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High-Frequency Statistics with Asynchronous and Irregular Data (Mathematische Optimierung und Wirtschaftsmathematik | Mathematical Optimization and Economathematics) - Softcover
Book 3 of 5: Mathematische Optimierung und Wirtschaftsmathematik | Mathematical Optimization and Economathematics
Synopsis
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.
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 irregularlyobserved data.
"synopsis" may belong to another edition of this title.
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.
From the Back Cover
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.
"About this title" may belong to another edition of this title.
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High-Frequency Statistics with Asynchronous and Irregular Data (eng)
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High-Frequency Statistics with Asynchronous and Irregular Data
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High-Frequency Statistics with Asynchronous and Irregular Data
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Springer Fachmedien Wiesbaden Nov 2019, 2019
ISBN 10: 365828417X
ISBN 13: 9783658284176
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 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. 340 pp. Englisch. Seller Inventory # 9783658284176
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High-Frequency Statistics with Asynchronous and Irregular Data (Mathematische Optimierung und Wirtschaftsmathematik | Mathematical Optimization and Economathematics)
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High-frequency Statistics With Asynchron
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High-Frequency Statistics with Asynchronous and Irregular Data (Mathematische Optimierung und Wirtschaftsmathematik | Mathematical Optimization and Economathematics)
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High-Frequency Statistics with Asynchronous and Irregular Data
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ISBN 10: 365828417X
ISBN 13: 9783658284176
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. New methods extending theory for regular dataNew methods extending theory for regular dataOle Martin extends well-established techniques for the analysis of high-frequency data based on regular observations to the more general setting of. Seller Inventory # 335811368
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High-Frequency Statistics with Asynchronous and Irregular Data
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. 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 irregularlyobserved data. Seller Inventory # 9783658284176
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