IDEAS home Printed from https://ideas.repec.org/a/men/journl/v4y2018i2p111-125.html
   My bibliography  Save this article

Does the Federal Constitutional Court Ruling Mean the German Financial Market is Efficient?

Author

Listed:
  • Bachar Fakhry

    (The University of Lahore)

  • Christian Richter

    (German University in Cairo, Egypt)

Abstract

Following the landmark ruling by the German Federal Constitutional Court in Karlsruhe on 7th February 2014 in which they endorsed the efficient market hypothesis, we present evidence on the efficiency of the German financial market. Introducing a new variance bound test based on the Component-GARCH model of volatility to analyse the long- and short-runs effects on the efficiency of the German financial market, we test the price volatility of four markets: DAX stock index, German sovereign debt index as provided by Barclays and Bloomberg, Euro gold index by the World Gold Council and Euro currency index by the Bank of England. Our use of the Component-GARCH-T model highlight two key contributions, the first being the analysis of the efficiency of the market in the long and short runs. However, a more important contribution is the result of our variance bound test highlight the relatively strong acceptance of the efficient market hypothesis in both the short and long runs in all the observed financial markets. It must be stated our research is of importance to researches in both applied finance and portfolio management. The influencing question of what moves specific markets is crucial to market participants seeking market alpha for their investments strategies and portfolio optimisations.

Suggested Citation

  • Bachar Fakhry & Christian Richter, 2018. "Does the Federal Constitutional Court Ruling Mean the German Financial Market is Efficient?," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, vol. 4(2), pages 111-125.
    • Handle: RePEc:men:journl:v:4:y:2018:i:2:p:111-125
    DOI: 10.11118/ejobsat.v4i2.120
    as

    Download full text from publisher

    File URL: http://ejobsat.cz/doi/10.11118/ejobsat.v4i2.120.html
    Download Restriction: free of charge
    File URL: http://ejobsat.cz/doi/10.11118/ejobsat.v4i2.120.pdf
    Download Restriction: free of charge
    File URL: https://libkey.io/10.11118/ejobsat.v4i2.120?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 look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Miles Parker & Daan Steenkamp, 2012. "The economic impact of the Canterbury earthquakes," Reserve Bank of New Zealand Bulletin, Reserve Bank of New Zealand, vol. 75, pages 13-25, September.
    2. Gadi Barlevy, 2007. "Economic theory and asset bubbles," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 31(Q III), pages 44-59.
    3. Simón Sosvilla-Rivero & Amalia Morales-Zumaquero, 2011. "Volatility in EMU sovereign bond yields: Permanent and transitory components," Working Papers del Instituto Complutense de Estudios Internacionales 1106, Universidad Complutense de Madrid, Instituto Complutense de Estudios Internacionales.
    4. Economou, Fotini & Kostakis, Alexandros & Philippas, Nikolaos, 2011. "Cross-country effects in herding behaviour: Evidence from four south European markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 21(3), pages 443-460, July.
    5. Narayan, Paresh Kumar & Narayan, Seema & Zheng, Xinwei, 2010. "Gold and oil futures markets: Are markets efficient?," Applied Energy, Elsevier, vol. 87(10), pages 3299-3303, October.
    6. Bachar FAKHRY, 2016. "A Literature Review of the Efficient Market Hypothesis," Turkish Economic Review, KSP Journals, vol. 3(3), pages 431-442, September.
    7. Burton G. Malkiel, 1962. "Expectations, Bond Prices, and the Term Structure of Interest Rates," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 76(2), pages 197-218.
    8. Wang, Yudong & Wei, Yu & Wu, Chongfeng, 2011. "Analysis of the efficiency and multifractality of gold markets based on multifractal detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(5), pages 817-827.
    9. Shiller, Robert J, 1979. "The Volatility of Long-Term Interest Rates and Expectations Models of the Term Structure," Journal of Political Economy, University of Chicago Press, vol. 87(6), pages 1190-1219, December.
    10. Du, Ding & Hu, Ou, 2014. "The long-run component of foreign exchange volatility and stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 31(C), pages 268-284.
    11. Onali, Enrico & Goddard, John, 2011. "Are European equity markets efficient? New evidence from fractal analysis," International Review of Financial Analysis, Elsevier, vol. 20(2), pages 59-67, April.
    12. Ray Ball, 2009. "The Global Financial Crisis and the Efficient Market Hypothesis: What Have We Learned?," Journal of Applied Corporate Finance, Morgan Stanley, vol. 21(4), pages 8-16, September.
    13. Olivier J. Blanchard & Mark W. Watson, 1982. "Bubbles, Rational Expectations and Financial Markets," NBER Working Papers 0945, National Bureau of Economic Research, Inc.
    14. Ľuboš Pástor & Robert F. Stambaugh, 2012. "Are Stocks Really Less Volatile in the Long Run?," Journal of Finance, American Finance Association, vol. 67(2), pages 431-478, April.
    15. Jiang, Zhi-Qiang & Zhou, Wei-Xing & Sornette, Didier & Woodard, Ryan & Bastiaensen, Ken & Cauwels, Peter, 2010. "Bubble diagnosis and prediction of the 2005-2007 and 2008-2009 Chinese stock market bubbles," Journal of Economic Behavior & Organization, Elsevier, vol. 74(3), pages 149-162, June.
    16. Mali, Provash & Mukhopadhyay, Amitabha, 2014. "Multifractal characterization of gold market: A multifractal detrended fluctuation analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 413(C), pages 361-372.
    17. Theodore Panagiotidis, 2010. "Market efficiency and the Euro: the case of the Athens stock exchange," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 37(3), pages 237-251, July.
    18. Guo, Hui & Neely, Christopher J., 2008. "Investigating the intertemporal risk-return relation in international stock markets with the component GARCH model," Economics Letters, Elsevier, vol. 99(2), pages 371-374, May.
    19. Engle, Robert F. & White (the late), Halbert (ed.), 1999. "Cointegration, Causality, and Forecasting: Festschrift in Honour of Clive W. J. Granger," OUP Catalogue, Oxford University Press, number 9780198296836, Decembrie.
    20. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    21. Colacito, Riccardo & Engle, Robert F. & Ghysels, Eric, 2011. "A component model for dynamic correlations," Journal of Econometrics, Elsevier, vol. 164(1), pages 45-59, September.
    22. Maria Rosa Borges, 2010. "Efficient market hypothesis in European stock markets," The European Journal of Finance, Taylor & Francis Journals, vol. 16(7), pages 711-726.
    23. Tobias Adrian & Joshua Rosenberg, 2008. "Stock Returns and Volatility: Pricing the Short‐Run and Long‐Run Components of Market Risk," Journal of Finance, American Finance Association, vol. 63(6), pages 2997-3030, December.
    24. John R. Nofsinger & Richard W. Sias, 1999. "Herding and Feedback Trading by Institutional and Individual Investors," Journal of Finance, American Finance Association, vol. 54(6), pages 2263-2295, December.
    25. Sensoy, Ahmet & Tabak, Benjamin M., 2015. "Time-varying long term memory in the European Union stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 147-158.
    26. Bachar Fakhry & Christian Richter, 2015. "Is the sovereign debt market efficient? Evidence from the US and German sovereign debt markets," International Economics and Economic Policy, Springer, vol. 12(3), pages 339-357, September.
    27. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    28. Shiller, Robert J, 1981. "The Use of Volatility Measures in Assessing Market Efficiency," Journal of Finance, American Finance Association, vol. 36(2), pages 291-304, May.
    29. Christian Rudolf RICHTER & Bachar FAKHRY, 2016. "Testing the Efficiency of the GIPS Sovereign Debt Markets using an Asymmetrical Volatility Test," Journal of Economics and Political Economy, KSP Journals, vol. 3(3), pages 524-535, September.
    30. Hui Guo, 2006. "The Risk‐Return Relation in International Stock Markets," The Financial Review, Eastern Finance Association, vol. 41(4), pages 565-587, November.
    31. Markus K. Brunnermeier, 2009. "Deciphering the Liquidity and Credit Crunch 2007-2008," Journal of Economic Perspectives, American Economic Association, vol. 23(1), pages 77-100, Winter.
    32. Sornette, Didier & Cauwels, Peter, 2015. "Financial Bubbles: Mechanisms and Diagnostics," Review of Behavioral Economics, now publishers, vol. 2(3), pages 279-305, October.
    33. Zhang, Yue-Jun & Wei, Yi-Ming, 2010. "The crude oil market and the gold market: Evidence for cointegration, causality and price discovery," Resources Policy, Elsevier, vol. 35(3), pages 168-177, September.
    34. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    35. Alexandru Todea & Dorina Lazar, 2012. "Global Crisis and Relative Efficiency: Empirical Evidence from Central and Eastern European Stock Markets," The Review of Finance and Banking, Academia de Studii Economice din Bucuresti, Romania / Facultatea de Finante, Asigurari, Banci si Burse de Valori / Catedra de Finante, vol. 4(1), pages 045-053, June.
    36. Hsien-Yi Lee & Khatanbaatar Sodoikhuu, 2012. "Efficiency Tests in Foreign Exchange Market," International Journal of Economics and Financial Issues, Econjournals, vol. 2(2), pages 216-224.
    37. R. F. Engle & A. J. Patton, 2001. "What good is a volatility model?," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 237-245.
    38. 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)

    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. BAUWENS, Luc & HAFNER, Christian & LAURENT, Sébastien, 2011. "Volatility models," LIDAM Discussion Papers CORE 2011058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
      • Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
      • Bauwens, L. & Hafner C. & Laurent, S., 2011. "Volatility Models," LIDAM Discussion Papers ISBA 2011044, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    2. Bachar Fakhry & Christian Richter, 2015. "Is the sovereign debt market efficient? Evidence from the US and German sovereign debt markets," International Economics and Economic Policy, Springer, vol. 12(3), pages 339-357, September.
    3. Catania, Leopoldo & Proietti, Tommaso, 2020. "Forecasting volatility with time-varying leverage and volatility of volatility effects," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
    4. Christoffersen, Peter & Jacobs, Kris & Ornthanalai, Chayawat & Wang, Yintian, 2008. "Option valuation with long-run and short-run volatility components," Journal of Financial Economics, Elsevier, vol. 90(3), pages 272-297, December.
    5. Yu-Hua Zeng & Shou-Lei Wang & Yu-Fei Yang, 2014. "Calibration of the Volatility in Option Pricing Using the Total Variation Regularization," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-9, March.
    6. Jovanovic, Franck & Schinckus, Christophe, 2017. "Econophysics and Financial Economics: An Emerging Dialogue," OUP Catalogue, Oxford University Press, number 9780190205034, Decembrie.
    7. Saker Sabkha & Christian Peretti & Dorra Hmaied, 2019. "On the informational market efficiency of the worldwide sovereign credit default swaps," Journal of Asset Management, Palgrave Macmillan, vol. 20(7), pages 581-608, December.
    8. Mehmet Sahiner, 2022. "Forecasting volatility in Asian financial markets: evidence from recursive and rolling window methods," SN Business & Economics, Springer, vol. 2(10), pages 1-74, October.
    9. Conrad, Christian & Loch, Karin, 2012. "Anticipating Long-Term Stock Market Volatility," Working Papers 0535, University of Heidelberg, Department of Economics.
    10. Muhammad Sheraz & Imran Nasir, 2021. "Information-Theoretic Measures and Modeling Stock Market Volatility: A Comparative Approach," Risks, MDPI, vol. 9(5), pages 1-20, May.
    11. Kin-Boon Tang & Shao-Jye Wong & Shih-Kuei Lin & Szu-Lang Liao, 2020. "Excess volatility and market efficiency in government bond markets: the ASEAN-5 context," Journal of Asset Management, Palgrave Macmillan, vol. 21(2), pages 154-165, March.
    12. 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.
    13. Liu, Min & Lee, Chien-Chiang, 2022. "Is gold a long-run hedge, diversifier, or safe haven for oil? Empirical evidence based on DCC-MIDAS," Resources Policy, Elsevier, vol. 76(C).
    14. Subrata ROY, 2021. "Volatility Forecasting, Market Efficiency and Effect of Recession of SRI Indices," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(2(627), S), pages 259-284, Summer.
    15. Cheikh, Nidhaleddine Ben & Zaied, Younes Ben & Chevallier, Julien, 2020. "Asymmetric volatility in cryptocurrency markets: New evidence from smooth transition GARCH models," Finance Research Letters, Elsevier, vol. 35(C).
    16. Mohamed CHIKHI & Claude DIEBOLT & Tapas MISHRA, 2019. "Memory that Drives! New Insights into Forecasting Performance of Stock Prices from SEMIFARMA-AEGAS Model," Working Papers 07-19, Association Française de Cliométrie (AFC).
    17. 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).
    18. Rosenberg, Joshua V. & Engle, Robert F., 2002. "Empirical pricing kernels," Journal of Financial Economics, Elsevier, vol. 64(3), pages 341-372, June.
    19. Benlagha, Noureddine & Chargui, Sana, 2017. "Range-based and GARCH volatility estimation: Evidence from the French asset market," Global Finance Journal, Elsevier, vol. 32(C), pages 149-165.
    20. Claudeci Da Silva & Hugo Agudelo Murillo & Joaquim Miguel Couto, 2014. "Early Warning Systems: Análise De Ummodelo Probit De Contágio De Crise Dos Estados Unidos Para O Brasil(2000-2010)," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 110, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].

    More about this item

    Keywords

    EMH; volatility tests; C-GARCH-T; financial markets; gold market;
    All these keywords.

    JEL classification:

    • B13 - Schools of Economic Thought and Methodology - - History of Economic Thought through 1925 - - - Neoclassical through 1925 (Austrian, Marshallian, Walrasian, Wicksellian)
    • B21 - Schools of Economic Thought and Methodology - - History of Economic Thought since 1925 - - - Microeconomics
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • H63 - Public Economics - - National Budget, Deficit, and Debt - - - Debt; Debt Management; Sovereign Debt

    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:men:journl:v:4:y:2018:i:2:p:111-125. 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: Ivo Andrle (email available below). General contact details of provider: https://edirc.repec.org/data/femencz.html .

    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.