IDEAS home Printed from https://ideas.repec.org/p/wpa/wuwpma/0512016.html
   My bibliography  Save this paper

Stock market returns and economic activity: evidence from wavelet analysis

Author

Listed:
  • Marco Gallegati

    (Department of Economics, Università Politecnica delle Marche)

Abstract

In this paper we investigate the relationship between stock market returns and economic activity by using signal decomposition techniques based on wavelet analysis. In particular, we apply the maximum overlap discrete wavelet transform (MODWT) to the DJIA stock price index and the industrial production index for US over the period 1961:1- 2005:3 and using the definitions of wavelet variance, wavelet correlation and cross-correlations analyze the association as well as the lead/lag relationship between stock prices and industrial production at the different time scales. Our results show that stock market returns tends to lead the level of economic activity but only at the highest scales (lowest frequencies), corresponding to periods of 16 months and longer, and that the periods by which stock returns lead output increase as the wavelet time scale increases.

Suggested Citation

  • Marco Gallegati, 2005. "Stock market returns and economic activity: evidence from wavelet analysis," Macroeconomics 0512016, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpma:0512016
    Note: Type of Document - pdf; pages: 12
    as

    Download full text from publisher

    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/mac/papers/0512/0512016.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Christoph Schleicher, 2002. "An Introduction to Wavelets for Economists," Staff Working Papers 02-3, Bank of Canada.
    2. Ramsey, J.B., 2002. "Wavelets in Economics and Finance: Past and Future," Working Papers 02-02, C.V. Starr Center for Applied Economics, New York University.
    3. Gençay, Ramazan & Selçuk, Faruk & Whitcher, Brandon, 2001. "Scaling properties of foreign exchange volatility," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 289(1), pages 249-266.
    4. Ramsey James B., 2002. "Wavelets in Economics and Finance: Past and Future," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(3), pages 1-29, November.
    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. Khalfaoui Rabeh, K & Boutahar Mohamed, B, 2011. "A time-scale analysis of systematic risk: wavelet-based approach," MPRA Paper 31938, University Library of Munich, Germany.

    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. Muhammad Azmat Hayat & Huma Ghulam & Maryam Batool & Muhammad Zahid Naeem & Abdullah Ejaz & Cristi Spulbar & Ramona Birau, 2021. "Investigating the Causal Linkages among Inflation, Interest Rate, and Economic Growth in Pakistan under the Influence of COVID-19 Pandemic: A Wavelet Transformation Approach," JRFM, MDPI, vol. 14(6), pages 1-22, June.
    2. Chakrabarty, Anindya & De, Anupam & Gunasekaran, Angappa & Dubey, Rameshwar, 2015. "Investment horizon heterogeneity and wavelet: Overview and further research directions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 45-61.
    3. Marco GALLEGATI, 2001. "A Wavelet Analysis of MENA stock markets," Middle East and North Africa 330400031, EcoMod.
    4. Francis In & Sangbae Kim, 2012. "An Introduction to Wavelet Theory in Finance:A Wavelet Multiscale Approach," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8431, August.
    5. Luca De Benedictis & Marco Gallegati, 2005. "Trade balance and terms of trade in U.S.: a time-scale decomposition analysis," International Trade 0512016, University Library of Munich, Germany.
    6. Patrick M. Crowley, 2007. "A Guide To Wavelets For Economists," Journal of Economic Surveys, Wiley Blackwell, vol. 21(2), pages 207-267, April.
    7. Patrick M. Crowley, 2005. "An intuitive guide to wavelets for economists," GE, Growth, Math methods 0508009, University Library of Munich, Germany.
    8. Charalampos Basdekis & Apostolos Christopoulos & Ioannis Katsampoxakis & Vasileios Nastas, 2022. "The Impact of the Ukrainian War on Stock and Energy Markets: A Wavelet Coherence Analysis," Energies, MDPI, vol. 15(21), pages 1-15, November.
    9. Meng, Xiangcai & Huang, Chia-Hsing, 2019. "The time-frequency co-movement of Asian effective exchange rates: A wavelet approach with daily data," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 131-148.
    10. Saumya Ranjan Dash & Debasish Maitra & Byomakesh Debata & Jitendra Mahakud, 2021. "Economic policy uncertainty and stock market liquidity: Evidence from G7 countries," International Review of Finance, International Review of Finance Ltd., vol. 21(2), pages 611-626, June.
    11. Gallegati, Marco & Ramsey, James B., 2013. "Structural change and phase variation: A re-examination of the q-model using wavelet exploratory analysis," Structural Change and Economic Dynamics, Elsevier, vol. 25(C), pages 60-73.
    12. Joanna Bruzda, 2011. "Business cycle synchronization according to wavelets – the case of Poland and the euro zone member countries," Bank i Kredyt, Narodowy Bank Polski, vol. 42(3), pages 5-32.
    13. Ibrahim Ahamada & Philippe Jolivaldt, 2010. "Classical vs wavelet-based filters Comparative study and application to business cycle," Post-Print halshs-00476022, HAL.
    14. repec:zbw:bofrdp:2013_034 is not listed on IDEAS
    15. Baqaee, David, 2010. "Using wavelets to measure core inflation: The case of New Zealand," The North American Journal of Economics and Finance, Elsevier, vol. 21(3), pages 241-255, December.
    16. Ahmed, Walid M.A., 2022. "On the higher-order moment interdependence of stock and commodity markets: A wavelet coherence analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 83(C), pages 135-151.
    17. Roger Bowden & Jennifer Zhu, 2010. "Multi-scale variation, path risk and long-term portfolio management," Quantitative Finance, Taylor & Francis Journals, vol. 10(7), pages 783-796.
    18. Bai, Limiao & Yan, Sen & Zheng, Xiaolian & Chen, Ben M., 2015. "Market turning points forecasting using wavelet analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 437(C), pages 184-197.
    19. Patrick Crowley, 2005. "An intuitive guide to wavelets for economists," Econometrics 0503017, University Library of Munich, Germany.
    20. Usman Khalid & Olivier Habimana, 2021. "Military Spending and Economic Growth in Turkey: A Wavelet Approach," Defence and Peace Economics, Taylor & Francis Journals, vol. 32(3), pages 362-376, April.
    21. Ibrahim Ahamada & Philippe Jolivaldt, 2010. "Classical vs wavelet-based filters Comparative study and application to business cycle," Documents de travail du Centre d'Economie de la Sorbonne 10027, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.

    More about this item

    Keywords

    stock market; industrial production; wavelet analysis;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:wpa:wuwpma:0512016. 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: EconWPA (email available below). General contact details of provider: https://econwpa.ub.uni-muenchen.de .

    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.