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Stock index pegging and extreme markets

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  • Dong, Xinyue
  • Ma, Rong
  • Li, Honggang

Abstract

In this paper, we design a multi-agent model to explore endogenous mechanisms that create extremes in stock markets. This study will show that when making trading decisions, if the changing trends of a stock index are taken into consideration, several stylized facts, including synchronized behavior, increased downside correlations and the leverage effect, are reproducible in the model. If reversed, these facts prove the reliability of our assumption of the microscopic mechanism in the model. We finally conclude that a market drop causes synchronized behavior and further market drops. In other words, the stock index not only represents and describes a general market assessment but can also affect market sentiment and change future market trends.

Suggested Citation

  • Dong, Xinyue & Ma, Rong & Li, Honggang, 2019. "Stock index pegging and extreme markets," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 13-21.
    • Handle: RePEc:eee:finana:v:64:y:2019:i:c:p:13-21
    DOI: 10.1016/j.irfa.2019.04.012
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    1. Stephen Morris & Hyun Song Shin, 2004. "Liquidity Black Holes," Review of Finance, European Finance Association, vol. 8(1), pages 1-18.
    2. Markus Brunnermeier & Gary Gorton & Arvind Krishnamurthy, 2013. "Liquidity Mismatch Measurement," NBER Chapters, in: Risk Topography: Systemic Risk and Macro Modeling, pages 99-112, National Bureau of Economic Research, Inc.
    3. Siegel, Jeremy J, 1992. "Equity Risk Premia, Corporate Profit Forecasts, and Investor Sentiment around the Stock Crash of October 1987," The Journal of Business, University of Chicago Press, vol. 65(4), pages 557-570, October.
    4. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233, Elsevier.
    5. Tesfatsion, Leigh S., 2002. "Agent-Based Computational Economics: Growing Economies from the Bottom Up," Staff General Research Papers Archive 5075, Iowa State University, Department of Economics.
    6. Robert J. Shiller, 1988. "Portfolio Insurance and Other Investor Fashions as Factors in the 1987 Stock Market Crash," NBER Chapters, in: NBER Macroeconomics Annual 1988, Volume 3, pages 287-297, National Bureau of Economic Research, Inc.
    7. Ken C. Yook, 2003. "Larger Return to Cash Acquisitions: Signaling Effect or Leverage Effect?," The Journal of Business, University of Chicago Press, vol. 76(3), pages 477-498, July.
    8. Mark A. Carlson, 2006. "A brief history of the 1987 stock market crash with a discussion of the Federal Reserve response," Finance and Economics Discussion Series 2007-13, Board of Governors of the Federal Reserve System (U.S.).
    9. Itzhak Ben‐David & Francesco Franzoni & Rabih Moussawi, 2018. "Do ETFs Increase Volatility?," Journal of Finance, American Finance Association, vol. 73(6), pages 2471-2535, December.
    10. Lee, Wayne Y. & Jiang, Christine X. & Indro, Daniel C., 2002. "Stock market volatility, excess returns, and the role of investor sentiment," Journal of Banking & Finance, Elsevier, vol. 26(12), pages 2277-2299.
    11. Robert J. Shiller, 1987. "Investor Behavior in the October 1987 Stock Market Crash: Survey Evidence," NBER Working Papers 2446, National Bureau of Economic Research, Inc.
    12. Yeh, Yin-Hua & Lee, Tsun-Siou, 2000. "The interaction and volatility asymmetry of unexpected returns in the greater China stock markets," Global Finance Journal, Elsevier, vol. 11(1-2), pages 129-149.
    13. Chiarella, Carl & He, Xue-Zhong & Pellizzari, Paolo, 2012. "A Dynamic Analysis Of The Microstructure Of Moving Average Rules In A Double Auction Market," Macroeconomic Dynamics, Cambridge University Press, vol. 16(4), pages 556-575, September.
    14. Ma, Rong & Zhang, Yin & Li, Honggang, 2017. "Traders’ behavioral coupling and market phase transition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 618-627.
    15. Mr. Sunil Sharma & Sushil Bikhchandani, 2000. "Herd Behavior in Financial Markets: A Review," IMF Working Papers 2000/048, International Monetary Fund.
    16. Jacklin, Charles J & Kleidon, Allan W & Pfleiderer, Paul, 1992. "Underestimation of Portfolio Insurance and the Crash of October 1987," The Review of Financial Studies, Society for Financial Studies, vol. 5(1), pages 35-63.
    17. repec:bla:jfinan:v:44:y:1989:i:4:p:827-48 is not listed on IDEAS
    18. Tim Bollerslev & Julia Litvinova & George Tauchen, 2006. "Leverage and Volatility Feedback Effects in High-Frequency Data," Journal of Financial Econometrics, Oxford University Press, vol. 4(3), pages 353-384.
    19. Heikki Lehkonen, 2015. "Stock Market Integration and the Global Financial Crisis," Review of Finance, European Finance Association, vol. 19(5), pages 2039-2094.
    20. Jean-Philippe Bouchaud & Andrew Matacz & Marc Potters, 2001. "The leverage effect in financial markets: retarded volatility and market panic," Science & Finance (CFM) working paper archive 0101120, Science & Finance, Capital Fund Management.
    21. Li, Qi & Yang, Jian & Hsiao, Cheng & Chang, Young-Jae, 2005. "The relationship between stock returns and volatility in international stock markets," Journal of Empirical Finance, Elsevier, vol. 12(5), pages 650-665, December.
    22. Christie, Andrew A., 1982. "The stochastic behavior of common stock variances : Value, leverage and interest rate effects," Journal of Financial Economics, Elsevier, vol. 10(4), pages 407-432, December.
    23. Kofman, Paul & Koedijk, Kees & Campbell, Rachel, 2002. "Increased Correlation in Bear markets: A Downside Risk Perspective," CEPR Discussion Papers 3172, C.E.P.R. Discussion Papers.
    24. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-896, July.
    25. Zhang, Ting & Li, Honggang, 2013. "Buying on margin, selling short in an agent-based market model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(18), pages 4075-4082.
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