Nonlinear time series models in empirical finance:
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...
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| 1. Verfasser: | |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2000
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| Schlagworte: | |
| Online-Zugang: | BSB01 FHN01 UBG01 Volltext |
| Zusammenfassung: | 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 |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 05 Oct 2015) |
| Beschreibung: | 1 online resource (xvi, 280 pages) |
| ISBN: | 9780511754067 |
| DOI: | 10.1017/CBO9780511754067 |
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| 520 | |a 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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Datensatz im Suchindex
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| author | Franses, Philip Hans 1963- |
| author_facet | Franses, Philip Hans 1963- |
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| author_sort | Franses, Philip Hans 1963- |
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| bvnumber | BV043923762 |
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| dewey-hundreds | 300 - Social sciences |
| dewey-ones | 332 - Financial economics |
| dewey-raw | 332/.01/5118 |
| dewey-search | 332/.01/5118 |
| dewey-sort | 3332 11 45118 |
| dewey-tens | 330 - Economics |
| discipline | Mathematik Wirtschaftswissenschaften |
| doi_str_mv | 10.1017/CBO9780511754067 |
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| indexdate | 2024-07-10T07:38:42Z |
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| isbn | 9780511754067 |
| language | English |
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| spelling | Franses, Philip Hans 1963- Verfasser aut Nonlinear time series models in empirical finance Philip Hans Franses, Dick van Dijk Cambridge Cambridge University Press 2000 1 online resource (xvi, 280 pages) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 05 Oct 2015) 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 Mathematisches Modell Finance / Mathematical models Time-series analysis Nichtlineare Zeitreihenanalyse (DE-588)4276267-4 gnd rswk-swf Mathematisches Modell (DE-588)4114528-8 gnd rswk-swf Finanzmathematik (DE-588)4017195-4 gnd rswk-swf Volatilität (DE-588)4268390-7 gnd rswk-swf Rentabilität (DE-588)4049495-0 gnd rswk-swf Kapitalanlage (DE-588)4073213-7 gnd rswk-swf Kapitalanlage (DE-588)4073213-7 s Rentabilität (DE-588)4049495-0 s Volatilität (DE-588)4268390-7 s Nichtlineare Zeitreihenanalyse (DE-588)4276267-4 s 1\p DE-604 Finanzmathematik (DE-588)4017195-4 s Mathematisches Modell (DE-588)4114528-8 s 2\p DE-604 Dijk, Dick van Sonstige oth Erscheint auch als Druckausgabe 978-0-521-77041-5 Erscheint auch als Druckausgabe 978-0-521-77965-4 https://doi.org/10.1017/CBO9780511754067 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Franses, Philip Hans 1963- Nonlinear time series models in empirical finance Mathematisches Modell Finance / Mathematical models Time-series analysis Nichtlineare Zeitreihenanalyse (DE-588)4276267-4 gnd Mathematisches Modell (DE-588)4114528-8 gnd Finanzmathematik (DE-588)4017195-4 gnd Volatilität (DE-588)4268390-7 gnd Rentabilität (DE-588)4049495-0 gnd Kapitalanlage (DE-588)4073213-7 gnd |
| subject_GND | (DE-588)4276267-4 (DE-588)4114528-8 (DE-588)4017195-4 (DE-588)4268390-7 (DE-588)4049495-0 (DE-588)4073213-7 |
| title | Nonlinear time series models in empirical finance |
| title_auth | Nonlinear time series models in empirical finance |
| title_exact_search | Nonlinear time series models in empirical finance |
| title_full | Nonlinear time series models in empirical finance Philip Hans Franses, Dick van Dijk |
| title_fullStr | Nonlinear time series models in empirical finance Philip Hans Franses, Dick van Dijk |
| title_full_unstemmed | Nonlinear time series models in empirical finance Philip Hans Franses, Dick van Dijk |
| title_short | Nonlinear time series models in empirical finance |
| title_sort | nonlinear time series models in empirical finance |
| topic | Mathematisches Modell Finance / Mathematical models Time-series analysis Nichtlineare Zeitreihenanalyse (DE-588)4276267-4 gnd Mathematisches Modell (DE-588)4114528-8 gnd Finanzmathematik (DE-588)4017195-4 gnd Volatilität (DE-588)4268390-7 gnd Rentabilität (DE-588)4049495-0 gnd Kapitalanlage (DE-588)4073213-7 gnd |
| topic_facet | Mathematisches Modell Finance / Mathematical models Time-series analysis Nichtlineare Zeitreihenanalyse Finanzmathematik Volatilität Rentabilität Kapitalanlage |
| url | https://doi.org/10.1017/CBO9780511754067 |
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