Discrete time series, processes, and applications in finance
Most financial and investment decisions are based on considerations of possible future changes and require forecasts on the evolution of the financial world. Time series and processes are the natural tools for describing the dynamic behavior of financial data, leading to the required forecasts. This...
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| Главный автор: | |
|---|---|
| Формат: | Livre numérique |
| Язык: | Anglais |
| Опубликовано: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer
[20..].
Cham : Springer Nature |
| Серии: | Springer Finance
|
| Online-ссылка: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Примечание: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Discrete Time Series, Processes, and Applications in Finance, Gilles Zumbach, Berlin, Springer-Verlag, 2013, 1 vol. (xxi-319 p.), Springer finance, 978-3-642-31741-5 |
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| 100 | 1 | |a Zumbach, Gilles. | |
| 245 | 1 | 0 | |a Discrete time series, processes, and applications in finance |c by Gilles Zumbach. |
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg : |b Imprint: Springer. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Springer Finance |x 1616-0533 | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a Preface List of Figures.-List of Tables 1. Introduction 2.Notation, naming and general definitions 3.Stylized facts 4.Empirical mug shots 5.Process Overview 6.Logarithmic versus relative random walks 7.ARCH processes 8.Stochastic volatility processes 9.Regime switching process 10.Price and volatility using high-frequency data 11.Time reversal asymmetry 12.Characterizing heteroskedasticity 13.The innovation distributions 14.Leverage effect 15.Processes and market risk evaluation 16.Option pricing 17.Properties of large covariance matrices 18.Multivariate ARCH processes 19.The processes compatible with the stylized facts 20.Further thoughts.-Bibliography Index | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a Most financial and investment decisions are based on considerations of possible future changes and require forecasts on the evolution of the financial world. Time series and processes are the natural tools for describing the dynamic behavior of financial data, leading to the required forecasts. This book presents a survey of the empirical properties of financial time series, their descriptions by means of mathematical processes, and some implications for important financial applications used in many areas like risk evaluation, option pricing or portfolio construction. The statistical tools used to extract information from raw data are introduced. Extensive multiscale empirical statistics provide a solid benchmark of stylized facts (heteroskedasticity, long memory, fat-tails, leverage ), in order to assess various mathematical structures that can capture the observed regularities. The author introduces a broad range of processes and evaluates them systematically against the benchmark, summarizing the successes and limitations of these models from an empirical point of view. The outcome is that only multiscale ARCH processes with long memory, discrete multiplicative structures and non-normal innovations are able to capture correctly the empirical properties. In particular, only a discrete time series framework allows to capture all the stylized facts in a process, whereas the stochastic calculus used in the continuum limit is too constraining. The present volume offers various applications and extensions for this class of processes including high-frequency volatility estimators, market risk evaluation, covariance estimation and multivariate extensions of the processes. The book discusses many practical implications and is addressed to practitioners and quants in the financial industry, as well as to academics, including graduate (Master or PhD level) students. The prerequisites are basic statistics and some elementary financial mathematics.Gilles Zumbach has worked for several institutions, including banks, hedge funds and service providers and continues to be engaged in research on many topics in finance. His primary areas of interest are volatility, ARCH processes and financial applications | ||
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