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NFTs Emergence in Financial Markets and their Correlation with DeFis and Cryptocurrencies

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  • Khuloud M. Alawadhi
  • Nour Alshamali

Abstract

Non-fungible tokens (NFT) have been defined as digital assets that encode items such as art, collectables, and in-game goods. They are often stored in smart contracts on a blockchain and are exchanged online, frequently using Bitcoin. As NFT became increasingly popular in the last few years, decentralized financial assets (DeFi) tokens also started receiving growing attention as financial instruments that differ from NFTs and cryptocurrencies. Based on data on NFTs, DeFi tokens, and cryptocurrency daily prices between January 15th and December 6th, 2021, we examine the correlation between NFTs, DeFi tokens and major cryptocurrencies such as Bitcoin and Ethereum. Using the volatility spillover matrix approach by Diebold and Yilmaz (2012) as applied by Dowling (2021) and including DeFis into the discussion, we find that there is very limited spillover to and from non-traditional financial markets. Also, DeFi assets appear to be relatively unconnected to cryptocurrency markets. Following the methodology by Karim, Lucey, Naeem and Uddin (2021) of the quantile connectedness approach and the cross-quantilogram model of Han, Linton, Oka and Whang (2016), we determine that positive DeFi and Crypto spillovers exceeded negative NFT spillovers. This paper concludes that both NFTs and DeFi assets show significant potential in terms of portfolio diversification since they display low correlation with cryptocurrencies, especially in the case of DeFis thanks to it being disconnected from other assets in the market, based on this year's data. This has significant implications for investors who seek to diversify their portfolios by including cryptocurrency, NFTs and DeFis as assets.

Suggested Citation

  • Khuloud M. Alawadhi & Nour Alshamali, 2022. "NFTs Emergence in Financial Markets and their Correlation with DeFis and Cryptocurrencies," Applied Economics and Finance, Redfame publishing, vol. 9(1), pages 108-120, December.
    • Handle: RePEc:rfa:aefjnl:v:9:y:2022:i:1:p:108-120
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    References listed on IDEAS

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    1. Claeys, Peter & Vašíček, Bořek, 2014. "Measuring bilateral spillover and testing contagion on sovereign bond markets in Europe," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 151-165.
    2. Han, Heejoon & Linton, Oliver & Oka, Tatsushi & Whang, Yoon-Jae, 2016. "The cross-quantilogram: Measuring quantile dependence and testing directional predictability between time series," Journal of Econometrics, Elsevier, vol. 193(1), pages 251-270.
    3. 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.
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    Cited by:

    1. Wael Hemrit & Noureddine Benlagha & Racha Ben Arous & Mounira Ben Arab, 2023. "Exploring the time‐frequency connectedness among non‐fungible tokens and developed stock markets," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 30(4), pages 192-207, October.

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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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