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Market inefficiency spillover network across different regimes

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  • Yang, Jie
  • Feng, Yun

Abstract

This study examines risk transmission among 34 stock markets from the perspective of market inefficiency spillover effects. We suggest the use of the hidden Markov model along with the multifractal detrended fluctuation analysis to measure the degree of market efficiency for both bull and bear regimes. Diebold–Yilmaz spillover indices are used to document the asymmetric characteristics of market inefficiency spillovers in bull and bear regimes. When the market crashes or bubbles and the external economic and financial environment worsens, inefficiency spillovers increase significantly.

Suggested Citation

  • Yang, Jie & Feng, Yun, 2023. "Market inefficiency spillover network across different regimes," Finance Research Letters, Elsevier, vol. 58(PC).
  • Handle: RePEc:eee:finlet:v:58:y:2023:i:pc:s1544612323009492
    DOI: 10.1016/j.frl.2023.104577
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    References listed on IDEAS

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    1. Dew-Becker, Ian & Giglio, Stefano & Kelly, Bryan, 2021. "Hedging macroeconomic and financial uncertainty and volatility," Journal of Financial Economics, Elsevier, vol. 142(1), pages 23-45.
    2. Diebold, Francis X. & Yılmaz, Kamil, 2014. "On the network topology of variance decompositions: Measuring the connectedness of financial firms," Journal of Econometrics, Elsevier, vol. 182(1), pages 119-134.
    3. Mert Demirer & Francis X. Diebold & Laura Liu & Kamil Yilmaz, 2018. "Estimating global bank network connectedness," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(1), pages 1-15, January.
    4. Mensi, Walid & Yousaf, Imran & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Asymmetric spillover and network connectedness between gold, BRENT oil and EU subsector markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 76(C).
    5. Lastrapes, William D. & Wiesen, Thomas F.P., 2021. "The joint spillover index," Economic Modelling, Elsevier, vol. 94(C), pages 681-691.
    6. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2016. "Asymmetric connectedness on the U.S. stock market: Bad and good volatility spillovers," Journal of Financial Markets, Elsevier, vol. 27(C), pages 55-78.
    7. Wu, Fei & Zhang, Dayong & Zhang, Zhiwei, 2019. "Connectedness and risk spillovers in China’s stock market: A sectoral analysis," Economic Systems, Elsevier, vol. 43(3).
    8. Searat Ali & Benjamin Liu & Jen Je Su, 2022. "Does corporate governance have a differential effect on downside and upside risk?," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 49(9-10), pages 1642-1695, October.
    9. Lu, Dong & Tang, Huoqing & Zhang, Chengsi, 2023. "China's monetary policy surprises and corporate real investment," China Economic Review, Elsevier, vol. 77(C).
    10. Wang, Yudong & Liu, Li & Gu, Rongbao & Cao, Jianjun & Wang, Haiyan, 2010. "Analysis of market efficiency for the Shanghai stock market over time," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(8), pages 1635-1642.
    11. Mensi, Walid & Vo, Xuan Vinh & Kang, Sang Hoon, 2022. "Upward/downward multifractality and efficiency in metals futures markets: The impacts of financial and oil crises," Resources Policy, Elsevier, vol. 76(C).
    12. Feng, Yun & Yang, Jie & Huang, Qian, 2023. "Multiscale correlation analysis of Sino-US corn futures markets and the impact of international crude oil price: A new perspective from the multifractal method," Finance Research Letters, Elsevier, vol. 53(C).
    13. Kakinaka, Shinji & Umeno, Ken, 2022. "Cryptocurrency market efficiency in short- and long-term horizons during COVID-19: An asymmetric multifractal analysis approach," Finance Research Letters, Elsevier, vol. 46(PA).
    14. Jozef Baruník & Tomáš Křehlík, 2018. "Measuring the Frequency Dynamics of Financial Connectedness and Systemic Risk," Journal of Financial Econometrics, Oxford University Press, vol. 16(2), pages 271-296.
    15. Gu, Rongbao & Zhang, Bing, 2016. "Is efficiency of crude oil market affected by multifractality? Evidence from the WTI crude oil market," Energy Economics, Elsevier, vol. 53(C), pages 151-158.
    16. Cheng, Tingting & Liu, Junli & Yao, Wenying & Zhao, Albert Bo, 2022. "The impact of COVID-19 pandemic on the volatility connectedness network of global stock market," Pacific-Basin Finance Journal, Elsevier, vol. 71(C).
    17. Khan, Khalid & Su, Chi-Wei & Khurshid, Adnan & Umar, Muhammad, 2022. "COVID-19 impact on multifractality of energy prices: Asymmetric multifractality analysis," Energy, Elsevier, vol. 256(C).
    18. Xiang, Youtao & Borjigin, Sumuya, 2023. "Downside and upside risk spillovers between financial industry and real economy based on linear and nonlinear networks," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 1337-1374.
    19. Bahloul, Slah & Khemakhem, Imen, 2021. "Dynamic return and volatility connectedness between commodities and Islamic stock market indices," Resources Policy, Elsevier, vol. 71(C).
    20. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    21. Mensi, Walid & Al Rababa'a, Abdel Razzaq & Vo, Xuan Vinh & Kang, Sang Hoon, 2021. "Asymmetric spillover and network connectedness between crude oil, gold, and Chinese sector stock markets," Energy Economics, Elsevier, vol. 98(C).
    22. Reboredo, Juan C. & Rivera-Castro, Miguel A. & Ugolini, Andrea, 2016. "Downside and upside risk spillovers between exchange rates and stock prices," Journal of Banking & Finance, Elsevier, vol. 62(C), pages 76-96.
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    More about this item

    Keywords

    Market inefficiency spillover; Network connectedness; Multifractal analysis; Market regimes;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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