Software Downloads for "Gavazzi Carlo"

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 copy in English is also available You will find here : * how to code your own monte carlo simulation, for option pricing * a comparison of some of the Variance Reduction Technics * Benfeits of using MATLAB for MonteCarlo simulation.

  • Platform: Matlab, Scripts
  • Publisher: Vincent Leclercq
  • Date: 17-03-2013
  • Size: 399 KB

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).

  • Platform: Matlab, Scripts
  • Publisher: Francesco Pizzo
  • Date: 22-01-2013
  • Size: 21064 KB

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

  • Platform: Matlab, Scripts
  • Publisher: Sudhanshu Chadha
  • Date: 21-01-2013
  • Size: 10 KB

Monte Carlo eXtreme, otherwise kown as MCX, is a Monte Carlo simulation tool for time-resolved photon transport in 3D turbid media.

It uses Graphics Processing Units (GPU) based massively parallel computing techniques and is extremely fast compared to the traditional single-threaded CPU-based simulations.

Using an nVIDIA 8800GT graphics card (14MP/114Cores), the acceleration is about 300x~400x compared to tMCimg running on a single core of Xeon 5120 CPU; this ratio can be as high as 700x with a GTX 280 GPU and 1400x with a GTX 470.

Monte Carlo analysis is an enhancement to CPM and PERT methods built into MS Project. It enables project manager to run statistical simulation of possible project outcomes based on optimistic, pessimistic and most likely estimates..

  • Platform: Windows
  • Publisher: sasoskrlj
  • Date:
  • Size: 163 KB

RiskAMP is a full-featured Monte Carlo Simulation Engine for Microsoft Excel. With the RiskAMP Add-in, you can add Probability Simulation to your spreadsheet models or develop complex Monte Carlo simulation applications - quickly, easily, and for a fraction of the price of competing packages.The RiskAMP Add-in has everything you need to build complex Financial, Cost Planning, or Project Management spreadsheets, using a library of random probability and statistical analysis functions.The PERT distribution for cost and project modeling An easy-to-use wizard for creating tables and charts21 random distributions, including correlated multivariate normal 18 statistical analysis functions Comprehensive VBA integration.

  • Platform: Windows
  • Publisher: riskamp.com
  • Date: 14-10-2009
  • Size: 520 KB

When planning and saving for retirement, investors are confronted with a variety of investment choices, ranging from the very safe to very aggressive. There are 100s of Monte Carlo simulators and calculators to assist retirees in projecting a so-called "safe withdrawal rate" (SWR) from their volatile, equity-based portfolios that would minimize the risk of outliving their savings. But these tools do not compare those SWR projections with the safest -- and potentially less frugal -- alternative: funding one's retirement years with a portfolio of laddered Treasury Inflation Protected Securities ("TIPS"), fortified by a longevity annuity.

A Monte Carlo simulation of Major League Baseball(TM), used to find the best strategies in a baseball game. The effect of different batting orders and the addition of one super-star can be tested and archived in retrosheet format..

MCX is a Monte Carlo simulation software for static or time-resolved photon transport in 3D media. It uses GPU-based massively parallel computing techniques and is extremely fast compared to the traditional single-threaded CPU-based simulations..

MCMLL is a C++ template library (header files only! : ) ) for machine learning with an emphasis on Monte-Carlo methods. It includes a large number of different (multi-threaded) Evolutionary Algorithms, Particle Filtering framework....

MCS is a tool that exploits the Monte Carlo method and, with a complex algorithm based on the PERT (Program Evaluation and Review Technique), it estimates a project's time. MCS is a opensource project and it was devolped by Java Programming Language..

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 10,000 bits and measurements are made accordingly..

  • Platform: Matlab, Scripts
  • Publisher: Sanjeet Kumar
  • Date: 01-04-2013
  • Size: 10 KB

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. asianbasket.m and europeanbasket.m are the files for pricing. basketset.m is the function to generate a structure which is used for pricing functions. testfile.m is an example. For LMS, it draws inspiration from the following page: http://leippold.googlepages.com/longstaffSchwartz2a.

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 for the two cases..

  • Platform: Matlab, Scripts
  • Publisher: Ahmos Sansom
  • Date: 08-03-2013
  • Size: 10 KB

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 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 instance of a random process. The function expressionMCS samples an opened number of user-specified variables and expressions, by running the input string for N iterations. The function help is documented with four meaningful examples of various uses. The purpose of this function is to perform simple Monte Carlo testings for any kind of stochastic processes, without having to create a single .

  • Platform: Matlab, Scripts
  • Publisher: Gianluca Dorini
  • Date: 06-03-2013
  • Size: 10 KB

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 exponentially distributed. You just need to enter the number of experiments to determine the simulation time-span (recommended to be above 1000 experiments)and the MTTF and MTTR of the repairable component. As there is no convergence criteria, it is recommended that you run the simulation many times with a large number of experiments and of course, the same reliability data of the component.

  • Platform: Matlab, Scripts
  • Publisher: Jorge Thomas
  • Date: 21-06-2013
  • Size: 10 KB

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 and adopt. In the last decade, advances in hardware, increasing processor speeds and decreasing costs have made it easier to adopt Monte Carlo methods to solve numerically intensive problems. With growing access to data and demand for quicker results, researchers are constantly looking for better ways to implement algorithms using Monte Carlo methods.

  • Platform: Matlab, Scripts
  • Publisher: Sri Krishnamurthy
  • Date: 14-06-2013
  • Size: 553 KB

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 stationary distribution of the Markov chain. The algorithm is described in: Cajo F.T. Ter Braak, "A Markov Chain Monte Carlo version of the genetic algorithm Differential Evolution: easy Bayesian computing for real parameter spaces", Stat Comput (2006) 16:239 249 As of the date of submission, this paper is freely available at: http://www.

  • Platform: Matlab, Scripts
  • Publisher: Corey Yanofsky
  • Date: 09-04-2013
  • Size: 10 KB

MiMMC (MultiModal Monte Carlo) is a research tool for Monte Carlo based radiotherapy planning and dosimetry.
MiMMC (MultiModal Monte Carlo) License - GNU General Public License (GPL).

  • Platform: WinOther
  • Publisher: Mimmc
  • Date:
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