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An intra-cryptocurrency analysis of volatility connectedness and its determinants: Evidence from mining coins, non-mining coins and tokens

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  • Charfeddine, Lanouar
  • Benlagha, Noureddine
  • Khediri, Karim Ben

Abstract

This paper analysis the dynamic of the volatility connectedness between three main categories of the cryptocurrency market (mineable coins, non-mineable coins and tokens).11The list four mining coins considered in this study contains Bitcoin (BTC), Ethereum (ETH), Litecoin (LTC) and DASH (DASH), the four non-mining coins are Ripple (XRP), EOS (EOS), Binance coin (BNB), and Stellar (XLM)), and the list of four tokens includes Maker (MKR), Basic Attention (BAT), Chainlink (LINK), Augur (REP)). Furthermore, it investigates factors (internal and external) that can help to predict the net directional and total volatility connectedness indices. We find that the CC market is highly connected where mining coins dominate the CC market and are typically net transmitter of shocks. For the non-mining coins, a low connectedness with all mining coins and tokens versus a high connectedness with Stellar are highlighted. The results show also that, unlike previous studies, Ethereum is the dominant contributor to volatility spillover and the only CC net pairwise transmitter in our sample. Interestingly, we find that most of the tokens are highly connected with their platform (Ethereum) rather than bitcoin. Finally, we find that both financial and macroeconomic indicators play an important role in explaining the total and net directional connectedness, a result that can significantly help cryptocurrency market participants and investors improve their risk management and the benefits from diversification.

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  • Charfeddine, Lanouar & Benlagha, Noureddine & Khediri, Karim Ben, 2022. "An intra-cryptocurrency analysis of volatility connectedness and its determinants: Evidence from mining coins, non-mining coins and tokens," Research in International Business and Finance, Elsevier, vol. 62(C).
    • Handle: RePEc:eee:riibaf:v:62:y:2022:i:c:s0275531922000873
    DOI: 10.1016/j.ribaf.2022.101699
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    Cited by:

    1. Lin Li, 2023. "Investigating risk assessment in post-pandemic household cryptocurrency investments: an explainable machine learning approach," Journal of Asset Management, Palgrave Macmillan, vol. 24(4), pages 255-267, July.

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    More about this item

    Keywords

    Mineable coins; Non-mineable coins; Tokens; Connectedness; Economic fundamentals; Financial factors;
    All these keywords.

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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