This book looks at how research into predicting the financial markets has progressed in recent years. The first section of the book describes the financial markets and asks whether they are indeed predictable, given the number of possible economic and financial variables. The second section surveys existing prediction models and looks at how these can be refined so as to provide the best prediction of the market's value at the next time step i.e. in one month's time. The third and forth sections look at the theory of specific prediction models and their applications, whilst the final section discusses possible future developments i.e. so that prediction models can be made more immune to sudden global changes.

Klappentext

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Inhalt

I Introduction to Prediction in the Financial Markets.- 1 Introduction to the Financial Markets.- 2 Univariate and Multivariate Time Series Predictions.- 3 Evidence of Predictability in Financial Markets.- 4 Bond Pricing and the Yield Curve.- 5 Data Selection.- II Theory of Prediction Modelling.- 6 General Form of Models of Financial Markets.- 7 Overfitting, Generalisation and Regularisation.- 8 The Bootstrap, Bagging and Ensembles.- 9 Linear Models.- 10 Input Selection.- III Theory of Specific Prediction Models.- 11 Neural Networks.- 12 Learning Trading Strategies for Imperfect Markets.- 13 Dynamical Systems Perspective and Embedding.- 14 Vector Machines.- 15 Bayesian Methods and Evidence.- IV Prediction Model Applications.- 16 Yield Curve Modelling.- 17 Predicting Bonds Using the Linear Relevance Vector Machine.- 18 Artificial Neural Networks.- 19 Adaptive Lag Networks.- 20 Network Integration.- 21 Cointegration.- 22 Joint Optimisation in Statistical Arbitrage Trading.- 23 Univariate Modelling.- 24 Combining Models.- V Optimising and Beyond.- 25 Portfolio Optimisation.- 26 Multi-Agent Modelling.- 27 Financial Prediction Modelling: Summary and Future Avenues.- Further Reading.- References.