Historical and recent developments at international ?nancial markets
show that it is easy to loose money, while it is dif?cult to predict
future developments and op- mize decision-making towards maximizing
returns and minimizing risk. One of the reasons of our inability to make
reliable predictions and to make optimal decisions is the growing
complexity of the global economy. This is especially true for the f-
eign exchange market (FX market) which is considered as one of the
largest and most liquid ?nancial markets. Its grade of ef?ciencyand its
complexityis one of the starting points of this volume. From the high
complexity of the FX market, Christian Ullrich deduces the - cessity to
use tools from machine learning and arti?cial intelligence, e.g.,
support vector machines, and to combine such methods with sophisticated
?nancial mod- ing techniques. The suitability of this combination of
ideas is demonstrated by an empirical study and by simulation. I am
pleased to introduce this book to its - dience, hoping that it will
provide the reader with interesting ideas to support the understanding
of FX markets and to help to improve risk management in dif?cult times.
Moreover, I hope that its publication will stimulate further research to
contribute to the solution of the many open questions in this area.