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Modeling Volatility in Financial Time Series: A comparison between GARCH and MSM volatility models - Couverture souple
Synopsis
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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Présentation de l'éditeur
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.
Biographie de l'auteur
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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
- ÉditeurLAP LAMBERT Academic Publishing
- Date d'édition2010
- ISBN 10 3843362068
- ISBN 13 9783843362061
- ReliureBroché
- Langueanglais
- Nombre de pages88
- Coordonnées du fabricantnon disponible
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Modeling Volatility in Financial Time Series
Edité par
LAP LAMBERT Academic Publishing, 2010
ISBN 10 : 3843362068
ISBN 13 : 9783843362061
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : 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. N° de réf. du vendeur 5466167
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Modeling Volatility in Financial Time Series : A comparison between GARCH and MSM volatility models
Edité par
LAP LAMBERT Academic Publishing, 2010
ISBN 10 : 3843362068
ISBN 13 : 9783843362061
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : 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. N° de réf. du vendeur 9783843362061
Quantité disponible : 1 disponible(s)
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Modeling Volatility in Financial Time Series
Edité par
LAP LAMBERT Academic Publishing Okt 2010, 2010
ISBN 10 : 3843362068
ISBN 13 : 9783843362061
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : 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. N° de réf. du vendeur 9783843362061
Quantité disponible : 2 disponible(s)
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Modeling Volatility in Financial Time Series
Edité par
LAP LAMBERT Academic Publishing Okt 2010, 2010
ISBN 10 : 3843362068
ISBN 13 : 9783843362061
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : 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. N° de réf. du vendeur 9783843362061
Quantité disponible : 1 disponible(s)
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Modeling Volatility in Financial Time Series
Edité par
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2010
ISBN 10 : 3843362068
ISBN 13 : 9783843362061
Neuf
Couverture souple
Vendeur : Books Puddle, New York, NY, Etats-Unis
Évaluation du vendeur 4 sur 5 étoiles
Etat : New. pp. 88. N° de réf. du vendeur 26128852489
Quantité disponible : 4 disponible(s)
Image d'archives
Modeling Volatility in Financial Time Series
Edité par
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2010
ISBN 10 : 3843362068
ISBN 13 : 9783843362061
Neuf
Couverture souple
Vendeur : Majestic Books, Hounslow, Royaume-Uni
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Etat : 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. N° de réf. du vendeur 131702230
Quantité disponible : 4 disponible(s)
Image d'archives
Modeling Volatility in Financial Time Series
Edité par
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2010
ISBN 10 : 3843362068
ISBN 13 : 9783843362061
Neuf
Couverture souple
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. PRINT ON DEMAND pp. 88. N° de réf. du vendeur 18128852483
Quantité disponible : 4 disponible(s)