Tools of the trade

In order to analyze the financial data many commercial tools exist, that of course cost a lot of money. On the other hand there exists free software, or open source as it is often called, that can be downloaded for free and used without any fee. You would expect that this software is missing something but no; in the right hands it can become really powerful. To take a taste what you can find out there* I'll summarize here the major tools I am using:

• octave: for general purpose numerical computations (an alternative is scilab)
• R: for statistics specific calculations, includes clustering, machine learning, among the others
• python: a powerful programming language that can be combined with many mathematical packages
• perl: another programming language better suited for text processing (you don't want to do all the work by hand, right?)
• maxima: symbolic mathematics software can be handy if the calculations become tough
• ruby: this programming language is not really needed, but gives a fresh way of thinking
• inkscape: a vector graphics tool for drawing flow diagrams (an alternative is dia)

All these programs can be downloaded from the links above for any platform, windows, mac os x, or linux.

You might be thinking "but I do not know all these stuff"; that's the purpose of this blog: to teach you something different.

*with out there I mean the internet.

Chaos economics?

What is meant by chaos economics? In most economics schools the economics that are taught are standard and classic. The mathematics involved are kept to the minimum in order to be everything well understood, and all problems to be solvable. However, in real life is not like this; this, at least, has shown many economical crisis over the last two centuries. So, we need something different?

One important part of modern economics is time series forecasting. The aim of time series forecasting is to predict how a given variable will evolve in the future knowing its past behavior. Time series forecasting was a hot subject of discussion from the beginnings of the human civilization, see fortune-telling, astrology, hand-reading, etc. Humans wanted and still want to know the future in advance.

The situation today has not changed a lot. There aren't any wizards, but there are still published thousands of papers and books about time series forecasting. Many software have been also designed to solve such hard problems. Techniques vary from statistical methods, to optimal control, to neural networks and many more.

The purpose of this blog is to present uncommon techniques that can be implemented with open source software. This means that 0€ must be paid in order to apply these methods, since all the software is freely downloadable from the internet. Some of the software I am going to use includes octave (or scilab), R, python, and others. All these programs will be used to study and forecast time series from stock markets and weather (cliche?), to client orders, or even number of blog followers.

However, there is a warning. All these stuff wont predict the future for you. There is no crystal ball. The methods and techniques presented here are just to show you alternative ways of analysing your data.

But why chaos? Well, chaos theory, including also bifurcation theory and some of singularity theory, is something different. It deals with the non-linear character of the phenomena and how they behave at singularities.

Have fun!

Dimitris