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Volatility Spillovers and Correlation Between Cryptocurrencies and Asian Equity Market

Author

Listed:
  • Nidhi Malhotra

    (Lal Bahadur Shastri Institute of Management, Sector-11, Dwarka, New Delhi, India)

  • Saumya Gupta

    (PGDM (Finance) Student, Lal Bahadur Shastri Institute of Management, Sector-11, Dwarka, New Delhi, India)

Abstract

Although, the growth in the cryptocurrency market slowed down after the meteoric rise in late 2017, the market is still enjoying steady capital inflow. This has made the study of market dynamics between the cryptocurrencies and equity market indispensable. In this paper, the study of the volatility spillovers and correlation between the two has been undertaken by considering five Asian stock indices and four cryptocurrencies ranging from November 2014 to December 2018, to cover three phenomena-Leverage effect, Volatility spillovers and Time varying correlation using EGARCH, Diagonal BEKK and DCC tests respectively. Firstly, the EGARCH test reveals the absence of leverage effect in the returns of cryptocurrenices. Secondly, the multivariate GARCH test shows, out of all the cryptocurrencies taken, the past innovations in Bitcoin affect the future volatility of the equity market returns the most. Lastly, the DCC model reveals evidence of time varying correlation between the markets and Bitcoin.

Suggested Citation

  • Nidhi Malhotra & Saumya Gupta, 2019. "Volatility Spillovers and Correlation Between Cryptocurrencies and Asian Equity Market," International Journal of Economics and Financial Issues, International Journal of Economics and Financial Issues, vol. 9(6), pages 208-215.
    • Handle: RePEc:eco:journ1:2019-06-26
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    References listed on IDEAS

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    Citations

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    Cited by:

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    2. Umar, Muhammad & Rizvi, Syed Kumail Abbas & Naqvi, Bushra, 2021. "Dance with the devil? The nexus of fourth industrial revolution, technological financial products and volatility spillovers in global financial system," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    3. Balcilar, Mehmet & Ozdemir, Huseyin & Agan, Busra, 2022. "Effects of COVID-19 on cryptocurrency and emerging market connectedness: Empirical evidence from quantile, frequency, and lasso networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    4. Cong Gu & Benfu Lv & Ying Liu & Geng Peng, 2021. "The Impact of Quantitative Easing on Cryptocurrency," International Journal of Economics and Financial Issues, International Journal of Economics and Financial Issues, vol. 11(4), pages 27-34.
    5. Yasmine Snene Manzli & Naif Alsagr & Ahmed Jeribi, 2026. "Testing safe haven properties of digital and financial assets: wavelet coherence insights from G7 banking sector indices during crises," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 13(1), pages 1-15, December.

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    More about this item

    Keywords

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    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • 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

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