Implied Yields in Liquid Restaking: An Empirical Decomposition of Market-Implied Risk and Reward Premia

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Abstract Liquid Restaking Tokens (LRTs) allow users to secure multiple Actively Validated Services (AVSs) simultaneously, offering higher rewards to compensate for additional risk. These rewards often include illiquid, intangible assets like points from loyalty programs, making their true yield difficult to observe directly. For the first time, the emergence of yield futures markets, such as those on Pendle, enables the observation of market-implied forward yields for these complex instruments. While prior work has linked implied yield to aggregate proxies like Total Value Locked (TVL), the specific risk and reward components driving these premiums remain underexplored. We address this gap by constructing and analyzing a market-implied LRT premium spread, benchmarked against a more mature Liquid Staking Token (LST) for matched tenors. Our empirical analysis across various LRTs, chains, and maturities reveals systematic patterns in this spread, which we argue represents the market's aggregate pricing of both future rewards (e.g., anticipated airdrops) and compensation for a spectrum of risks, including correlated AVS slashing and LRT depegging. By dissecting this spread, our work provides a granular understanding of LRT risk-reward profiles and establishes an empirical foundation for future theoretical models designed to quantify these individual components. JEL Classification: G12 , C58 , D81
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Implied Yields in Liquid Restaking: An Empirical Decomposition of Market-Implied Risk and Reward Premia | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Implied Yields in Liquid Restaking: An Empirical Decomposition of Market-Implied Risk and Reward Premia Faris Chaudhry This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7411925/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 19 Dec, 2025 Read the published version in Digital Finance → Version 1 posted 9 You are reading this latest preprint version Abstract Liquid Restaking Tokens (LRTs) allow users to secure multiple Actively Validated Services (AVSs) simultaneously, offering higher rewards to compensate for additional risk. These rewards often include illiquid, intangible assets like points from loyalty programs, making their true yield difficult to observe directly. For the first time, the emergence of yield futures markets, such as those on Pendle, enables the observation of market-implied forward yields for these complex instruments. While prior work has linked implied yield to aggregate proxies like Total Value Locked (TVL), the specific risk and reward components driving these premiums remain underexplored. We address this gap by constructing and analyzing a market-implied LRT premium spread, benchmarked against a more mature Liquid Staking Token (LST) for matched tenors. Our empirical analysis across various LRTs, chains, and maturities reveals systematic patterns in this spread, which we argue represents the market's aggregate pricing of both future rewards (e.g., anticipated airdrops) and compensation for a spectrum of risks, including correlated AVS slashing and LRT depegging. By dissecting this spread, our work provides a granular understanding of LRT risk-reward profiles and establishes an empirical foundation for future theoretical models designed to quantify these individual components. JEL Classification: G12 , C58 , D81 Decentralized Finance Asset Pricing Yield Dynamics Liquid Restaking Risk Premia FinTech Full Text Additional Declarations Competing interest reported. Faris Chaudhry is an employee of Balyasny Asset Management. The views expressed in this article are solely his own and do not represent the views or opinions of Balyasny Asset Management. This research was conducted independently by the author in his personal academic capacity. The author's role at the firm is not related to cryptocurrency research or trading. Cite Share Download PDF Status: Published Journal Publication published 19 Dec, 2025 Read the published version in Digital Finance → Version 1 posted Editorial decision: Revision requested 14 Oct, 2025 Reviews received at journal 14 Oct, 2025 Reviews received at journal 24 Sep, 2025 Reviewers agreed at journal 28 Aug, 2025 Reviewers agreed at journal 28 Aug, 2025 Reviewers invited by journal 28 Aug, 2025 Editor assigned by journal 21 Aug, 2025 Submission checks completed at journal 20 Aug, 2025 First submitted to journal 19 Aug, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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