IDEAS home Printed from https://ideas.repec.org/a/spr/snbeco/v3y2023i7d10.1007_s43546-023-00508-2.html
   My bibliography  Save this article

An empirical characterization of volatility in the German stock market

Author

Listed:
  • Leonardo Quero Virla

    (Otto-Friedrich-Universität Bamberg (Faculty of Social Sciences, Economics, and Business Administration))

Abstract

Most previous studies on the volatility of returns in the German stock market have focused on issues of forecasting and predictability without further exploration of the economic determinants behind volatility over time. Using a GARCH model and a quantile regression framework, this paper expands the existing literature by conducting not only an estimation of volatility but also an empirical analysis of its economic determinants between 1991 and 2022. The main findings indicate that the volatility of the DAX is mainly influenced by the volatility of the US stock market, as well as by the assessment of the business situation and expectations of German industrial firms. Moreover, volatility reached its peak between 2001 and 2004 potentially due to Germany’s longest recession streak after the reunification. Nevertheless, recessions alone cannot uniformly explain volatility across all subsamples, and likewise, the relevance of other macroeconomic and financial factors is limited to specific cases. Overall, the findings stress the importance of appropriate distributional assumptions when analyzing extreme financial events.

Suggested Citation

  • Leonardo Quero Virla, 2023. "An empirical characterization of volatility in the German stock market," SN Business & Economics, Springer, vol. 3(7), pages 1-19, July.
    • Handle: RePEc:spr:snbeco:v:3:y:2023:i:7:d:10.1007_s43546-023-00508-2
    DOI: 10.1007/s43546-023-00508-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s43546-023-00508-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s43546-023-00508-2?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. Stefan Sauer & Klaus Wohlrabe, 2018. "The New ifo Business Climate Index for Germany," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 19(02), pages 59-64, July.
    2. Schmitt, Noemi & Westerhoff, Frank, 2014. "Speculative behavior and the dynamics of interacting stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 45(C), pages 262-288.
    3. Daniel Detzer & Nina Dodig & Trevor Evans & Eckhard Hein & Hansjörg Herr & Franz Josef Prante, 2017. "The German Financial System and the Financial and Economic Crisis," Financial and Monetary Policy Studies, Springer, number 978-3-319-56799-0, January.
    4. Eckhard Hein & Daniel Detzer, 2015. "Finance-Dominated Capitalism and Income Distribution: A Kaleckian Perspective on the Case of Germany," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 1(2), pages 171-191, July.
    5. Blaurock, Ivonne & Schmitt, Noemi & Westerhoff, Frank, 2018. "Market entry waves and volatility outbursts in stock markets," Journal of Economic Behavior & Organization, Elsevier, vol. 153(C), pages 19-37.
    6. Holger Claessen & Stefan Mittnik, 2002. "Forecasting stock market volatility and the informational efficiency of the DAX-index options market," The European Journal of Finance, Taylor & Francis Journals, vol. 8(3), pages 302-321.
    7. Barbu, Alexandru & Fricke, Christoph & ,, 2020. "Procyclical Asset Management and Bond Risk Premia," CEPR Discussion Papers 15123, C.E.P.R. Discussion Papers.
    8. Lux, Thomas, 2012. "Estimation of an agent-based model of investor sentiment formation in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1284-1302.
    9. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    10. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    11. Daniel Detzer & Nina Dodig & Trevor Evans & Eckhard Hein & Hansjörg Herr & Franz Josef Prante, 2017. "The Historical Development of the German Financial System," Financial and Monetary Policy Studies, in: The German Financial System and the Financial and Economic Crisis, chapter 0, pages 17-27, Springer.
    12. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    13. Roberto Veneziani & Luca Zamparelli & Maria Nikolaidi & Engelbert Stockhammer, 2017. "Minsky Models: A Structured Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 31(5), pages 1304-1331, December.
    14. Daniel Detzer & Nina Dodig & Trevor Evans & Eckhard Hein & Hansjörg Herr & Franz Josef Prante, 2017. "Regulation of the German Financial System," Financial and Monetary Policy Studies, in: The German Financial System and the Financial and Economic Crisis, chapter 0, pages 91-109, Springer.
    15. Werner, Thomas & Stapf, Jelena, 2003. "How wacky is the DAX? The changing structure of German stock market volatility," Discussion Paper Series 1: Economic Studies 2003,18, Deutsche Bundesbank.
    16. Robert J. Shiller, 2003. "From Efficient Markets Theory to Behavioral Finance," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 83-104, Winter.
    17. 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.
    18. Raunig, Burkhard, 2006. "The longer-horizon predictability of German stock market volatility," International Journal of Forecasting, Elsevier, vol. 22(2), pages 363-372.
    19. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    20. Eckhard Hein, 2015. "Finance-dominated capitalism and re-distribution of income: a Kaleckian perspective," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 39(3), pages 907-934.
    21. repec:ces:ifofor:v::y:2018:i::p: is not listed on IDEAS
    22. Roisin O'sullivan & Marc Tomljanovich, 2012. "Inflation targeting and financial market volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 22(9), pages 749-762, May.
    23. S. Muzzioli, 2010. "Option-based forecasts of volatility: an empirical study in the DAX-index options market," The European Journal of Finance, Taylor & Francis Journals, vol. 16(6), pages 561-586.
    24. Noemi Schmitt & Frank Westerhoff, 2017. "Herding behaviour and volatility clustering in financial markets," Quantitative Finance, Taylor & Francis Journals, vol. 17(8), pages 1187-1203, August.
    25. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    26. Daniel Detzer & Nina Dodig & Trevor Evans & Eckhard Hein & Hansjörg Herr & Franz Josef Prante, 2017. "The Institutional Structure of the German Financial System," Financial and Monetary Policy Studies, in: The German Financial System and the Financial and Economic Crisis, chapter 0, pages 55-70, Springer.
    27. Alexander J. McNeil & Rüdiger Frey & Paul Embrechts, 2015. "Quantitative Risk Management: Concepts, Techniques and Tools Revised edition," Economics Books, Princeton University Press, edition 2, number 10496.
    28. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    Full references (including those not matched with items on IDEAS)

    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. Virla, Leonardo Quero, 2021. "An empirical characterization of volatility dynamics in the DAX," IPE Working Papers 167/2021, Berlin School of Economics and Law, Institute for International Political Economy (IPE).
    2. Nicolau, Juan Luis & Sharma, Abhinav, 2022. "A review of research into drivers of firm value through event studies in tourism and hospitality: Launching the Annals of Tourism Research curated collection on drivers of firm value through event stu," Annals of Tourism Research, Elsevier, vol. 95(C).
    3. Muhammad Surajo Sanusi, 2017. "Investigating the sources of Black’s leverage effect in oil and gas stocks," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1318812-131, January.
    4. Chabi-Yo, Fousseni & Huggenberger, Markus & Weigert, Florian, 2022. "Multivariate crash risk," Journal of Financial Economics, Elsevier, vol. 145(1), pages 129-153.
    5. Sebastien Valeyre & Sofiane Aboura & Denis Grebenkov, 2019. "The Reactive Beta Model," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 42(1), pages 71-113, March.
    6. Chen, Xiaoyu & Chiang, Thomas C., 2016. "Stock returns and economic forces—An empirical investigation of Chinese markets," Global Finance Journal, Elsevier, vol. 30(C), pages 45-65.
    7. Peterburgsky, Stanley, 2021. "Aggregate volatility risk: International evidence," Global Finance Journal, Elsevier, vol. 47(C).
    8. S. Sudha, 2015. "Risk-return and Volatility analysis of Sustainability Index in India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 17(6), pages 1329-1342, December.
    9. Chuxuan Xiao & Winifred Huang & David P. Newton, 2024. "Predicting expected idiosyncratic volatility: Empirical evidence from ARFIMA, HAR, and EGARCH models," Review of Quantitative Finance and Accounting, Springer, vol. 63(3), pages 979-1006, October.
    10. Kumari, Jyoti, 2019. "Investor sentiment and stock market liquidity: Evidence from an emerging economy," Journal of Behavioral and Experimental Finance, Elsevier, vol. 23(C), pages 166-180.
    11. Imlak Shaikh & Puja Padhi, 2014. "The forecasting performance of implied volatility index: evidence from India VIX," Economic Change and Restructuring, Springer, vol. 47(4), pages 251-274, November.
    12. Jonas Rothfuss & Fabio Ferreira & Simon Walther & Maxim Ulrich, 2019. "Conditional Density Estimation with Neural Networks: Best Practices and Benchmarks," Papers 1903.00954, arXiv.org, revised Apr 2019.
    13. Keunbae Ahn, 2021. "Predictable Fluctuations in the Cross-Section and Time-Series of Asset Prices," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2021, January-A.
    14. Hediger, Simon & Näf, Jeffrey, 2024. "Combining the MGHyp distribution with nonlinear shrinkage in modeling financial asset returns," Journal of Empirical Finance, Elsevier, vol. 77(C).
    15. Karpouzis, Efstathios & Bouras, Chris & Kanas, Angelos, 2019. "Hedge fund activism, voice, and value creation," MPRA Paper 92576, University Library of Munich, Germany.
    16. Kei Nakagawa & Yusuke Uchiyama, 2020. "GO-GJRSK Model with Application to Higher Order Risk-Based Portfolio," Mathematics, MDPI, vol. 8(11), pages 1-12, November.
    17. Choi, Jaewon & Richardson, Matthew, 2016. "The volatility of a firm's assets and the leverage effect," Journal of Financial Economics, Elsevier, vol. 121(2), pages 254-277.
    18. Wang, Kai Y.K. & Chen, Cathy W.S. & So, Mike K.P., 2023. "Quantile three-factor model with heteroskedasticity, skewness, and leptokurtosis," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
    19. Cathy W. S. Chen & Muyi Li & Nga T. H. Nguyen & Songsak Sriboonchitta, 2017. "On Asymmetric Market Model with Heteroskedasticity and Quantile Regression," Computational Economics, Springer;Society for Computational Economics, vol. 49(1), pages 155-174, January.
    20. Hitz, Lukas & Mustafi, Ismail H. & Zimmermann, Heinz, 2022. "The pricing of volatility risk in the US equity market," International Review of Financial Analysis, Elsevier, vol. 79(C).

    More about this item

    Keywords

    Asset prices; Macro-financial linkages; Expectations; Quantile regression;
    All these keywords.

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

    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:spr:snbeco:v:3:y:2023:i:7:d:10.1007_s43546-023-00508-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.