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Fancy Bitcoin and conventional financial assets: Measuring market integration based on connectedness networks

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  • Zeng, Ting
  • Yang, Mengying
  • Shen, Yifan

Abstract

We investigate the relationship between Bitcoin and conventional financial assets from a perspective on the connectedness of asset networks. We adopt the method of measuring connectedness proposed by Diebold and Yilmaz (2009, 2012, and 2014) in a VAR system to study the dynamic interdependence between returns in Bitcoin, stocks, oil, and gold. We find that the connectedness between bitcoin and conventional assets is weak. The separation of positive and negative returns in the Bitcoin market shows the existence of an asymmetric pattern of the spillover effects between Bitcoin and conventional assets. A rolling window analysis finds that although Bitcoin prices experience a rising link to other financial assets, the magnitude is proven to be moderate. However, connectedness via negative returns is much stronger than via positive ones and exhibits a clearly increasing trend in recent periods. Our results in application are generally robust to other popular cryptocurrencies, such as ETH and Ripple. The findings presented in this paper have important implications for financial market participants, policymakers, and researchers in light of projected increases in the adoption of Bitcoin, as well as the rapid development of cryptocurrency.

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  • Zeng, Ting & Yang, Mengying & Shen, Yifan, 2020. "Fancy Bitcoin and conventional financial assets: Measuring market integration based on connectedness networks," Economic Modelling, Elsevier, vol. 90(C), pages 209-220.
    • Handle: RePEc:eee:ecmode:v:90:y:2020:i:c:p:209-220
    DOI: 10.1016/j.econmod.2020.05.003
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    More about this item

    Keywords

    Cryptocurrency; Conventional assets; Market integration; Return connectedness networks;
    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
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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