High-Frequency Statistics with Asynchronous and Irregular Data
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 come
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Ole Martin
High-Frequency Statistics with Asynchronous and Irregular Data
Mathematische Optimierung und Wirtschaftsmathematik | Mathematical Optimization and Economathematics Reihe herausgegeben von Ralf Werner, Augsburg, Deutschland Tobias Harks, Augsburg, Deutschland Vladimir Shikhman, Chemnitz, Deutschland
In der Reihe werden Arbeiten zu aktuellen Themen der mathematischen Optimie rung und der Wirtschaftsmathematik publiziert. Hierbei werden sowohl Themen aus Grundlagen, Theorie und Anwendung der Wirtschafts-, Finanz- und Ver sicherungsmathematik als auch der Optimierung und des Operations Research behandelt. Die Publikationen sollen insbesondere neue Impulse für weiterge hende Forschungsfragen liefern, oder auch zu offenen Problemstellungen aus der Anwendung Lösungsansätze anbieten. Die Reihe leistet damit einen Beitrag der Bündelung der Forschung der Optimierung und der Wirtschaftsmathematik und der sich ergebenden Perspektiven.
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Ole Martin
High-Frequency Statistics with Asynchronous and Irregular Data
Ole Martin Department of Mathematics Kiel University (CAU) Kiel, Germany Dissertation, Kiel University (CAU), 2018
ISSN 2523-7926 ISSN 2523-7934 (electronic) Mathematische Optimierung und Wirtschaftsmathematik | Mathematical Optimization and Economathematics ISBN 978-3-658-28418-3 (eBook) ISBN 978-3-658-28417-6 https://doi.org/10.1007/978-3-658-28418-3 Springer Spektrum © Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2019 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer Spektrum imprint is published by the registered company Springer Fachmedien Wiesbaden GmbH part of Springer Nature. The registered company address is: Abraham-Lincoln-Str. 46, 65189 Wiesbaden, Germany
Preface Over the past two decades the field of high-frequency statistics especially
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