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Matlab-GUI equity derivative calculator

MathWorks Webinar: Using Genetic Algorithms in Financial Applications

This zip file contains the Presentation (PDF) and M-files that were demonstrated in the MathWorks Webinar: Using Genetic Algorithms in Financial Applications delivered on Dec 11 2007.

The purpose of the webinar was to highlight how Genetic Algorithms may be used to supplement portfolio optimization problems. The Genetic Algorithm contains custom evolution algorithms that were built specifically for this webinar. They allow the user to explore subsets of fixed size from a larger universe of stocks to search for a minimum variance portfolio with a given return. This is related to what is known as portfolio “cardinality constraints” or “mean variance spanning”. This will also be useful for anyone interested in solving mixed integer proglems in MATLAB.

Please see the included ReadMe.doc for a description of the contents.

Visualize dynamic hedging

Function HEDGEDEMO aims to help students and instructors of finance visualize trading demands of simple static or dynamic value-hedging strategies. In a single-factor setting, 2-asset hedge portfolios are constructed to match, at a point in time, value and delta of the hedged portfolio, consisting of 1-2 assets, one unit of each. (Delta is estimated by shifting the factor path by +/- 0.01). Factor dynamics are described by a Matlab expression or function that defines vector ‘X’ in terms of vector ‘T’, where T = StartDate:EndDate. With ‘X’ defined and evaluated, paths of asset prices are similarly given by Matlab expressions or functions inputting ‘X’ and ‘T’.

Asian Option – Pricing using Monte Carlo Control Variate Method

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

Simple option pricing GUI

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, Butterfly

It plots the pricing surface for the appropriate option and then runs a number of Monte Carlo simulations (daily granularity) for that given set of parameters. It provides some useful information on the Monte Carlo simulation in graphical form.

Algorithmic Trading with MATLAB

These are the files and some of the data that I used in my recent webinar on Algorithmic Trading. Data has been shortened for size reasons. Included are:

MARISA

Nearest Neighbour model

Trailing stop-loss code

an illustration of Takens Theorem

Pricing Derivatives Securities using MATLAB

Algorithmic Trading with MATLAB

Files used in the webinar – Algorithmic Trading with MATLAB Products for Financial Applications broadcast on November 18, 2010. This webinar can be viewed at http://www.mathworks.com/wbnr52491.

The download includes an additional demo, not shown in the webinar, that shows how to generate C-code from MATLAB.

Statistical Backtest Toolbox

Black and Shcoles calculator

Graphical Black and Shcoles calculator for visualizing different sensetives of vanila call and put options, stradle and butterfly as a function of underlying price and time to maturity

Shows the following sensetives:

Price of call, put, stradle and butterfly

Delta of call, put, stradle and butterfly

Gamma of call, put, stradle and butterfly

Vega of call, put, stradle and butterfly

Theta of call, put, stradle and butterfly

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