A second application of NN

The HR-2 robot was constructed during a period of three months at Chalmers University in Sweden. It has 22 degrees of freedom which enables it to easily move around imitating human motions. The robot is also equipped with stereovision giving it possibilities to perform hand-eye coordination. For that task an artificial neural network is evolved. Furthermore, the artificial brain is capable of tracking faces as well as recognising them. The HR-2 is also able to speak.

A non financial application of NN

This simulated car is controlled by a neural network that has been trained by evolutionary algorithms (aka genetic algorithms). Its input are several rangefinder sensors, and outputs are speed and steering commands. No human knowledge has gone into designing the driving behaviour.

John Kenneth Galbraith died

"John Kenneth Galbraith, the iconoclastic economist, teacher and diplomat and an unapologetically liberal member of the political and academic establishment that he needled in prolific writings for more than half a century, died yesterday at a hospital in Cambridge, Mass. He was 97.

Galbraith lived in Cambridge and at an "unfarmed farm" near Newfane, Vt. His death was confirmed by his son J. Alan Galbraith.

Galbraith was one of the most widely read authors in the history of economics; among his 33 books was "The Affluent Society" (1958), one of those rare works that forces a nation to re-examine its values. He wrote fluidly, even on complex topics, and many of his compelling phrases - among them "the affluent society," "conventional wisdom" and "countervailing power" - became part of the language. An imposing presence, lanky and angular at 6 feet 8 inches tall, Galbraith was consulted frequently by national leaders, and he gave advice freely, though it may have been ignored as often as it was taken. Galbraith clearly preferred taking issue with the conventional wisdom he distrusted".
(source)

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ANN and ARIMA article summary

I would like to draw your attention to a paper published on the ASOR Bulletin in 2003. It's titled "comparing ANN Based Models with ARIMA for Prediction of Forex Rates". It's an interesting paper written in plain language. Let me give you a summary of the main ideas:
- the ANN models used (including SB, SCG and BR)all outperformed the ARIMA models (Box-Jenkins);
- the analysis was about the forex market, six currency pairs in total;
- "ANN proved to be very effective in describing the dynamics of non-stationary time series due to its unique non-parametric, non-assumable, noise-tolerant, and adaptive approximators that can map any nonlinear function without a priori assumptions about the data";
- details about ARIMA are available in Jarret "Business Forecasting Methods";
- the idea of NN is explained;
- multilayer feedforward network (MFN) is described briefly;
- no study has been reported to analytically determine the generalization performance of each algorithm;
- the author uses MA5, MA10, MA20, MA60, MA120 (Moving averages of given lengths);
- the NN used had 6 inputs, 1 layer and one output;
- the statistical metrics used to evaluate the performance are: Mean Square Error, Mean Absolute Error, Directional Symmetry;
- neural networks models produce much better performance than the conventional ARIMA models for both shorter and longer term forecasting;

A link

Good morning,

i would like to provide all of you who decided to join this attempt to understand NN with an interesting link. It's not directly connected with the subject of the blog, but it's rather interesting:
The pleasure of finding things out - RP Feynman --> link

Learning paradigms

we can distinguish three main learning paradigms:
- supervised learning
- nonsupervised learning
- reinforcement learning

Artificial intelligence vs. cognitive modelling

"Artificial intelligence and cognitive modeling try to simulate some properties of neural networks. While similar in their techniques, the former has the aim of solving particular tasks, while the latter aims to build mathematical models of biological neural systems.

In the artificial intelligence field, artificial neural networks have been applied successfully to speech recognition, image analysis and adaptive control, in order to construct software agents (in computer and video games) or autonomous robots. Most of the currently employed artificial neural networks for artificial intelligence are based on statistical estimation, optimisation and control theory.

The cognitive modelling field is the physical or mathematical modelling of the behaviour of neural systems; ranging from the individual neural level (e.g. modelling the spike response curves of neurons to a stimulus), through the neural cluster level (e.g. modelling the release and effects of dopamine in the basal ganglia) to the complete organism (e.g. behavioural modelling of the organism's response to stimuli)".
(source)

NN definition

Let's start by some basic issues... let's define neural networks:

" A neural network is an interconnected group of biological neurons. In modern usage the term can also refer to artificial neural networks, which are constituted of artificial neurons. Thus the term 'Neural Network' specifies two distinct concepts:

1. A biological neural network is a plexus of connected or functionally related neurons in the peripheral nervous system or the central nervous system. In the field of neuroscience, it most often refers to a group of neurons from a nervous system that are suited for laboratory analysis.
2. Artificial neural networks were designed to model some properties of biological neural networks, though most of the applications are of technical nature as opposed to cognitive models."

(source: http://en.wikipedia.org/wiki/Neural_networks ).

Introduction to the blog

Welcome!

This is a blog that will allow me to introduce the idea of NN and their application for financial markets... this mix will represent a mix of theory, empirical findings, forecasts and opionions... it will cover the topic from a newbie to a professional level... you are welcome to add comments and write anything you want on the topic...