IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v312y2017icp49-65.html
   My bibliography  Save this article

The windowed scalogram difference: A novel wavelet tool for comparing time series

Author

Listed:
  • Bolós, V.J.
  • Benítez, R.
  • Ferrer, R.
  • Jammazi, R.

Abstract

We introduce a new wavelet-based tool called windowed scalogram difference (WSD), which has been designed to compare time series. This tool allows quantifying if two time series follow a similar pattern over time, comparing their scalograms and determining if they give the same weight to the different scales. The WSD can be seen as an alternative to another tool widely used in wavelet analysis called wavelet squared coherence (WSC) and, in some cases, it detects features that the WSC is not able to identify. As an application, the WSD is used to examine the dynamics of the integration of government bond markets in the euro area since the inception of the euro as a European single currency in January 1999.

Suggested Citation

  • Bolós, V.J. & Benítez, R. & Ferrer, R. & Jammazi, R., 2017. "The windowed scalogram difference: A novel wavelet tool for comparing time series," Applied Mathematics and Computation, Elsevier, vol. 312(C), pages 49-65.
  • Handle: RePEc:eee:apmaco:v:312:y:2017:i:c:p:49-65
    DOI: 10.1016/j.amc.2017.05.046
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300317303478
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2017.05.046?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Cho, Jin Seo & Kim, Tae-hwan & Shin, Yongcheol, 2015. "Quantile cointegration in the autoregressive distributed-lag modeling framework," Journal of Econometrics, Elsevier, vol. 188(1), pages 281-300.
    2. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    3. Abad, Pilar & Chuliá, Helena & Gómez-Puig, Marta, 2010. "EMU and European government bond market integration," Journal of Banking & Finance, Elsevier, vol. 34(12), pages 2851-2860, December.
    4. Luís Aguiar-Conraria & Maria Joana Soares, 2014. "The Continuous Wavelet Transform: Moving Beyond Uni- And Bivariate Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 28(2), pages 344-375, April.
    5. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    6. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    7. Pozzi, Lorenzo & Wolswijk, Guido, 2012. "The time-varying integration of euro area government bond markets," European Economic Review, Elsevier, vol. 56(1), pages 36-53.
    8. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    9. Christian Bayer & Christoph Hanck, 2013. "Combining non-cointegration tests," Journal of Time Series Analysis, Wiley Blackwell, vol. 34(1), pages 83-95, January.
    10. Patrick M. Crowley, 2007. "A Guide To Wavelets For Economists," Journal of Economic Surveys, Wiley Blackwell, vol. 21(2), pages 207-267, April.
    11. Guodong Li & Yang Li & Chih-Ling Tsai, 2015. "Quantile Correlations and Quantile Autoregressive Modeling," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 246-261, March.
    12. Sim, Nicholas & Zhou, Hongtao, 2015. "Oil prices, US stock return, and the dependence between their quantiles," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 1-8.
    13. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    14. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tiwari, Aviral Kumar & Aikins Abakah, Emmanuel Joel & Adekoya, Oluwasegun B. & Hammoudeh, Shawkat, 2023. "What do we know about the price spillover between green bonds and Islamic stocks and stock market indices?," Global Finance Journal, Elsevier, vol. 55(C).
    2. Doğan, Buhari & Trabelsi, Nader & Tiwari, Aviral Kumar & Ghosh, Sudeshna, 2023. "Dynamic dependence and causality between crude oil, green bonds, commodities, geopolitical risks, and policy uncertainty," The Quarterly Review of Economics and Finance, Elsevier, vol. 89(C), pages 36-62.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, January.
    2. Adrian C. Darnell, 1994. "A Dictionary Of Econometrics," Books, Edward Elgar Publishing, number 118.
    3. Mohamed El Hedi Arouri & Mondher Bellalah & Duc Khuong Nguyen, 2010. "The comovements in international stock markets: new evidence from Latin American emerging countries," Applied Economics Letters, Taylor & Francis Journals, vol. 17(13), pages 1323-1328.
    4. Committee, Nobel Prize, 2003. "Time-series Econometrics: Cointegration and Autoregressive Conditional Heteroskedasticity," Nobel Prize in Economics documents 2003-1, Nobel Prize Committee.
    5. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, April.
    6. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    7. Madina D. Sharapiyeva & Kunanbayeva Duissekul & Nurseiytova Gulmira & Kozhamkulova Zhanna, 2019. "Energy Efficiency of Transport and Logistics Infrastructure: The Example of the Republic of Kazakhstan," International Journal of Energy Economics and Policy, Econjournals, vol. 9(5), pages 331-338.
    8. Ericsson, Neil R & Hendry, David F & Mizon, Grayham E, 1998. "Exogeneity, Cointegration, and Economic Policy Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(4), pages 370-387, October.
    9. Esparcia, Carlos & Jareño, Francisco & Umar, Zaghum, 2022. "Revisiting the safe haven role of Gold across time and frequencies during the COVID-19 pandemic," The North American Journal of Economics and Finance, Elsevier, vol. 61(C).
    10. Pami Dua & Nishita Raje & Satyananda Sahoo, 2004. "Interest Rate Modeling and Forecasting in India," Occasional papers 3, Centre for Development Economics, Delhi School of Economics.
    11. John Geweke & Joel Horowitz & M. Hashem Pesaran, 2006. "Econometrics: A Bird’s Eye View," CESifo Working Paper Series 1870, CESifo.
    12. Salles, Andre Assis de, 2014. "Asymmetry between Gasoline and Crude Oil Prices in the Brazilian Economy and Some Selected Developed Economies," MPRA Paper 98985, University Library of Munich, Germany, revised 2020.
    13. David Greasley & Les Oxley, 2010. "Cliometrics And Time Series Econometrics: Some Theory And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 24(5), pages 970-1042, December.
    14. Yarovaya, Larisa & Lau, Marco Chi Keung, 2016. "Stock market comovements around the Global Financial Crisis: Evidence from the UK, BRICS and MIST markets," Research in International Business and Finance, Elsevier, vol. 37(C), pages 605-619.
    15. Zhao, Yixiu & Upreti, Vineet & Cai, Yuzhi, 2021. "Stock returns, quantile autocorrelation, and volatility forecasting," International Review of Financial Analysis, Elsevier, vol. 73(C).
    16. Bathia, Deven & Demirer, Riza & Gupta, Rangan & Kotzé, Kevin, 2021. "Unemployment fluctuations and currency returns in the United Kingdom: Evidence from over one and a half century of data," Journal of Multinational Financial Management, Elsevier, vol. 61(C).
    17. Nikolaos A. Kyriazis, 2021. "A Survey on Volatility Fluctuations in the Decentralized Cryptocurrency Financial Assets," JRFM, MDPI, vol. 14(7), pages 1-46, June.
    18. Lang, Korbinian & Auer, Benjamin R., 2020. "The economic and financial properties of crude oil: A review," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    19. Ebenezer, Appiah Collins & Jatoe, John Baptist D. & Mensa-Bonsu, Akwasi, 2018. "Food Price Sensitivity To Changes In Petroleum Price And Exchange Rate In Ghana: A Cointegration Analysis," 2018 Conference (2nd), August 8-11, Kumasi, Ghana 277791, Ghana Association of Agricultural Economists.
    20. Ping, Li & Ziyi, Zhang & Tianna, Yang & Qingchao, Zeng, 2018. "The relationship among China’s fuel oil spot, futures and stock markets," Finance Research Letters, Elsevier, vol. 24(C), pages 151-162.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:apmaco:v:312:y:2017:i:c:p:49-65. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.