IDEAS home Printed from https://ideas.repec.org/b/cvv/eslbks/978-605-2132-47-0.html

Impact of the Crises on the Efficiency of the Financial Market: Evidence from the SDM

Author

Listed:
  • Bachar Fakhry

    (University of Bedfordshire, United Kingdom)

Abstract

The efficient market hypothesis has been around since 1962, the theory based on a simple rule that states the price of any asset must fully reflect all available information. Yet there is empirical evidence suggesting that markets are too volatile to be efficient. In essence, this evidence seems to suggest that the reaction of the market participants to the information or events that is the crucial factor, rather than the actual information. This highlights the need to include the behavioural finance theory in the pricing of assets. Essentially, the research aims to analyse the efficiency of six key sovereign debt markets during a period of changing volatility including the recent global financial and sovereign debt crises. We analyse the markets in the pre-crisis period and during the financial and sovereign debt crises to determine the impact of the crises on the efficiency of these financial markets. We use two GARCH-based variance bound tests to test the null hypothesis of the market being too volatile to be efficient. Proposing a GJR-GARCH variant of the variance bound test to account for variation in the asymmetrical effect. This leads to an analysis of the changing behaviour of price volatility to identify what makes the market efficient or inefficient. In general, our EMH tests resulted in mixed results, hinting at the acceptance of the null hypothesis of the market being too volatile to be efficient. However, interestingly a number of 2017 observations under both models seem to be hinting at the rejection of the null hypothesis. Furthermore, our proposed GJR-GARCH variant of the variance bound test seems to be more likely to accept the EMH than the GARCH variant of the test.

Suggested Citation

  • Bachar Fakhry, 2018. "Impact of the Crises on the Efficiency of the Financial Market: Evidence from the SDM," EconSciences Library Books, EconSciences Library Books, edition 1, number 978-605-2132-47-0.
  • Handle: RePEc:cvv:eslbks:978-605-2132-47-0
    as

    Download full text from publisher

    File URL: https://econsciences.com/wp-content/uploads/2023/02/978-605-2132-47-0.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dahlquist, Magnus & Gray, Stephen F., 2000. "Regime-switching and interest rates in the European monetary system," Journal of International Economics, Elsevier, vol. 50(2), pages 399-419, April.
    2. 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.
    3. Barberis, Nicholas & Shleifer, Andrei & Vishny, Robert, 1998. "A model of investor sentiment," Journal of Financial Economics, Elsevier, vol. 49(3), pages 307-343, September.
    4. Olivier J. Blanchard & Mark W. Watson, 1982. "Bubbles, Rational Expectations and Financial Markets," NBER Working Papers 0945, National Bureau of Economic Research, Inc.
    5. Tauchen, George E & Pitts, Mark, 1983. "The Price Variability-Volume Relationship on Speculative Markets," Econometrica, Econometric Society, vol. 51(2), pages 485-505, March.
    6. Glaeser, Edward L. & Gyourko, Joseph & Saiz, Albert, 2008. "Housing supply and housing bubbles," Journal of Urban Economics, Elsevier, vol. 64(2), pages 198-217, September.
    7. Philipp Mohl & David Sondermann, 2013. "Has political communication during the crisis impacted sovereign bond spreads in the euro area?," Applied Economics Letters, Taylor & Francis Journals, vol. 20(1), pages 48-61, January.
    8. Adrian Blundell-Wignall & Patrick Slovik, 2011. "A Market Perspective on the European Sovereign Debt and Banking Crisis," OECD Journal: Financial Market Trends, OECD Publishing, vol. 2010(2), pages 9-36.
    9. Krolzig, H., 1996. "Statistical Analysis of Cointegrated VAR Processes with Markovian Regime Shifts," SFB 373 Discussion Papers 1996,25, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    10. Barro, Robert J & Gordon, David B, 1983. "A Positive Theory of Monetary Policy in a Natural Rate Model," Journal of Political Economy, University of Chicago Press, vol. 91(4), pages 589-610, August.
    11. Barberis, Nicholas & Thaler, Richard, 2003. "A survey of behavioral finance," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 18, pages 1053-1128, Elsevier.
    12. Peter C. B. Phillips & Shu-Ping Shi & Jun Yu, 2011. "Testing for Multiple Bubbles," Working Papers CoFie-03-2011, Singapore Management University, Sim Kee Boon Institute for Financial Economics.
    13. Rabemananjara, R & Zakoian, J M, 1993. "Threshold Arch Models and Asymmetries in Volatility," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(1), pages 31-49, Jan.-Marc.
    14. Hans-Martin Krolzig, 2000. "Predicting Markov-Switching Vector Autoregressive Processes," Economics Series Working Papers 2000-W31, University of Oxford, Department of Economics.
    15. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    16. Hamilton, James D & Gang, Lin, 1996. "Stock Market Volatility and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 573-593, Sept.-Oct.
    17. Donald W. K. Andrews, 2003. "Tests for Parameter Instability and Structural Change with Unknown Change Point: A Corrigendum," Econometrica, Econometric Society, vol. 71(1), pages 395-397, January.
    18. Ricardo J. Caballero & Arvind Krishnamurthy, 2008. "Collective Risk Management in a Flight to Quality Episode," Journal of Finance, American Finance Association, vol. 63(5), pages 2195-2230, October.
    19. Shin, Hyun Song, 2008. "Risk and liquidity in a system context," Journal of Financial Intermediation, Elsevier, vol. 17(3), pages 315-329, July.
    20. Cai, Jun, 1994. "A Markov Model of Switching-Regime ARCH," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 309-316, July.
    21. Dungey, Mardi & McKenzie, Michael & Tambakis, Demosthenes N., 2009. "Flight-to-quality and asymmetric volatility responses in US Treasuries," Global Finance Journal, Elsevier, vol. 19(3), pages 252-267.
    22. Cosslett, Stephen R. & Lee, Lung-Fei, 1985. "Serial correlation in latent discrete variable models," Journal of Econometrics, Elsevier, vol. 27(1), pages 79-97, January.
    23. repec:bla:jfinan:v:53:y:1998:i:6:p:1839-1885 is not listed on IDEAS
    24. Kenneth D. West, 1987. "A Specification Test for Speculative Bubbles," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 102(3), pages 553-580.
    25. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, Department of Economics and Business Economics, Aarhus University.
    26. Benigno, Gianluca & Benigno, Pierpaolo, 2006. "Designing targeting rules for international monetary policy cooperation," Journal of Monetary Economics, Elsevier, vol. 53(3), pages 473-506, April.
    27. Kon S. Lai & Michael Lai, 1991. "A cointegration test for market efficiency," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 11(5), pages 567-575, October.
    28. Michael Woodford, 2007. "The Case for Forecast Targeting as a Monetary Policy Strategy," Journal of Economic Perspectives, American Economic Association, vol. 21(4), pages 3-24, Fall.
    29. Zakoian, Jean-Michel, 1994. "Threshold heteroskedastic models," Journal of Economic Dynamics and Control, Elsevier, vol. 18(5), pages 931-955, September.
    30. Philip R. Lane, 2012. "The European Sovereign Debt Crisis," Journal of Economic Perspectives, American Economic Association, vol. 26(3), pages 49-68, Summer.
    31. Poterba, James M. & Summers, Lawrence H., 1988. "Mean reversion in stock prices : Evidence and Implications," Journal of Financial Economics, Elsevier, vol. 22(1), pages 27-59, October.
    32. 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.
    33. Stefan Collignon & Piero Esposito & Hanna Lierse, 2013. "European Sovereign Bailouts, Political Risk And The Economic Consequences Of Mrs. Merkel," Journal of International Commerce, Economics and Policy (JICEP), World Scientific Publishing Co. Pte. Ltd., vol. 4(02), pages 1-25.
    34. Gabriele Galati & Kostas Tsatsaronis, 2003. "The impact of the euro on Europe's financial markets," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 12(3), pages 165-222, August.
    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. Bachar FAKHRY, 2020. "The Covid-19 pandemic uncertainty behavioural factor model," Turkish Economic Review, EconSciences Journals, vol. 7(4), pages 214-265, December.

    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. Boswijk, H. Peter & Hommes, Cars H. & Manzan, Sebastiano, 2007. "Behavioral heterogeneity in stock prices," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1938-1970, June.
    2. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    3. 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).
      • 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).
    4. Dettoni, Robinson & Gil-Alana, Luis A. & Bahamondes, Cliff, 2025. "Analyzing rational speculative bubbles in S&P 500 index sectors through fractional integration and generalized link-based additive survival models," Finance Research Letters, Elsevier, vol. 85(PB).
    5. Timo Teräsvirta, 2009. "An Introduction to Univariate GARCH Models," Springer Books, in: Thomas Mikosch & Jens-Peter Kreiß & Richard A. Davis & Torben Gustav Andersen (ed.), Handbook of Financial Time Series, chapter 1, pages 17-42, Springer.
    6. Zhang, Michael Yuanjie & Russell, Jeffrey R. & Tsay, Ruey S., 2001. "A nonlinear autoregressive conditional duration model with applications to financial transaction data," Journal of Econometrics, Elsevier, vol. 104(1), pages 179-207, August.
    7. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    8. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    9. Nick James & Max Menzies, 2023. "Collective dynamics, diversification and optimal portfolio construction for cryptocurrencies," Papers 2304.08902, arXiv.org, revised Jun 2023.
    10. PERRON, Benoît, 1999. "Jumps in the Volatility of Financial Markets," Cahiers de recherche 9912, Universite de Montreal, Departement de sciences economiques.
    11. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [euro;]36.18, Hardback, ISBN 0-521-770416-0, $90, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    12. Degiannakis, Stavros & Xekalaki, Evdokia, 2004. "Autoregressive Conditional Heteroskedasticity (ARCH) Models: A Review," MPRA Paper 80487, University Library of Munich, Germany.
    13. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    14. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415.
    15. Kyriazis, Nikolaos & Papadamou, Stephanos & Corbet, Shaen, 2020. "A systematic review of the bubble dynamics of cryptocurrency prices," Research in International Business and Finance, Elsevier, vol. 54(C).
    16. Shekar Bose & Hafizur Rahman, 2022. "Are News Effects Necessarily Asymmetric? Evidence from Bangladesh Stock Market," SAGE Open, , vol. 12(4), pages 21582440221, October.
    17. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2006. "Volatility and Correlation Forecasting," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 15, pages 777-878, Elsevier.
    18. Taipalus, Katja, 2012. "Detecting asset price bubbles with time-series methods," Scientific Monographs, Bank of Finland, number 2012_047.
    19. Taipalus, Katja, 2012. "Detecting asset price bubbles with time-series methods," Bank of Finland Scientific Monographs, Bank of Finland, volume 0, number sm2012_047, December.
    20. Dettoni, Robinson & Gil-Alana, Luis A. & Yaya, OlaOluwa S., 2024. "Stock market prices and Dividends in the US: Bubbles or Long-run equilibria relationships?," International Review of Financial Analysis, Elsevier, vol. 94(C).

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • Q01 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Sustainable Development
    • O44 - Economic Development, Innovation, Technological Change, and Growth - - Economic Growth and Aggregate Productivity - - - Environment and Growth

    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:cvv:eslbks:978-605-2132-47-0. 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: Bilal KARGI (email available below). General contact details of provider: http://econsciences.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.