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This comprehensive guide delves into the theory and practice of volatility models in financial engineering, a crucial topic in today's fast-paced communication landscape. It reviews recent advancements in empirical finance and time series econometrics, focusing on essential concepts for modeling financial time series volatility—both univariate and multivariate, as well as parametric and non-parametric, across varying frequencies. Contributions from international experts enrich the text with real-world examples and applications, demonstrating effective methods for assessing volatility rates. The book is structured into three sections that blend statistical and practical aspects of volatility. The first section covers Autoregressive Conditional Heteroskedasticity and Stochastic Volatility, emphasizing recent research on equity market spillovers. The second section introduces alternative approaches, including multiplicative error models, nonparametric and semi-parametric models, and copula-based models of (co)volatilities. The final section addresses the measurement of volatility through realized variances and covariances, offering guidance on modeling and forecasting these metrics. This resource is invaluable for academics and practitioners in finance, business, and econometrics, serving as a reference and a supplementary text for upper-undergraduate and graduate courses on risk management and volatility.
Achat du livre
Handbook of Volatility Models and Their Applications, Christian M. Hafner, Luc Bauwens, Laurent Sébastien Fournier
- Langue
- Année de publication
- 2012
- Reliure
- (rigide)
Modes de paiement
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- Titre
- Handbook of Volatility Models and Their Applications
- Langue
- Anglais
- Éditeur
- Wiley
- Publié
- 2012
- Format
- rigide
- Pages
- 576
- ISBN10
- 0470872519
- ISBN13
- 9780470872512
- Séries
- Mots clés
- Nonfiction, Commerce, Affaires & Gestion, Économie, Finance, Écrits rassemblés, Assurance
- Description
- This comprehensive guide delves into the theory and practice of volatility models in financial engineering, a crucial topic in today's fast-paced communication landscape. It reviews recent advancements in empirical finance and time series econometrics, focusing on essential concepts for modeling financial time series volatility—both univariate and multivariate, as well as parametric and non-parametric, across varying frequencies. Contributions from international experts enrich the text with real-world examples and applications, demonstrating effective methods for assessing volatility rates. The book is structured into three sections that blend statistical and practical aspects of volatility. The first section covers Autoregressive Conditional Heteroskedasticity and Stochastic Volatility, emphasizing recent research on equity market spillovers. The second section introduces alternative approaches, including multiplicative error models, nonparametric and semi-parametric models, and copula-based models of (co)volatilities. The final section addresses the measurement of volatility through realized variances and covariances, offering guidance on modeling and forecasting these metrics. This resource is invaluable for academics and practitioners in finance, business, and econometrics, serving as a reference and a supplementary text for upper-undergraduate and graduate courses on risk management and volatility.