Diploma Thesis from the year 2007 in the subject Business economics -
Banking, Stock Exchanges, Insurance, Accounting, grade: 1,7, University
of Hamburg (Department Informatik), language: English, abstract: In this
thesis Genetic Programming is used to create trading systems for the
EUR/USD foreign exchange market using intraday data. In addition to the
exchange rates several moving averages are used as inputs. The developed
evolutionary algorithm extends the framework ECJ. The created trading
systems are being evaluated by a fitness function that consists of a
trading simulation. Genetic operators have been adapted to support "node
weights". By using these on the one hand macromutaion is tried to be
reduced on the other hand the interpretability of the created trading
systems is tried to be improved. Results of experiments show that
created trading systems are apparently successfull in profitably using
informations contained within the exchange rates. Profits of the created
trading systems are maximized by using the optimal position size. It is
shown that if the minimum investment period is met the achieved results
are optimal even when taking into account the used risk adjusted
performance figure.