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Market Behavior in the Face of Political Violence: Evidence from Tsarist Russia

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  • Christopher A. Hartwell

    (International Management Institute, Department of International Business, ZHAW School of Management and Law, 8400 Winterthur, Switzerland
    Department of International Management, Kozminski University, 03-301 Warsaw, Poland)

Abstract

Even efficient financial markets may break down under periods of prolonged stress, especially when the ramification of an event is unclear. Political violence is such an event, sending immediate signals about possible impact on firm valuations but unclear information about the future viability of existing institutions. This paper examines the effect of political violence in 19th century Russia on its stock market; using a battery of unit root and variance ratio tests, the evidence is that Russian financial markets were mostly efficient in processing short-term information from political violence. However, when violence was at its peak between the assassination of the Tsar in 1881 and the 1905 revolution, large deviations from efficiency can be detected, as markets were unsure about the viability of the existing rules of the game.

Suggested Citation

  • Christopher A. Hartwell, 2021. "Market Behavior in the Face of Political Violence: Evidence from Tsarist Russia," JRFM, MDPI, vol. 14(9), pages 1-13, September.
  • Handle: RePEc:gam:jjrfmx:v:14:y:2021:i:9:p:445-:d:635810
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    References listed on IDEAS

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    1. Lo, Andrew W. & MacKinlay, A. Craig, 1989. "The size and power of the variance ratio test in finite samples : A Monte Carlo investigation," Journal of Econometrics, Elsevier, vol. 40(2), pages 203-238, February.
    2. Zivot, Eric & Andrews, Donald W K, 2002. "Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 25-44, January.
    3. Schwert, G William, 2002. "Tests for Unit Roots: A Monte Carlo Investigation," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 5-17, January.
    4. Anagnostidis, P. & Varsakelis, C. & Emmanouilides, C.J., 2016. "Has the 2008 financial crisis affected stock market efficiency? The case of Eurozone," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 116-128.
    5. Andrew Worthington & Helen Higgs, 2009. "Efficiency in the Australian stock market, 1875-2006: a note on extreme long-run random walk behaviour," Applied Economics Letters, Taylor & Francis Journals, vol. 16(3), pages 301-306.
    6. Ceyda Aktan & Perihan Iren & Tolga Omay, 2019. "Market development and market efficiency: evidence based on nonlinear panel unit root tests," The European Journal of Finance, Taylor & Francis Journals, vol. 25(11), pages 979-993, July.
    7. Chow, K. Victor & Denning, Karen C., 1993. "A simple multiple variance ratio test," Journal of Econometrics, Elsevier, vol. 58(3), pages 385-401, August.
    8. Andrey Ukhov, 2003. "Financial Innovaton and Russian Government Debt Before 1918," Yale School of Management Working Papers ysm390, Yale School of Management.
    9. Mnasri, Ayman & Nechi, Salem, 2016. "Impact of terrorist attacks on stock market volatility in emerging markets," Emerging Markets Review, Elsevier, vol. 28(C), pages 184-202.
    10. Kim, Jae H., 2006. "Wild bootstrapping variance ratio tests," Economics Letters, Elsevier, vol. 92(1), pages 38-43, July.
    11. Philip Bond & Alex Edmans & Itay Goldstein, 2012. "The Real Effects of Financial Markets," Annual Review of Financial Economics, Annual Reviews, vol. 4(1), pages 339-360, October.
    12. Jesús Otero & Jeremy Smith, 2017. "Response surface models for OLS and GLS detrending-based unit-root tests in nonlinear ESTAR models," Stata Journal, StataCorp LP, vol. 17(3), pages 704-722, September.
    13. Kian‐Ping Lim & Robert Brooks, 2011. "The Evolution Of Stock Market Efficiency Over Time: A Survey Of The Empirical Literature," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 69-108, February.
    14. Lee, Chien-Chiang & Lee, Jun-De & Lee, Chi-Chuan, 2010. "Stock prices and the efficient market hypothesis: Evidence from a panel stationary test with structural breaks," Japan and the World Economy, Elsevier, vol. 22(1), pages 49-58, January.
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    Cited by:

    1. Christopher A. Hartwell & Paul M. Vaaler, 2023. "The Price of Empire: Unrest Location and Sovereign Risk in Tsarist Russia," Papers 2309.06885, arXiv.org, revised Nov 2023.

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