Quantile and Copula Spectrum: A New Approach to Investigate Cyclical Dependence in Economic Time Series

Gilles Dufrénot (), Takashi Matsuki and Kimiko Sugimoto
Additional contact information
Kimiko Sugimoto: Konan University

A chapter in Recent Econometric Techniques for Macroeconomic and Financial Data, 2021, pp 3-34 from Springer

Abstract: Abstract This chapter presents a survey of some recent methods used in economics and finance to account for cyclical dependence and account for their multifaced dynamics: nonlinearities, extreme events, asymmetries, non-stationarity, time-varying moments. To circumvent the caveats of the standard spectral analysis, new tools are now used based on copula spectrum, quantile spectrum and Laplace periodogram in both non-parametric and parametric contexts. The chapter presents a comprehensive overview of both theoretical and empirical issues as well as a computational approach to explain how the methods can be implemented using the R Package.

Date: 2021
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
Working Paper: Quantile and Copula Spectrum: A New Approach to Investigate Cyclical Dependence in Economic Time Series (2021)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:dymchp:978-3-030-54252-8_1

Ordering information: This item can be ordered from
http://www.springer.com/9783030542528

DOI: 10.1007/978-3-030-54252-8_1

Access Statistics for this chapter

More chapters in Dynamic Modeling and Econometrics in Economics and Finance from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().