Modeling Volatility in Financial Time Series

Jesper Boer

ISBN 10: 3843362068 / ISBN 13: 9783843362061

Published by LAP LAMBERT Academic Publishing Okt 2010, 2010

About this Item

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.

Seller Inventory # 9783843362061

Bibliographic Details

• Title: Modeling Volatility in Financial Time Series
• Publisher: LAP LAMBERT Academic Publishing Okt 2010
• Publication Date: 2010
• Language: English
• ISBN 10: 3843362068
• ISBN 13: 9783843362061
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 6D millimeters 220 millimeters width by 150 millimeters height by 6 millimeters depth
• Weight: 149 grams

About this title

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.

About the Author

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.