unknown or where sample sizes are small. Their...


Platforms: Matlab

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 unknown or where sample sizes are small. Their...


Platforms: Matlab

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 unknown or where sample sizes are small. Their...


Platforms: Matlab

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 unknown or where sample sizes are small. Their...


Platforms: Matlab

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 unknown or where sample sizes are small. Their...


Platforms: Matlab

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


Platforms: Matlab

Use this code to simulate basic microstructure evolution. This is quite an old code. Will post the updated code in 2D and 3D shortly. This version uses wrap boundary condition and the computation is a bit slower as against the new code. However, I am making some changes to the newer versions. So,...


Platforms: Matlab