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ORCIDNeural Networks and the Financial Markets, 2002
- Jimmy Shadbolt, John G. Taylor:
Neural Networks and the Financial Markets - Predicting, Combining and Portfolio Optimisation. Perspectives in Neural Computing, Springer 2002, ISBN 978-1-85233-531-1 - John G. Taylor:
Introduction to the Financial Markets. 3-9 - John G. Taylor:
Univariate and Multivariate Time Series Predictions. 11-22 - Neville Towers:
Evidence of Predictability in Financial Markets. 23-33 - Sebastian Larsson:
Bond Pricing and the Yield Curve. 35-40 - Jimmy Shadbolt:
Data Selection. 41-45 - John G. Taylor:
General Form of Models of Financial Markets. 49-53 - Jimmy Shadbolt:
Overfitting, Generalisation and Regularisation. 55-59 - Jimmy Shadbolt:
The Bootstrap, Bagging and Ensembles. 61-67 - Neville Towers:
Linear Models. 69-76 - Jimmy Shadbolt, John G. Taylor:
Input Selection. 77-83 - John G. Taylor:
Neural Networks. 87-93 - Neville Towers, A. Neil Burgess:
Learning Trading Strategies for Imperfect Markets. 95-108 - Neep Hazarika:
Dynamical Systems Perspective and Embedding. 109-115 - Neep Hazarika, John G. Taylor:
Vector Machines. 117-121 - Sebastian Larsson:
Bayesian Methods and Evidence. 123-130 - Sebastian Larsson:
Yield Curve Modelling. 133-143 - Neep Hazarika, John G. Taylor:
Predicting Bonds Using the Linear Relevance Vector Machine. 145-155 - David Attew:
Artificial Neural Network. 157-166 - Jimmy Shadbolt:
Adaptive Lag Networks. 167-174 - Sebastian Larsson:
Network Integration. 175-179 - A. Neil Burgess:
Cointegration. 181-191 - Neville Towers:
Joint Optimisation in Statistical Arbitrage Trading. 193-201 - Neep Hazarika:
Univariate Modelling. 203-210 - Neep Hazarika, John G. Taylor:
Combining Models. 211-217 - Christopher J. Adcock:
Portfolio Optimisation. 221-246 - John G. Taylor:
Multi-Agent Modelling. 247-252 - John G. Taylor:
Financial Prediction Modelling: Summary and Future Avenues. 253-258
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