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Documents authored by Moallemi, Ciamac C.

Document
Extended Abstract
DOI: 10.4230/LIPIcs.AFT.2026.14
Uniform-Loss Automated Market Making for Prediction Markets (Extended Abstract)

Authors: Ciamac C. Moallemi, Dan Robinson, and Brian Zhu

Published in: LIPIcs, Volume 395, 8th Conference on Advances in Financial Technologies (AFT 2026)

Abstract
Automated market makers (AMMs) for prediction markets descend from market scoring rules, where a mechanism operator subsidizes a market to aggregate beliefs about uncertain events. The existing literature has focused on bounding the total worst-case loss to the subsidizer, but has not addressed how that loss is distributed across price states or over time. We use the framework of loss-versus-rebalancing (LVR) to study this distribution and introduce uniform AMMs, defined by the property that instantaneous LVR is proportional to pool value and independent of the current token price. In a static setting, we show that for a broad class of win-martingales - processes that converge to 0 or 1 at a fixed resolution time - there exists a pricing function that achieves uniform LVR under that process, and conversely, that any sufficiently regular pricing function induces a win-martingale under which it is uniform. We then extend the framework to dynamic liquidity management, showing that liquidity levels can be adjusted over time to implement a prescribed target expected cumulative loss schedule. This theory is illustrated with canonical examples of win-martingales and pricing functions. Our results can inform AMM designers and liquidity providers on how the inevitable cost of subsidizing price discovery can be shaped and controlled across both price and time.
Cite as

Ciamac C. Moallemi, Dan Robinson, and Brian Zhu. Uniform-Loss Automated Market Making for Prediction Markets (Extended Abstract). In 8th Conference on Advances in Financial Technologies (AFT 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 395, pp. 14:1-14:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{moallemi_et_al:LIPIcs.AFT.2026.14,
  author =	{Moallemi, Ciamac C. and Robinson, Dan and Zhu, Brian},
  title =	{{Uniform-Loss Automated Market Making for Prediction Markets}},
  booktitle =	{8th Conference on Advances in Financial Technologies (AFT 2026)},
  pages =	{14:1--14:3},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-451-2},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{395},
  editor =	{Kiayias, Aggelos and Kyropoulou, Maria},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.AFT.2026.14},
  URN =		{urn:nbn:de:0030-drops-278684},
  doi =		{10.4230/LIPIcs.AFT.2026.14},
  annote =	{Keywords: Prediction markets, automated market makers, loss-versus-rebalancing, win-martingales, liquidity provision}
}
Document
Extended Abstract
DOI: 10.4230/LIPIcs.AFT.2026.36
Who Loses and Why? Market Microstructure of Perpetual Futures (Extended Abstract)

Authors: Ruizhe Jia, Ciamac C. Moallemi, Shouqiao Wang, and Xinmeng Zeng

Published in: LIPIcs, Volume 395, 8th Conference on Advances in Financial Technologies (AFT 2026)

Abstract
This extended abstract summarizes the essence of [Ruizhe Jia et al., 2026], which asks who loses money in perpetual-futures trading, and why. We study Hyperliquid, a leading decentralized perpetual-futures venue, using the complete on-chain record of orders and trades from March 27, 2025 through June 30, 2026 for its ten most actively traded contracts. We classify wallets into algorithmic market makers, front-end traders, and algorithmic takers; front-end traders trade manually through the venue’s interface, and we interpret them as predominantly retail. For each group we then measure profit and loss trade by trade, valuing every trade against the midprice two hours later and subtracting the fees paid. On this measure front-end traders lose 1.11billion, market makers gain $208 million, and algorithmic takers approximately break even. Three channels carry the transfer and account for the whole of it. The first is voluntary trading. Front-end traders demand immediacy, placing large aggressive orders whose size scales little with displayed liquidity, and so pay the highest execution costs; favorable post-trade price movement and maker income offset part of that cost. The second is forced exits. Leverage converts adverse price moves into forced liquidations, which exit at prices far worse than any voluntary trade, and auto-deleveraging returns only part of the loss. The third is fees. Front-end traders cross the spread on most of their volume and sit in the highest-fee tiers, and so pay most of the venue’s fees. Post-trade price impact is organized by trade purpose, though group differences persist within each purpose category. These results identify immediacy, forced exits, and fees as the principal channels of wealth transfer in decentralized perpetual-futures markets.
Cite as

Ruizhe Jia, Ciamac C. Moallemi, Shouqiao Wang, and Xinmeng Zeng. Who Loses and Why? Market Microstructure of Perpetual Futures (Extended Abstract). In 8th Conference on Advances in Financial Technologies (AFT 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 395, pp. 36:1-36:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{jia_et_al:LIPIcs.AFT.2026.36,
  author =	{Jia, Ruizhe and Moallemi, Ciamac C. and Wang, Shouqiao and Zeng, Xinmeng},
  title =	{{Who Loses and Why? Market Microstructure of Perpetual Futures}},
  booktitle =	{8th Conference on Advances in Financial Technologies (AFT 2026)},
  pages =	{36:1--36:3},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-451-2},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{395},
  editor =	{Kiayias, Aggelos and Kyropoulou, Maria},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.AFT.2026.36},
  URN =		{urn:nbn:de:0030-drops-278900},
  doi =		{10.4230/LIPIcs.AFT.2026.36},
  annote =	{Keywords: Perpetual futures, cryptocurrency derivatives, decentralized exchanges, on-chain data, retail trading, market microstructure, execution costs, liquidations}
}
Document
DOI: 10.4230/LIPIcs.AFT.2024.18
Loss-Versus-Fair: Efficiency of Dutch Auctions on Blockchains

Authors: Ciamac C. Moallemi and Dan Robinson

Published in: LIPIcs, Volume 316, 6th Conference on Advances in Financial Technologies (AFT 2024)

Abstract
Milionis et al. (2023) studied the rate at which automated market makers leak value to arbitrageurs when block times are discrete and follow a Poisson process, and where the risky asset price follows a geometric Brownian motion. We extend their model to analyze another popular mechanism in decentralized finance for onchain trading: Dutch auctions. We compute the expected losses that a seller incurs to arbitrageurs and expected time-to-fill for Dutch auctions as a function of starting price, volatility, decay rate, and average interblock time. We also extend the analysis to gradual Dutch auctions, a variation on Dutch auctions for selling tokens over time at a continuous rate. We use these models to explore the tradeoff between speed of execution and quality of execution, which could help inform practitioners in setting parameters for starting price and decay rate on Dutch auctions, or help platform designers determine performance parameters like block times.
Cite as

Ciamac C. Moallemi and Dan Robinson. Loss-Versus-Fair: Efficiency of Dutch Auctions on Blockchains. In 6th Conference on Advances in Financial Technologies (AFT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 316, pp. 18:1-18:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{moallemi_et_al:LIPIcs.AFT.2024.18,
  author =	{Moallemi, Ciamac C. and Robinson, Dan},
  title =	{{Loss-Versus-Fair: Efficiency of Dutch Auctions on Blockchains}},
  booktitle =	{6th Conference on Advances in Financial Technologies (AFT 2024)},
  pages =	{18:1--18:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-345-4},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{316},
  editor =	{B\"{o}hme, Rainer and Kiffer, Lucianna},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.AFT.2024.18},
  URN =		{urn:nbn:de:0030-drops-209541},
  doi =		{10.4230/LIPIcs.AFT.2024.18},
  annote =	{Keywords: Dutch auctions, blockchain, decentralized finance}
}
Document
DOI: 10.4230/LIPIcs.ITCS.2024.81
A Myersonian Framework for Optimal Liquidity Provision in Automated Market Makers

Authors: Jason Milionis, Ciamac C. Moallemi, and Tim Roughgarden

Published in: LIPIcs, Volume 287, 15th Innovations in Theoretical Computer Science Conference (ITCS 2024)

Abstract
In decentralized finance ("DeFi"), automated market makers (AMMs) enable traders to programmatically exchange one asset for another. Such trades are enabled by the assets deposited by liquidity providers (LPs). The goal of this paper is to characterize and interpret the optimal (i.e., profit-maximizing) strategy of a monopolist liquidity provider, as a function of that LP’s beliefs about asset prices and trader behavior. We introduce a general framework for reasoning about AMMs based on a Bayesian-like belief inference framework, where LPs maintain an asset price estimate, which is updated by incorporating traders' price estimates. In this model, the market maker (i.e., LP) chooses a demand curve that specifies the quantity of a risky asset to be held at each dollar price. Traders arrive sequentially and submit a price bid that can be interpreted as their estimate of the risky asset price; the AMM responds to this submitted bid with an allocation of the risky asset to the trader, a payment that the trader must pay, and a revised internal estimate for the true asset price. We define an incentive-compatible (IC) AMM as one in which a trader’s optimal strategy is to submit its true estimate of the asset price, and characterize the IC AMMs as those with downward-sloping demand curves and payments defined by a formula familiar from Myerson’s optimal auction theory. We generalize Myerson’s virtual values, and characterize the profit-maximizing IC AMM. The optimal demand curve generally has a jump that can be interpreted as a "bid-ask spread," which we show is caused by a combination of adverse selection risk (dominant when the degree of information asymmetry is large) and monopoly pricing (dominant when asymmetry is small). This work opens up new research directions into the study of automated exchange mechanisms from the lens of optimal auction theory and iterative belief inference, using tools of theoretical computer science in a novel way.
Cite as

Jason Milionis, Ciamac C. Moallemi, and Tim Roughgarden. A Myersonian Framework for Optimal Liquidity Provision in Automated Market Makers. In 15th Innovations in Theoretical Computer Science Conference (ITCS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 287, pp. 81:1-81:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{milionis_et_al:LIPIcs.ITCS.2024.81,
  author =	{Milionis, Jason and Moallemi, Ciamac C. and Roughgarden, Tim},
  title =	{{A Myersonian Framework for Optimal Liquidity Provision in Automated Market Makers}},
  booktitle =	{15th Innovations in Theoretical Computer Science Conference (ITCS 2024)},
  pages =	{81:1--81:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-309-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{287},
  editor =	{Guruswami, Venkatesan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2024.81},
  URN =		{urn:nbn:de:0030-drops-196094},
  doi =		{10.4230/LIPIcs.ITCS.2024.81},
  annote =	{Keywords: Posted-Price Mechanisms, Asset Exchange, Market Making, Automated Market Makers (AMMs), Blockchains, Decentralized Finance, Incentive Compatibility, Optimization}
}

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