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Über das Produkt
An accessible guide to one of the fastest growing areas in financial analysis by one of Europes's leading teaching and researching teams, first published in 2000. This classroom-tested advanced undergraduate and graduate textbook provides an in-depth treatment of non-linear models, including regime-switching and artificial neural networks.
Kurzbeschreibung
Although many of the models commonly used in empirical finance are linear, the nature of financial data suggests that non-linear models are more appropriate for forecasting and accurately describing returns and volatility. The enormous number of non-linear time series models appropriate for modeling and forecasting economic time series models makes choosing the best model for a particular application daunting. This classroom-tested advanced undergraduate and graduate textbook, first published in 2000, provides a rigorous treatment of recently developed non-linear models, including regime-switching and artificial neural networks. The focus is on the potential applicability for describing and forecasting financial asset returns and their associated volatility. The models are analysed in detail and are not treated as 'black boxes'. Illustrated using a wide range of financial data, drawn from sources including the financial markets of Tokyo, London and Frankfurt.
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Einleitungssatz
In this chapter we discuss several concepts that are useful for the analysis of time series with linear models, while some of them can also fruitfully be applied to nonlinear time series. Lesen Sie die erste Seite
Buchdeckel | Copyright | Inhaltsverzeichnis | Auszug | Stichwortverzeichnis | Rückseite
In this chapter we discuss several concepts that are useful for the analysis of time series with linear models, while some of them can also fruitfully be applied to nonlinear time series. Lesen Sie die erste Seite
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7 Rezensionen
38 von 38 Kunden fanden die folgende Rezension hilfreich
An excellent, up-to-date guide of finance non-linear models
22. August 2001
Format:Taschenbuch
If you are interested in what's up nowadays in the finance modeling, you should have this book. It's a review of some of the more recent, important and promising works of the field. Advanced undergraduate students and graduate students will probably understand the book (although I recommend it mostly for people interested in the field). If you want an easy introduction of most of the topics (but pretty older), then, grab Walter Enders book or, the more complicated, but also more complete book of James D. Hamilton. Reading this manual is easy because it's clear and its style is not boring. If you really love finance econometrics, you'll find this book fun to read. The fields covered by the authors are: 1.-Linear models (pretty brief), unit roots, seasonality and aberrant observations; 2.-Regime-switching models for returns such as TAR (Threshold Autoregressive), SETAR,...; 3.-Regime switching models for volatility (and here you'll have the entire family of ARCH models, with its youngest cousins such as GARCH QGARCH, LSTGARCH, VS-GARCH); 4.-Artificial Neural Network for returns. I'm particularly interested in GARCH-type models, and I can tell this part is particularly well done. At the end of the chapter there is a very illuminating empirical comparison between the models. I cannot say if the "artificial neural networks" is a good chapter since I'm not an expert, but the least I can say is that it's pretty understandable (although quite challenging for an ignorant like myself).
31 von 32 Kunden fanden die folgende Rezension hilfreich
A timely survey on an important area
10. Januar 2001
Format:Gebundene Ausgabe|Von Amazon bestätigter Kauf
The title of this book caught my attention immediately and it actually contains more interesting topics than I thought. After I bought a copy through Amazon and have a closer read, I'm not disapointed by the two authors' writing, which is probably partially based on the second author's PhD dissertation, and so it is a little narrow-focused. But as the authors stated, they want to produce a book which deals with nonlinear techniques as opposed to Mills's mostly linear methods in fiance time series. They have delivered. With hot topics such as regime switching, ARCH models, and neural network applications in finance, I'm sure this book will find a lot of interested readers and will be a key reference in nonlinear empirical finance.
23 von 23 Kunden fanden die folgende Rezension hilfreich
nice coverage of time series methods applicable to finance
7. Februar 2008
Format:Taschenbuch
Like his other books, Franses provides an nice applied treatment of non-linear time series models that are in this case applicable to finance. It includes extensive coverage of regime switching models. It includes data drawn from several financial markets including Tokyo, London and Frankfurt.
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