## Time Series Models: In econometrics, finance and other fieldsThe analysis prediction and interpolation of economic and other time series has a long history and many applications. Major new developments are taking place, driven partly by the need to analyze financial data. The five papers in this book describe those new developments from various viewpoints and are intended to be an introduction accessible to readers from a range of backgrounds. The book arises out of the second Seminaire European de Statistique (SEMSTAT) held in Oxford in December 1994. This brought together young statisticians from across Europe, and a series of introductory lectures were given on topics at the forefront of current research activity. The lectures form the basis for the five papers contained in the book. The papers by Shephard and Johansen deal respectively with time series models for volatility, i.e. variance heterogeneity, and with cointegration. Clements and Hendry analyze the nature of prediction errors. A complementary review paper by Laird gives a biometrical view of the analysis of short time series. Finally Astrup and Nielsen give a mathematical introduction to the study of option pricing. Whilst the book draws its primary motivation from financial series and from multivariate econometric modelling, the applications are potentially much broader. |

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### Contents

List of contributors xi | 9 |

Likelihoodbased inference for cointegration of some nonstationary | 69 |

Forecasting in macroeconomics | 101 |

Pricing by no arbitrage | 177 |

Acknowledgements | 223 |

### Other editions - View all

Time Series Models: In econometrics, finance and other fields D. R. Cox,D. V. Hinkley,O. E. Barndorff-Nielsen No preview available - 2013 |

### Common terms and phrases

allow analysis Applied approach approximation arbitrage ARCH models asset assumed assumption asymptotic autoregressive called changes cointegrating common complete conditional Consider consistent correction correlation corresponding covariance defined Definition denotes depend derivative determined differences discussion distribution Econometrics economic effects elements empirical Engle equation equivalent estimate example exists expectation forecast error function future GARCH Gaussian give given Hence Hendry implies important independent inference initial integrated interest Journal Journal of Econometrics levels likelihood linear martingale measure matrix mean measure methods missing multivariate normal observations option parameters positive possible predictable probability problem properties random rank regression relations requires restrictions sample simple specified squared standard stationary Statistics stochastic structure suggests SV models Table Theorem theory trading strategy University variables variance vector volatility zero

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