This is the most up-to-date and accessible guide to one of the fastest growing areas in financial analysis by two of the most accomplished young econometricians in Europe. This classroom-tested advanced undergraduate and graduate textbook provides an in-depth treatment of recently developed nonlinear models, including regime-switching and artificial neural networks, and applies them to describing and forecasting financial asset returns and volatility. It uses a wide range of financial data, drawn from sources including the markets of Tokyo, London and Frankfurt.
Author(s): Philip Hans Franses, Dick van Dijk
Edition: 1
Publisher: Cambridge University Press
Year: 2000
Language: English
Pages: 297
Table of Contents......Page 8
List of figures......Page 10
List of tables......Page 12
Preface......Page 16
1.1 Introduction and outline of the book......Page 18
1.2 Typical features of financial time series......Page 22
2.1 Preliminaries......Page 37
2.2 Empirical specification strategy......Page 44
2.3 Forecasting returns with linear models......Page 61
2.4 Unit roots and seasonality......Page 68
2.5 Aberrant observations......Page 78
3 Regime-switching models for returns......Page 86
3.1 Representation......Page 88
3.2 Estimation......Page 100
3.3 Testing for regime-switching nonlinearity......Page 117
3.4 Diagnostic checking......Page 125
3.5 Forecasting......Page 134
3.6 Impulse response functions......Page 142
3.7 On multivariate regime-switching models......Page 149
4 Regime-switching models for volatility......Page 152
4.1 Representation......Page 153
4.2 Testing for GARCH......Page 174
4.3 Estimation......Page 187
4.4 Diagnostic checking......Page 199
4.5 Forecasting......Page 204
4.6 Impulse response functions......Page 214
4.7 On multivariate GARCH models......Page 217
5 Artificial neural networks for returns......Page 223
5.1 Representation......Page 224
5.2 Estimation......Page 232
5.3 Model evaluation and model selection......Page 239
5.4 Forecasting......Page 251
5.5 ANNs and other regime-switching models......Page 254
5.6 Testing for nonlinearity using ANNs......Page 262
6 Conclusions......Page 268
Bibliography......Page 271
D......Page 289
J......Page 290
P......Page 291
W......Page 292
Z......Page 293
C......Page 294
M......Page 295
U......Page 296
W......Page 297
