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 Vegas Monte Carlo Matlab 

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Numerical integration with Monte Carlo method (on FPGA chip).

Requirements:

- Matlab/Simulink
- Diamond IDE (3L)
- FPGA Xilinx VIrtex II (SMT8036E) http://www.sundance.com/web/files/static.asp?pagename=uni_offer_1)
- Visual Studio (Optional)
- Xilinx System Generator (Recommended)
- Xilinx ISE (Recommended)



An example to price an Arithmetic Average fixed strike Call option in the Black-Scholes framework using Monte Carlo Control Variate



This set of files show some of the principles of Monte Carlo simulations, applied in the financial industry. this is the content of the web seminar called "Simulations de Monte Carlo en MATLAB".

The slides are in French and a...



I saw something like this in C++ as an introduction to Monte Carlo, so I decided to make something similar in Python. My original code used for loops, but I vectorized it with no small amount of effort, and it now runs orders of magnitude faster....



This practical function provides a tool for quickly including a random process within a Monte Carlo Simulation framework.

The main input argument, is a string containing commands in Matlab syntax. Each execution of such string is an...



Monte Carlo methods have long been used in computational finance to solve problems where analytical solutions are not feasible or are difficult to formulate. However, these methods are computationally intensive making it challenging to implement...



Numerical Integration using Monte Carlo method.



Calculating area under the curve using Monte Carlo method
for any given function.



Calculating PI using random numbers (Monte Carlo method)



Function for pricing basket option using Monte Carlo Simulation. You can specify if you want an American option. For American options, it follows LMS algorithm. You can choose to specify Averaging date, Average Price, Average type etc.



To calculate an area S(A) of a figure A, bounded by a Jordan curve (which in our case is constructed by a cubic spline
approximation) the Monte Carlo method is applied



This simple code shows how the Monte Carlo Chronological method works. This example is intended to be for educational purpose, generating an artificial history data vectors of a single component modeled in a two state Markov chain model and...



This code implements a Markov chain Monte Carlo algorithm which automatically and efficiently tunes the proposal distribution to the covariance structure of the target distribution. This is achieved while maintaining the target distribution as the...



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.



The MATLAB program simulates binary frequency shift keying (BFSK) at baseband through Monte Carlo method. The goal is to simulate bit error rate (BER) over an additive white Gaussian noise (AWGN) channel. For realizing that, the effect of noise is...



The MATLAB program simulates binary phase shift keying (BPSK) at baseband through Monte Carlo method. The goal is to simulate bit error rate (BER) over an additive white Gaussian noise (AWGN) channel. For realizing that, the effect of noise is...



This program performs a Monte Carlo simulation of a coherent QPSK communication system and plot the error probability performance over additive whit Gaussian noise channel. The detection is based on correlation metric. Simulation is performed for...



The solution of the nearest correlation matrix applies the hypershpere or spectral decomposition methods as outlined in Monte Carlo methods in Finance by Peter Jackel, Chapter 6.

Use CorrelationExample.m that applies a simple example...



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 programs discretizes the CEV (constant elasticity of volatilty process and uses the process to price an option using Monte
Carlo methods.