Intelligent trading systems : applying artificial intelligence to financial markets
著者
書誌事項
Intelligent trading systems : applying artificial intelligence to financial markets
Harriman House, 2010
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注記
Includes bibliographical references (p. 195-197)
内容説明・目次
内容説明
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.
目次
Introduction 1: Reality, the intersection of multiple theories Efficient market hypothesis The theory of chaos Behavioral market theory 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 3: Security exchanges at a glance Financial markets Security exchanges Exchange clearing systems 4: Basic tenets of automated trading Indicators and oscillators Money management Statistics The sensitivity to changes of system parameters 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 6: Optimization of trading strategies Parametric trading strategies Genetic algorithms Inspiration from nature Computational model of genetic evolution Optimization case study 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
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