High-Frequency Statistics with Asynchronous and Irregular Data: Mathematische Optimierung und Wirtschaftsmathematik | Mathematical Optimization and Economathematics
Autor Ole Martinen Limba Engleză Paperback – 14 noi 2019
Ole Martin extends well-established techniques for the analysis of high-frequency data based on regular observations to the more general setting of asynchronous and irregular observations. Such methods are much needed in practice as real data usually comes in irregular form. In the theoretical part he develops laws of large numbers and central limit theorems as well as a new bootstrap procedure to assess asymptotic laws. The author then applies the theoretical results to estimate the quadratic covariation and to construct tests for the presence of common jumps. The simulation results show that in finite samples his methods despite the much more complex setting perform comparably well as methods based on regular data.
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Specificații
ISBN-13: 9783658284176
ISBN-10: 365828417X
Pagini: 323
Ilustrații: XIII, 323 p. 34 illus.
Dimensiuni: 148 x 210 mm
Greutate: 0.41 kg
Ediția:1st ed. 2019
Editura: Springer Fachmedien Wiesbaden
Colecția Springer Spektrum
Seria Mathematische Optimierung und Wirtschaftsmathematik | Mathematical Optimization and Economathematics
Locul publicării:Wiesbaden, Germany
ISBN-10: 365828417X
Pagini: 323
Ilustrații: XIII, 323 p. 34 illus.
Dimensiuni: 148 x 210 mm
Greutate: 0.41 kg
Ediția:1st ed. 2019
Editura: Springer Fachmedien Wiesbaden
Colecția Springer Spektrum
Seria Mathematische Optimierung und Wirtschaftsmathematik | Mathematical Optimization and Economathematics
Locul publicării:Wiesbaden, Germany
Cuprins
Laws of Large Numbers.- Random Observation Schemes.- Bootstrapping Asymptotic Laws.- Testing for (Common) Jumps.
Notă biografică
Dr. Ole Martin completed his PhD at the Kiel University (CAU), Germany. His research focuses on high-frequency statistics for semimartingales with the aim to develop methods based on irregularly observed data.
Textul de pe ultima copertă
Ole Martin extends well-established techniques for the analysis of high-frequency data based on regular observations to the more general setting of asynchronous and irregular observations. Such methods are much needed in practice as real data usually comes in irregular form. In the theoretical part he develops laws of large numbers and central limit theorems as well as a new bootstrap procedure to assess asymptotic laws. The author then applies the theoretical results to estimate the quadratic covariation and to construct tests for the presence of common jumps. The simulation results show that in finite samples his methods despite the much more complex setting perform comparably well as methods based on regular data.
Contents
- Laws of Large Numbers
- Random Observation Schemes
- Bootstrapping Asymptotic Laws
- Testing for (Common) Jumps
Target Groups
- Scientists andstudents in the field of mathematical statistics, econometrics and financial mathematics
- Practitioners in the field of financial mathematics
About the Author
Dr. Ole Martin completed his PhD at the Kiel University (CAU), Germany. His research focuses on high-frequency statistics for semimartingales with the aim to develop methods based on irregularly observed data.
Caracteristici
New methods extending theory for regular data