Financial markets are incredible systems. Thousands of instruments are traded by millions of participants every day, around the world, in a never ending battle to make money. Is it possible to capture the workings of the markets in a mathematical model, and possible to find neglected areas of the markets where a careful application of statistics.

This study is an attempt to apply a new nonlinear statistical modeling technique, Radial Basis Functions, to the rather bold task of stock market prediction and analysis. The success of our approach will ultimately depend on whether or not there are significant nonlinear relationships in the markets that can be discovered empirically.

Certainly numbers and quantitative analysis are invaluable for the accounting side of the financial markets, to “keep score” of how participants are doing. But in the last 30 years the financial world has embraced a decidedly quantitative orientation for many parts of the decision making processes as well, widely adopting quantitative theories such as modern portfolio theory, the Capital Asset Pricing Model, and option pricing theory.

Read More

Artificial Neural Networks adalah sebuah sistem yang berisi beberapa elemen (neuron) yang bertugas menjalankan suatu proses sederhana, yang saling dihubungkan sehingga membentuk suatu jaringan (Fausett, 1994).

Sebenarnya model ini sangat mirip dengan model regressi biasa namun dengan proses yang tidak dapat di capture atau orang lain bisa menyebutnya dengan “black box” . Jaringan syaraf tiruan secara matematis, yang hasilnya yaitu sebagai berikut:

Read More