A new version of the numerical computation software Octave has been released.
In a previous blog we showed how to visualise stock prices for Deutsch Bank using core graphics functionalities of Octave. In this blog we will take a look at some finance-specific plot types available in the Financial Package on Octave Forge. This blog will show how to fetch some price data for Apple and use the data to make a:
First we will consider snippets of code to download data and create each type of plot. In the appendix a complete listing of code is given so you can easily reproduce the results on your own machine.
In this blog we want to demonstrate the power of Octave for doing simulations. Specifically we will take a look at the Black Scholes formula and how fast an option price computed using Monte Carlo simulation will converge to the actual value using the closed-form solution. The idea is to demonstrate how Octave can be used for this kind of simulations. In a previous blog we showed how to created plots, so here will will focus on the simulation only. The mantra when using Octave is "use vectors and matrices". If you can pull that off, your code will be efficient. On the other hand if you need to resort to for-loops, that will slow things down significantly.
In this blog the basics of generating and saving plots to file using Octave will be demonstrated. We are going to make plots and do some basic data analysis on the Deutsche Bank stock prices. Deutsche has been under pressure these last days, which rose our curiosity.
Deutsche Bank shares collapsed by nearly 7% taking it close to a 30-year low on Thursday evening following reports that hedge funds were pulling assets from it amid suggestions the German government may be forced to bail it out.
Deutsche Bank's share price approaches 30-year low -The Guardian
We are looking at Octave as an alternative or extension to Matlab. Octave has the major advantage of being open source allowing you to share your code with ease and no additional cost. Anybody interested in your code can simply download and install Octave and start executing and editing the code. Matlab code can also be shared, but a license fee is charged for each Matlab installation. Depending on your target audience this might significantly reduce your reach.
For those of you unfamiliar with Octave:
GNU Octave is a high-level interpreted language, primarily intended for numerical computations. It provides capabilities for the numerical solution of linear and nonlinear problems, and for performing other numerical experiments. It also provides extensive graphics capabilities for data visualization and manipulation. Octave is normally used through its interactive command line interface, but it can also be used to write non-interactive programs. The Octave language is quite similar to Matlab so that most programs are easily portable.
We will be blogging about experiences to help others in their considerations of Octave and in the hope to gather feedback from the financial engineering community.