Intelligent Trading Systems

Jacket text for Intelligent Trading Systems

This book deals with the issue of problematic market price prediction in the context of crowd behaviour affected by the psychology of the masses. It highlights the contrast between a phenomenon of mass psychology and the efficient market hypothesis, which is essentially based on a common economic theory. The basic assumption is that if there is a model of interaction between masses and agents participating in markets, then there also exist means for prediction of the whole market's behaviour, though nevertheless the behaviour of every single agent is not predictable.

From a practical point of view, this book describes technical analysis methods used to predict price movements, and discusses a soft computing approach used in a composition of automated trading systems. This book brings alternative, soft computing computational models to trading strategies and innovatively combines two different areas of science - artificial intelligence and technical analysis. One of the main benefits of this book is a demonstration that the soft computing approach in a combination with the "soft" social sciences accounts more reliable results than the conventional mathematical models.

This book is for anyone interested in trading, financial markets and security exchanges, as well as for those who have theoretical or practical knowledge from the fields of artificial intelligence and soft computing, and want to know how these topics can be applied in financial markets.

Chapter headings for Intelligent Trading Systems

Introduction

Chapter 1: Reality, the intersection of multiple theories
Efficient market hypothesis
The theory of chaos
Behavioral market theory

Chapter 2: The dynamics of crowd behavior
Methodologies for the study of markets
The system theory point of view
The wave principle
Fibonacci mathematics in financial markets

Chapter 3: Security exchanges at a glance
Financial markets
Security exchanges
Exchange clearing systems

Chapter 4: Basic tenets of automated trading
Indicators and oscillators
Money management
Statistics
The sensitivity to changes of system parameters

Chapter 5: Simulation and backtesting of trading strategies
The value of simulation in the trading
Human factor in the trading chain
Modeling of order execution
Modeling of time and price skews
Discrete Event System Specification
Simulation of the trading environment
Embedding trading strategies into the simulation
Simulation case study

Chapter 6: Optimization of trading strategies
Parametric trading strategies
Genetic algorithms
Inspiration from nature
Computational model of genetic evolution
Optimization case study

Chapter 7: Fuzzy approach to trading strategies
Concept of uncertainty and the basics of fuzzy logic theory
Fuzzy logic and fuzzy inference
Fuzzy-based trading strategies
Analysis of sensitivity and robustness
Case study

Summary
Bibliography and further reading
Notations, functions and mathematical symbols

About Ondrej Martinsky

Ondrej Martinsky specialises in mathematics and computer science, intelligent and decision support systems. He has been working on several research projects within these areas during his recent stay at Brno University of Technology. Ondrej is also the author of several scientific papers which have been presented at international conferences. Ondrej also studies economics, financial markets and security exchanges, and in particular technical analysis of market prices in combination with the short-term trading of financial derivatives. Alongside conventional trading he is also interested in the scientific approach, wondering not only how markets move, but also why they move as they do. During the last few years, he has been investigating how advanced computational methods can be applied in financial markets. In his book, "Intelligent Trading Systems", he provides the results of this research and a unique interconnection of knowledge from the fields of computer science and financial markets.

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