Risk Estimation on High Frequency Financial Data Empirical Analysis
By studying the ability of the Normal Tempered Stable (NTS) model to fit the statistical features of intraday data at a 5 min sampling frequency, Florian Jacobs extends the research on high frequency data as well as the appliance of tempered stable models
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Springer awards „BestMasters“ to the best master’s theses which have been completed at renowned universities in Germany, Austria, and Switzerland. The studies received highest marks and were recommended for publication by supervisors. They address current issues from various fields of research in natural sciences, psychology, technology, and economics. The series addresses practitioners as well as scientists and, in particular, offers guidance for early stage researchers.
Florian Jacob
Risk Estimation on High Frequency Financial Data Empirical Analysis of the DAX 30
Florian Jacob Karlsruhe, Germany
BestMasters ISBN 978-3-658-09388-4 ISBN 978-3-658-09389-1 (eBook) DOI 10.1007/978-3-658-09389-1 Library of Congress Control Number: 2015936902 Springer Spektrum © Springer Fachmedien Wiesbaden 2015 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, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper Springer Spektrum is a brand of Springer Fachmedien Wiesbaden Springer Fachmedien Wiesbaden is part of Springer Science+Business Media (www.springer.com)
Acknowledgements
This work would not have been possible without the support, encouragement, and advice of several people. Foremost, I would like to thank Dr. habil. Young Shin (Aaron) Kim for the introduction to the topic during my time as a master student at the Karlsruher Institute of Technology, as well as for the guidance and support throughout this thesis. I would also want to express my gratitude to Prof. Dr. Wolf-Dieter Heller and Prof. Dr. Svetlozar (Zari) Rachev for giving me the opportunity to pursue my interests in Germany and during my two month stay at Stony Brook University, USA. This time as well as helping me to develop a professional skill set, let me develop as a person.
Florian Jacob
Contents
1. Introduction
1
2. Theory of Time Series Modeling and Risk Estimation
5
2.1. Financial Econometrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
6
2.1.1. GARCH models . . . . . . . . . . . . . . . . . . . . . . . .
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