Residual Component

Sometimes it seems from the visual point of view that the analyzed time series does not indicate the presence of any systematic component, so that it is white noise only (even if this white noise can be shifted to a nonzero level). For example, the graphi

  • PDF / 10,621,691 Bytes
  • 409 Pages / 439.42 x 683.15 pts Page_size
  • 42 Downloads / 227 Views

DOWNLOAD

REPORT


Time Series in Economics and Finance

Time Series in Economics and Finance

Tomas Cipra

Time Series in Economics and Finance

Tomas Cipra Faculty of Mathematics and Physics Charles University Prague, Czech Republic

ISBN 978-3-030-46346-5 ISBN 978-3-030-46347-2 https://doi.org/10.1007/978-3-030-46347-2

(eBook)

Mathematics Subject Classification: 62M10, 91B84, 62M20, 62P20, 91B25, 91B30 © Springer Nature Switzerland AG 2020 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 imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Contents

1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Part I 2

Subject of Time Series

Random Processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Random Processes as Models for Time Series . . . . . . . . . . . . . 2.2 Specific Problems of Time Series Analysis . . . . . . . . . . . . . . . 2.2.1 Problems of Economic and Financial Data Observed in Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2.2 Methodological Problems . . . . . . . . . . . . . . . . . . . . . 2.2.3 Problems with Construction of Predictions . . . . . . . . . 2.3 Random Processes with Discrete States in Discrete Time . . . . . 2.3.1 Binary Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.2 Random Walk . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.3 Branching Process . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3.4 Markov Chain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4 Random Processes with Discrete States in Continuous Time . . 2.4.1 Poisson Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.2 Markov Process . . . . . . . . . . . . . . . . . . . . . . . .

Data Loading...