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Ciamac Moallemi

Ciamac Moallemi

· Professor of Business

Columbia University · Decision Sciences and Operations

Active 1991–2026

h-index27
Citations2.3k
Papers9534 last 5y
Funding$230k

Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.

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Research topics

  • Computer Science
  • Finance
  • Machine Learning
  • Economics
  • Artificial Intelligence
  • Microeconomics
  • Business
  • Econometrics
  • Monetary economics
  • Statistics

Selected publications

  • Monopoly without a Monopolist: An Economic Analysis of the Bitcoin Payment System

    The Review of Economic Studies · 2021 · 233 citations

    Senior authorCorresponding

    Abstract Bitcoin provides its users with transaction-processing services which are similar to those of traditional payment systems. This article models the novel economic structure implied by Bitcoin’s innovative decentralized design, which allows the payment system to be reliably operated by unrelated parties called miners. We find that this decentralized design protects users from monopoly pricing. Competition among service providers within the platform and free entry imply no entity can profi…

  • Automated Market Making and Loss-Versus-Rebalancing

    arXiv (Cornell University) · 2022 · 55 citations

    We consider the market microstructure of automated market makers (AMMs) from the perspective of liquidity providers (LPs). Our central contribution is a ``Black-Scholes formula for AMMs''. We identify the main adverse selection cost incurred by LPs, which we call ``loss-versus-rebalancing'' (LVR, pronounced ``lever''). LVR captures costs incurred by AMM LPs due to stale prices that are picked off by better informed arbitrageurs. We derive closed-form expressions for LVR applicable to all automat…

  • Near-Optimal A-B Testing

    Management Science · 2020 · 45 citations

    We consider the problem of A-B testing when the impact of the treatment is marred by a large number of covariates. Randomization can be highly inefficient in such settings, and thus we consider the problem of optimally allocating test subjects to either treatment with a view to maximizing the precision of our estimate of the treatment effect. Our main contribution is a tractable algorithm for this problem in the online setting, where subjects arrive, and must be assigned, sequentially, with cova…

  • Automated Market Making and Arbitrage Profits in the Presence of Fees

    arXiv (Cornell University) · 2023-05-24 · 16 citations

    preprintOpen access

    We consider the impact of trading fees on the profits of arbitrageurs trading against an automated market maker (AMM) or, equivalently, on the adverse selection incurred by liquidity providers (LPs) due to arbitrage. We extend the model of Milionis et al. [2022] for a general class of two asset AMMs to introduce both fees and discrete Poisson block generation times. In our setting, we are able to compute the expected instantaneous rate of arbitrage profit in closed form. When the fees are low, i…

  • Complexity-Approximation Trade-Offs in Exchange Mechanisms: AMMs vs. LOBs

    Lecture notes in computer science · 2023-11-30 · 13 citations

    book-chapterCorresponding

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