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DeFi vs TradFi: Valuation Using Multiples and Discounted Cash Flow

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  • Teng Andrea Xu
  • Jiahua Xu
  • Kristof Lommers

Abstract

As of August 2022, blockchain-based assets boast a combined market capitalisation exceeding one trillion USD, among which the most prominent are the decentralised autonomous organisation (DAO) tokens associated with decentralised finance (DeFi) protocols. In this work, we seek to value DeFi tokens using the canonical multiples and Discount Cash Flow (DCF) approaches. We examine a subset of DeFi services including decentralised exchanges (DEXs), protocol for loanable funds (PLFs), and yield aggregators. We apply the same analysis to some publicly traded firms and compare them with DeFi tokens of the analogous category. Interestingly, despite the crypto bear market lasting for more than one year as of August 2022, both approaches evidence overvaluation in DeFi.

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  • Teng Andrea Xu & Jiahua Xu & Kristof Lommers, 2022. "DeFi vs TradFi: Valuation Using Multiples and Discounted Cash Flow," Papers 2210.16846, arXiv.org.
    • Handle: RePEc:arx:papers:2210.16846
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    References listed on IDEAS

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    1. Damodaran, Aswath, 2007. "Valuation Approaches and Metrics: A Survey of the Theory and Evidence," Foundations and Trends(R) in Finance, now publishers, vol. 1(8), pages 693-784, April.
    2. Ivo Welch & Amit Goyal, 2008. "A Comprehensive Look at The Empirical Performance of Equity Premium Prediction," The Review of Financial Studies, Society for Financial Studies, vol. 21(4), pages 1455-1508, July.
    3. Simon Cousaert & Jiahua Xu & Toshiko Matsui, 2021. "SoK: Yield Aggregators in DeFi," Papers 2105.13891, arXiv.org, revised Mar 2022.
    4. Bryan Kelly & Seth Pruitt, 2013. "Market Expectations in the Cross-Section of Present Values," Journal of Finance, American Finance Association, vol. 68(5), pages 1721-1756, October.
    5. Teng Andrea Xu & Jiahua Xu, 2022. "A Short Survey on Business Models of Decentralized Finance (DeFi) Protocols," Papers 2202.07742, arXiv.org, revised Jul 2023.
    6. Florian Steiger, 2010. "The Validity of Company Valuation Using Discounted Cash Flow Methods," Papers 1003.4881, arXiv.org, revised Apr 2010.
    7. Shanaev, Savva & Sharma, Satish & Ghimire, Binam & Shuraeva, Arina, 2020. "Taming the blockchain beast? Regulatory implications for the cryptocurrency Market," Research in International Business and Finance, Elsevier, vol. 51(C).
    8. Jing Liu & Doron Nissim & Jacob Thomas, 2002. "Equity Valuation Using Multiples," Journal of Accounting Research, Wiley Blackwell, vol. 40(1), pages 135-172, March.
    9. Lewis Gudgeon & Sam M. Werner & Daniel Perez & William J. Knottenbelt, 2020. "DeFi Protocols for Loanable Funds: Interest Rates, Liquidity and Market Efficiency," Papers 2006.13922, arXiv.org, revised Oct 2020.
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    Cited by:

    1. Andry Alamsyah & Gede Natha Wijaya Kusuma & Dian Puteri Ramadhani, 2024. "A Review on Decentralized Finance Ecosystems," Future Internet, MDPI, vol. 16(3), pages 1-29, February.
    2. Şoiman, Florentina & Dumas, Jean-Guillaume & Jimenez-Garces, Sonia, 2023. "What drives DeFi market returns?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).

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