IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2210.16846.html
   My bibliography  Save this paper

DeFi vs TradFi: Valuation Using Multiples and Discounted Cash Flow

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2210.16846
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Raphael Auer & Bernhard Haslhofer & Stefan Kitzler & Pietro Saggese & Friedhelm Victor, 2024. "The technology of decentralized finance (DeFi)," Digital Finance, Springer, vol. 6(1), pages 55-95, March.
    2. Fernando M. Duarte & Carlo Rosa, 2015. "The equity risk premium: a review of models," Economic Policy Review, Federal Reserve Bank of New York, issue 2, pages 39-57.
    3. Souza, Thiago de Oliveira, 2020. "Dollar carry timing," Discussion Papers on Economics 10/2020, University of Southern Denmark, Department of Economics.
    4. repec:ipg:wpaper:2013-020 is not listed on IDEAS
    5. Leland E. Farmer & Lawrence Schmidt & Allan Timmermann, 2023. "Pockets of Predictability," Journal of Finance, American Finance Association, vol. 78(3), pages 1279-1341, June.
    6. Han, Liyan & Xu, Yang & Yin, Libo, 2018. "Forecasting the CNY-CNH pricing differential: The role of investor attention," Pacific-Basin Finance Journal, Elsevier, vol. 49(C), pages 232-247.
    7. Obaid, Khaled & Pukthuanthong, Kuntara, 2022. "A picture is worth a thousand words: Measuring investor sentiment by combining machine learning and photos from news," Journal of Financial Economics, Elsevier, vol. 144(1), pages 273-297.
    8. Yu, Deshui & Huang, Difang & Chen, Li & Li, Luyang, 2023. "Forecasting dividend growth: The role of adjusted earnings yield," Economic Modelling, Elsevier, vol. 120(C).
    9. Andreou, Panayiotis C. & Kagkadis, Anastasios & Philip, Dennis & Taamouti, Abderrahim, 2019. "The information content of forward moments," Journal of Banking & Finance, Elsevier, vol. 106(C), pages 527-541.
    10. Gonçalo Faria & Fabio Verona, 2016. "Forecasting the equity risk premium with frequency-decomposed predictors," Working Papers de Economia (Economics Working Papers) 06, Católica Porto Business School, Universidade Católica Portuguesa.
    11. Yuan Liao & Xinjie Ma & Andreas Neuhierl & Zhentao Shi, 2023. "Economic Forecasts Using Many Noises," Papers 2312.05593, arXiv.org, revised Dec 2023.
    12. Ian Martin, 2017. "What is the Expected Return on the Market?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(1), pages 367-433.
    13. Back, Kerry & Crotty, Kevin & Kazempour, Seyed Mohammad, 2022. "Validity, tightness, and forecasting power of risk premium bounds," Journal of Financial Economics, Elsevier, vol. 144(3), pages 732-760.
    14. He, Mengxi & Zhang, Yaojie & Wen, Danyan & Wang, Yudong, 2021. "Forecasting crude oil prices: A scaled PCA approach," Energy Economics, Elsevier, vol. 97(C).
    15. João F. Caldeira & Rangan Gupta & Hudson S. Torrent, 2020. "Forecasting U.S. Aggregate Stock Market Excess Return: Do Functional Data Analysis Add Economic Value?," Mathematics, MDPI, vol. 8(11), pages 1-16, November.
    16. Shi, Qi, 2023. "The RP-PCA factors and stock return predictability: An aligned approach," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).
    17. Bennett, Donyetta & Mekelburg, Erik & Strauss, Jack & Williams, T.H., 2024. "Unlocking the black box of sentiment and cryptocurrency: What, which, why, when and how?," Global Finance Journal, Elsevier, vol. 60(C).
    18. Gupta, Rangan & Hammoudeh, Shawkat & Modise, Mampho P. & Nguyen, Duc Khuong, 2014. "Can economic uncertainty, financial stress and consumer sentiments predict U.S. equity premium?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 33(C), pages 367-378.
    19. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
    20. Boudoukh, Jacob & Israel, Ronen & Richardson, Matthew, 2022. "Biases in long-horizon predictive regressions," Journal of Financial Economics, Elsevier, vol. 145(3), pages 937-969.
    21. Kelly, Bryan & Pruitt, Seth, 2015. "The three-pass regression filter: A new approach to forecasting using many predictors," Journal of Econometrics, Elsevier, vol. 186(2), pages 294-316.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2210.16846. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.