Logo - springer
Slogan - springer

Statistics - Statistical Theory and Methods | Indexation and Causation of Financial Markets - Nonstationary Time Series Analysis Method

Indexation and Causation of Financial Markets

Nonstationary Time Series Analysis Method

Tanokura, Yoko, Kitagawa, Genshiro

2015, Approx. 90 p. 30 illus., 20 illus. in color.

Available Formats:

Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.

You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.

After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.


ISBN 978-4-431-55276-5

digitally watermarked, no DRM

The eBook version of this title will be available soon

learn more about Springer eBooks

add to marked items


Softcover (also known as softback) version.

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.


(net) price for USA

ISBN 978-4-431-55275-8

free shipping for individuals worldwide

Due: August 5, 2015

add to marked items

  • About this book

  • ​Provides a method of analysis for nonstationary non-Gaussian multivariate time series
  • Develops a means of constructing an index for financial time series
  • Explains a practical statistical technique for global investment management
​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.

Content Level » Research

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

Related subjects » Business, Economics & Finance - Physical & Information Science - Statistical Theory and Methods

Table of contents 

1: Introduction.- 2: Nonstationary time series  modeling.-3 : Construction method of a distribution-dependent index.- 4: Power contribution analysis of a feedback system.- 5: Application to financial data.- 6: Related information on the website.

Popular Content within this publication 



Services for this book

New Book Alert

Get alerted on new Springer publications in the subject area of Statistical Theory and Methods.