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Quantile return and volatility connectedness among Non-Fungible Tokens (NFTs) and (un)conventional asset

Author

Listed:
  • Urom, C.
  • Ndubuisi, Gideon

    (RS: GSBE other - not theme-related research, Mt Economic Research Inst on Innov/Techn)

  • Guesmi, K.

Abstract

This paper uses the Quantile Vector-Autoregressive (Q-VAR) connectedness technique to examine the return and volatility connectedness among NFTs and (un)conventional assets including cryptocurrency, energy, technology, equity, precious metals, and fixed income financial assets across three quantiles corresponding to the normal, bearish, and bullish market conditions. It also explores the predictive powers of major macroeconomic and geopolitical indicators on the return and volatility connectedness across these three market conditions using a linear regression model. The main findings are as follows. First, the return and volatility connectedness vary across the market conditions, with the levels during the bearish and bullish market conditions being higher. Second, except under the bullish market condition, the total return connectedness is higher than those of total volatility connectedness. Third, NFTs are, at best, decoupled from (un)conventional assets during the normal market condition. Fourth, NFTs is a net return shock receivers except under the bullish market condition where it is a net transmitters. However, it is a net volatility shock receiver irrespective of the market condition. Fifth, during periods of economic crisis the total return and volatility connectedness rise (decreases) under the normal and bearish (bullish) market conditions. Finally, geopolitical risks, business environment conditions, and market and economic policy uncertainty are important predictors of return and volatility connectedness, although the predictive strength and direction vary across market conditions. We discuss the implications of our findings.

Suggested Citation

  • Urom, C. & Ndubuisi, Gideon & Guesmi, K., 2022. "Quantile return and volatility connectedness among Non-Fungible Tokens (NFTs) and (un)conventional asset," MERIT Working Papers 2022-017, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
  • Handle: RePEc:unm:unumer:2022017
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    References listed on IDEAS

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    1. Urom, Christian & Ndubuisi, Gideon & Guesmi, Khaled, 2022. "Dynamic dependence and predictability between volume and return of Non-Fungible Tokens (NFTs): The roles of market factors and geopolitical risks," Finance Research Letters, Elsevier, vol. 50(C).
    2. Lin, Min-Bin & Wang, Bingling & Bocart, Fabian Y.R.P. & Hafner, Christian M. & Härdle, Wolfgang K., 2022. "DAI Digital Art Index : a robust price index for heterogeneous digital assets," LIDAM Discussion Papers ISBA 2022036, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    3. Ndubuisi, Gideon & Urom, Christian, 2023. "Dependence and risk spillovers among clean cryptocurrencies prices and media environmental attention," Research in International Business and Finance, Elsevier, vol. 65(C).

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    More about this item

    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
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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