Jerzy J. Korczak

Evolution Strategy in Portfolio Optimization

In this paper an evolutionary algorithm to optimize a stock portfolio is presented. The method, based on Evolution Strategies, uses artificial trading experts discovered by a genetic algorithm. This approach is tested on a sample of stocks taken from the French market. Results obtained are compared with the Buy-and-Hold strategy and a stock index. Presented research extends evolutionary methods on financial economics worked out earlier for stock trading.

Evolutionary building of stock trading experts in a real-time system

This paper addresses the problem of constructing real-time stock trading expertise for financial time series. The expertise is arrived at via an evolutionary algorithm on the basis of a set of specified trading rules. As in most real-time expert systems, one of the main bottlenecks is the time constraint. In this paper, two approaches were compared using our system, Bourse-Expert, the first based on 350 trading rules, and the second based on 150 particular linear combinations of these 350 rules. Experiments carried out on real data from the Paris Stock Exchange showed that focusing on only 150 rules highly reduced the computation time without significantly reducing the quality of the expertise.

Performance Measures in an Evolutionary Stock Trading Expert System

This paper addresses the problem of investment assessment and selection. A number of various performance measures are evaluated and studied. The goal of these investigations is to compare these performance measures on real-life data and to discover an optimal performance measure for selecting investment strategies in an evolutionary stock trading decision support system. Evaluations have been performed on financial time series from the Paris Stock Exchange.

Neuronal clustering of brain fMRI images

Functional Magnetic Resonance Imaging (fMRI) allows the neuroscientists to observe the human brain in vivo. The current approach consists in statistically validating their hypotheses. Data mining techniques provide an opportunity to help them in making up their hypotheses. This paper shows how a neuronal clustering technique can highlight active areas thanks to an appropriate distance between fMRI image sequences. This approach has been integrated into an interactive environment for knowledge discovery in brain fMRI. Its results on a typical dataset validate the approach and open further developments in this direction.

Analysis and evaluation of learning classifier systems applied to hyperspectral image classification

In this article, two learning classifier systems based on evolutionary techniques are described to classify remote sensing images. Usually, these images contain voluminous, complex, and sometimes erroneous and noisy data. The first approach implements ICU, an evolutionary rule discovery system, generating simple and robust rules. The second approach applies the real-valued accuracy-based classification system XCSR. The two algorithms are detailed and validated on hyperspectral data.

Early warning in online stock trading systems

In this paper, a new functionality of early warning for an online stock trading system is presented. The warning functionality helps to focus traders attention on specific situations on the stock market. The specific situations relate to the rare circumstances where a trader should be alerted by exceptional raises or drops of share prices, volatilities and market index changes. Usually, these alerts force a trader to make a decision either to buy or sell a share. To discover the warning rules and events, an evolution-based model is proposed. This model also introduces a new function that stores the experimental knowledge by keeping track of all historical alert events-solutions and actions taken by a trader. This model is composed of the three following components, which are integrated with each other: alert rules, pattern clustering and genetic engine. This approach has been tested on real data extracted from the Internet Bourse Expert System and Paris Stock Exchange.