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Indexation and Causation of Financial Markets

  • Yoko Tanokura
  • Genshiro Kitagawa

Part of the SpringerBriefs in Statistics book series (BRIEFSSTATIST)

Also part of the JSS Research Series in Statistics book sub series (JSSRES)

Table of contents

  1. Front Matter
    Pages i-x
  2. Yoko Tanokura, Genshiro Kitagawa
    Pages 1-11
  3. Yoko Tanokura, Genshiro Kitagawa
    Pages 13-34
  4. Yoko Tanokura, Genshiro Kitagawa
    Pages 35-47
  5. Yoko Tanokura, Genshiro Kitagawa
    Pages 49-99
  6. Back Matter
    Pages 101-103

About this book

Introduction

​This book presents a new statistical method of constructing a price index of a financial asset where the price distributions are skewed and heavy-tailed and investigates the effectiveness of the method. In order to fully reflect the movements of prices or returns on a financial asset, the index should reflect their distributions. However, they are often heavy-tailed and possibly skewed, and identifying them directly is not easy. This book first develops an index construction method depending on the price distributions, by using nonstationary time series analysis. Firstly, the long-term trend of the distributions of the optimal Box–Cox transformed prices is estimated by fitting a trend model with time-varying observation noises. By applying state space modeling, the estimation is performed and missing observations are automatically interpolated. Finally, the index is defined by taking the inverse Box–Cox transformation of the optimal long-term trend. This book applies the method to various financial data. For example, applying it to the sovereign credit default swap market where the number of observations varies over time due to the immaturity, the spillover effects of the financial crisis are detected by using the power contribution analysis measuring the information flows between indices. The investigations show that applying this method to the markets with insufficient information such as fast-growing or immature markets can be effective.

Keywords

Financial market Non-Gaussian Nonstationary State-space modeling Time series Time-varying system

Authors and affiliations

  • Yoko Tanokura
    • 1
  • Genshiro Kitagawa
    • 2
  1. 1.Graduate School of Advanced Mathematical Sciences, Meiji UniversityNakano-kuJapan
  2. 2.Research Organization of Information and SystemsMinato-kuJapan

Bibliographic information

  • DOI https://doi.org/10.1007/978-4-431-55276-5
  • Copyright Information The Author(s) 2015
  • Publisher Name Springer, Tokyo
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-4-431-55275-8
  • Online ISBN 978-4-431-55276-5
  • Series Print ISSN 2191-544X
  • Series Online ISSN 2191-5458
  • Buy this book on publisher's site
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