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Modeling Volatility in Financial Time Series: A comparison between GARCH and MSM volatility models - Softcover
Inhaltsangabe
Volatility is one of the biggest topics in finance today. It is the most important measure of risk and plays a crucial role in the valuation of derivatives. Volatility estimations are therefore essential in most financial decisions. However, it has been proven extremely difficult to model and forecast the volatility one witnesses in time series. This book compares two volatility models, their properties and their performances. The models compared are the GARCH model and the Markov Switching Multifractal model, two models that rely on completely different assumptions. This book assesses how both models perform in replicating financial time series. The model parameters are estimated on historical returns and option prices. The results are used to produce volatility forecasts which in their turn are evaluated in a Value at Risk setup. The analysis done shows some unexpected conclusions and promising leads for further research. This book provides a step by step manual on how to estimate various volatility models and how resulting estimates can be used for derivative pricing. This is extremely valuable for practitioners and others interested in modeling volatility in financial markets.
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Reseña del editor
Volatility is one of the biggest topics in finance today. It is the most important measure of risk and plays a crucial role in the valuation of derivatives. Volatility estimations are therefore essential in most financial decisions. However, it has been proven extremely difficult to model and forecast the volatility one witnesses in time series. This book compares two volatility models, their properties and their performances. The models compared are the GARCH model and the Markov Switching Multifractal model, two models that rely on completely different assumptions. This book assesses how both models perform in replicating financial time series. The model parameters are estimated on historical returns and option prices. The results are used to produce volatility forecasts which in their turn are evaluated in a Value at Risk setup. The analysis done shows some unexpected conclusions and promising leads for further research. This book provides a step by step manual on how to estimate various volatility models and how resulting estimates can be used for derivative pricing. This is extremely valuable for practitioners and others interested in modeling volatility in financial markets.
Biografía del autor
Jesper Roelof Boer, 28-03-1987. Studied: BSc and MSc Econometrics and Management Science; Quantitative Finance, at Erasmus University Rotterdam. MSc Research in Political Science, at Universidad Pompeu Fabra, Barcelona. Current positions: Associate professor, Research Assistant and PhD student in Political Sciences, at Universidad Pompeu Fabra.
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- VerlagLAP LAMBERT Academic Publishing
- Erscheinungsdatum2010
- ISBN 10 3843362068
- ISBN 13 9783843362061
- EinbandTapa blanda
- SpracheEnglisch
- Anzahl der Seiten88
- Kontakt zum HerstellerNicht verfügbar
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Modeling Volatility in Financial Time Series
Verlag:
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3843362068
ISBN 13: 9783843362061
Neu
Softcover
Anbieter: moluna, Greven, Deutschland
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Boer JesperJesper Roelof Boer, 28-03-1987. Studied: BSc and MSc Econometrics and Management Science Quantitative Finance, at Erasmus University Rotterdam. MSc Research in Political Science, at Universidad Pompeu Fabra, Barcelona. Cu. Bestandsnummer des Verkäufers 5466167
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Modeling Volatility in Financial Time Series
Verlag:
LAP LAMBERT Academic Publishing Okt 2010, 2010
ISBN 10: 3843362068
ISBN 13: 9783843362061
Neu
Taschenbuch
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Volatility is one of the biggest topics in finance today. It is the most important measure of risk and plays a crucial role in the valuation of derivatives. Volatility estimations are therefore essential in most financial decisions. However, it has been proven extremely difficult to model and forecast the volatility one witnesses in time series. This book compares two volatility models, their properties and their performances. The models compared are the GARCH model and the Markov Switching Multifractal model, two models that rely on completely different assumptions. This book assesses how both models perform in replicating financial time series. The model parameters are estimated on historical returns and option prices. The results are used to produce volatility forecasts which in their turn are evaluated in a Value at Risk setup. The analysis done shows some unexpected conclusions and promising leads for further research. This book provides a step by step manual on how to estimate various volatility models and how resulting estimates can be used for derivative pricing. This is extremely valuable for practitioners and others interested in modeling volatility in financial markets. 88 pp. Englisch. Bestandsnummer des Verkäufers 9783843362061
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Modeling Volatility in Financial Time Series : A comparison between GARCH and MSM volatility models
Verlag:
LAP LAMBERT Academic Publishing, 2010
ISBN 10: 3843362068
ISBN 13: 9783843362061
Neu
Taschenbuch
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Verkäuferbewertung 5 von 5 Sternen
Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Volatility is one of the biggest topics in finance today. It is the most important measure of risk and plays a crucial role in the valuation of derivatives. Volatility estimations are therefore essential in most financial decisions. However, it has been proven extremely difficult to model and forecast the volatility one witnesses in time series. This book compares two volatility models, their properties and their performances. The models compared are the GARCH model and the Markov Switching Multifractal model, two models that rely on completely different assumptions. This book assesses how both models perform in replicating financial time series. The model parameters are estimated on historical returns and option prices. The results are used to produce volatility forecasts which in their turn are evaluated in a Value at Risk setup. The analysis done shows some unexpected conclusions and promising leads for further research. This book provides a step by step manual on how to estimate various volatility models and how resulting estimates can be used for derivative pricing. This is extremely valuable for practitioners and others interested in modeling volatility in financial markets. Bestandsnummer des Verkäufers 9783843362061
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Modeling Volatility in Financial Time Series
Verlag:
LAP LAMBERT Academic Publishing Okt 2010, 2010
ISBN 10: 3843362068
ISBN 13: 9783843362061
Neu
Taschenbuch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Volatility is one of the biggest topics in finance today. It is the most important measure of risk and plays a crucial role in the valuation of derivatives. Volatility estimations are therefore essential in most financial decisions. However, it has been proven extremely difficult to model and forecast the volatility one witnesses in time series. This book compares two volatility models, their properties and their performances. The models compared are the GARCH model and the Markov Switching Multifractal model, two models that rely on completely different assumptions. This book assesses how both models perform in replicating financial time series. The model parameters are estimated on historical returns and option prices. The results are used to produce volatility forecasts which in their turn are evaluated in a Value at Risk setup. The analysis done shows some unexpected conclusions and promising leads for further research. This book provides a step by step manual on how to estimate various volatility models and how resulting estimates can be used for derivative pricing. This is extremely valuable for practitioners and others interested in modeling volatility in financial markets.Books on Demand GmbH, Überseering 33, 22297 Hamburg 88 pp. Englisch. Bestandsnummer des Verkäufers 9783843362061
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Modeling Volatility in Financial Time Series
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ISBN 10: 3843362068
ISBN 13: 9783843362061
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Zustand: New. PRINT ON DEMAND pp. 88. Bestandsnummer des Verkäufers 18128852483
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Modeling Volatility in Financial Time Series
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VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2010
ISBN 10: 3843362068
ISBN 13: 9783843362061
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Softcover
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Zustand: New. pp. 88. Bestandsnummer des Verkäufers 26128852489
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Beispielbild für diese ISBN
Modeling Volatility in Financial Time Series
Verlag:
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2010
ISBN 10: 3843362068
ISBN 13: 9783843362061
Neu
Softcover
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Zustand: New. Print on Demand pp. 88 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam. Bestandsnummer des Verkäufers 131702230
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