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Proof of Efficient Liquidity: A Staking Mechanism for Capital Efficient Liquidity

Author

Listed:
  • Arman Abgaryan
  • Utkarsh Sharma
  • Joshua Tobkin

Abstract

The Proof of Efficient Liquidity (PoEL) protocol, designed for specialised Proof of Stake (PoS) consensus-based blockchains that incorporate intrinsic DeFi applications, aims to support sustainable liquidity bootstrapping and network security. This concept seeks to efficiently utilise budgeted staking rewards to attract and sustain liquidity through a risk-structuring engine and incentive allocation strategy, both of which are designed to maximise capital efficiency. The proposed protocol serves the dual objective of: (i) capital creation by attracting risk capital efficiently and maximising its operational utility for intrinsic DeFi applications, thereby asserting sustainability; and (ii) enhancing the adopting blockchain network's economic security by augmenting their staking (PoS) mechanism with a harmonious layer seeking to attract a diversity of digital assets. Finally, the protocol's conceptual framework, as detailed in the appendix, is extended to encompass service fee credits. This extension capitalises on the network's auxiliary services to disperse incentives and attract liquidity, ensuring the network achieves and maintains the critical usage threshold essential for its sustained operational viability and progressive growth.

Suggested Citation

  • Arman Abgaryan & Utkarsh Sharma & Joshua Tobkin, 2024. "Proof of Efficient Liquidity: A Staking Mechanism for Capital Efficient Liquidity," Papers 2401.04521, arXiv.org, revised Feb 2024.
    • Handle: RePEc:arx:papers:2401.04521
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    References listed on IDEAS

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    1. Acerbi, Carlo & Tasche, Dirk, 2002. "On the coherence of expected shortfall," Journal of Banking & Finance, Elsevier, vol. 26(7), pages 1487-1503, July.
    2. Arthur A. B. Pessa & Matjaz Perc & Haroldo V. Ribeiro, 2023. "Age and market capitalization drive large price variations of cryptocurrencies," Papers 2302.12319, arXiv.org.
    3. Menkveld, Albert J. & Wang, Ting, 2013. "How do designated market makers create value for small-caps?," Journal of Financial Markets, Elsevier, vol. 16(3), pages 571-603.
    4. Clapham, Benjamin & Gomber, Peter & Lausen, Jens & Panz, Sven, 2021. "Liquidity provider incentives in fragmented securities markets," Journal of Empirical Finance, Elsevier, vol. 60(C), pages 16-38.
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