Ciamac C. Moallemi: Research and Publications

Analysis, optimization, and control of stochastic systems; applications in financial engineering, market microstructure, quantitative and algorithmic trading, and blockchain technology.

Podcast appearances:

Ava Labs x CBER Forum (9/2023)
"Loss-Versus-Rebalancing (LVR) at Decentralized Exchanges"
Columbia Bizcast (8/2023)
"Understanding and Unleashing the Power of Blockchain"
Macro Hive Conversations (2/2021)
"On Quant Investing, Machine Learning and Trading Styles"
Bloomberg Odd Lots Podcast (10/2020)
"What It Takes To Win At Quant Investing"

Short briefs that feature some of my work are available here:

Publications by Year of Initial Version

Publications by Topic

2024

[59]

C. C. Moallemi, D. Robinson. Loss-versus-fair: Efficiency of Dutch auctions on blockchains. Working paper. Initial version: May 2024. Revised: July 2024.
[pdf]

[58]

B. Bachu, X. Wan, C. C. Moallemi. Quantifying price improvement in order flow auctions. Working paper. Initial version: April 2024. Revised: May 2024.
[pdf]

[57]

G. Angeris, T. Diamandis, C. C. Moallemi. Multidimensional blockchain fees are (essentially) optimal. Working paper. Initial version: February 2024.
[pdf]

[56]

A. Adams, C. C. Moallemi, S. Reynolds, D. Robinson. am-AMM: An auction-managed automated market maker. In ACM FC 2025: Proceedings of the International Conference on Financial Cryptography and Data Security, forthcoming, February 2024.
[pdf]

2023

[55]

R. Dewey, C. C. Moallemi, A. Brown. Free exchange is not free. Wilmott Magazine, 2023(127), September 2023.
[pdf] [doi]

[54]

D. Crapis, C. C. Moallemi, S. Wang. Optimal dynamic fees for blockchain resources. In ACM FC 2024: Proceedings of the International Conference on Financial Cryptography and Data Security, forthcoming, May 2023.
[pdf]

[53]

J. Milionis, C. C. Moallemi, T. Roughgarden. Automated market making and arbitrage profits in the presence of fees. Working paper. Initial version: February 2023. Revised: May 2023.
[pdf]

2022

[52]

J. Milionis, C. C. Moallemi, T. Roughgarden. A Myersonian framework for optimal liquidity provision in automated market makers. In 15th Innovations in Theoretical Computer Science Conference (ITCS 2024), 2024.
[pdf] [doi]

[51]

J. Milionis, C. C. Moallemi, T. Roughgarden. Complexity-approximation trade-offs in exchange mechanisms: AMMs vs. LOBs. In ACM FC 2023: Proceedings of the International Conference on Financial Cryptography and Data Security, pages 326–343, 2023.
[pdf] [doi]

[50]

J. Milionis, C. C. Moallemi, T. Roughgarden, A. L. Zhang. Automated market making and loss-versus-rebalancing. Working paper. Initial version: August 2022. Revised: May 2024.
[pdf]

Preliminary version:

J. Milionis, C. C. Moallemi, T. Roughgarden, A. L. Zhang. Quantifying loss in automated market making. In DeFi'22: Proceedings of the 2022 ACM CCS Workshop on Decentralized Finance and Security, pages 71–74, November 2022.
[pdf] [doi]

[49]

C. C. Moallemi, U. Patange. Hybrid scheduling with mixed-integer programming at Columbia Business School. INFORMS Journal on Applied Analytics, forthcoming, August 2022.
[pdf] [doi]

[48]

V. F. Farias, C. C. Moallemi, T. Peng, A. T. Zheng. Synthetically controlled bandits. Working paper. Initial version: February 2022. Revised: December 2022.
[pdf]

[47]

S. Min, C. C. Moallemi, C. Maglaras. Risk-sensitive optimal execution via a conditional value-at-risk objective. Working paper. Initial version: January 2022.
[pdf]

2021

[46]

C. C. Moallemi, M. Wang. A reinforcement learning approach to optimal execution. Quantitative Finance, 22(6):1051–1069, March 2022.
[pdf] [doi]

[45]

C. Maglaras, C. C. Moallemi, M. Wang. A deep learning approach to estimating fill probabilities in a limit order book. Quantitative Finance, 22(11):1989–2003, October 2022.
[pdf] [doi]

2020

[44]

S. Min, C. C. Moallemi, D. J. Russo. Policy gradient optimization of Thompson sampling policies. Working paper. Initial version: June 2020. Revised: August 2022.
[pdf]

2019

[43]

R. Dewey, C. C. Moallemi. The unsolved mystery of the Medallion Fund's success. Bloomberg Businessweek, November 2019.
[link]

[42]

S. Min, C. Maglaras, C. C. Moallemi. Thompson sampling with information relaxation penalties. Management Science, forthcoming, February 2022.
[pdf] [online supplement]

Preliminary version:

S. Min, C. Maglaras, C. C. Moallemi. Thompson sampling with information relaxation penalties. In Advances in Neural Information Processing Systems 32, pages 3549–3558, 2019.

[41]

G. Huberman, J. Leshno, C. C. Moallemi. An economist's perspective on the Bitcoin payment system. In American Economic Association Papers and Proceedings, 109:93–96, May 2019.
[pdf] [doi]

2018

[40]

S. Min, C. Maglaras, C. C. Moallemi. Cross-sectional variation of intraday liquidity, cross-impact, and their effect on portfolio execution. Operations Research, 70(2):830–846, March–April 2022.
[pdf] [doi] [online supplement]

2017

[39]

G. Huberman, J. Leshno, C. C. Moallemi. The economics of the Bitcoin payment system. Vox EU, December 2017.
[link]

[38]

G. Huberman, J. Leshno, C. C. Moallemi. Monopoly without a monopolist: An economic analysis of the Bitcoin payment system. The Review of Economic Studies, 88(6):3011–3040, November 2021.
[pdf] [doi]

2016

[37]

C. C. Moallemi, K. Yuan. A model for queue position valuation in a limit order book. Working paper. Initial version: December 2016. Revised: June 2017.
[pdf]

[36]

C. C. Moallemi, K. Yuan. Portfolio liquidity estimation and optimal execution. Working paper. Initial version: December 2016. Revised: August 2019.
[pdf]

2015

[35]

N. Bhat, V. F. Farias, C. C. Moallemi, D. Sinha. Near optimal A-B testing. Management Science, 66(10):4477–4495, October 2020.
[pdf] [doi]

[34]

C. Maglaras, C. C. Moallemi, H. Zheng. Optimal execution in a limit order book and an associated microstructure market impact model. Working paper. Initial version: May 2015.
[pdf]

2014

[33]

O. Besbes, J. M. Chaneton, C. C. Moallemi. The exploration-exploitation tradeoff in the newsvendor problem. Stochastic Systems, 12(4):319–339, December 2022.
[pdf] [doi] [online supplement]

[32]

P. Glasserman, C. C. Moallemi, K. Yuan. Hidden illiquidity with multiple central counterparties. Operations Research, 64(5):1143–1158, September–October 2016.
[pdf] [doi]

[31]

K. Iyer, R. Johari, C. C. Moallemi. Welfare analysis of dark pools. Working paper. Initial version: October 2014. Revised: June 2018.
[pdf]

[30]

C. Chen, G. Iyengar, C. C. Moallemi. Asset price-based contagion models for systemic risk. Working paper. Initial version: October 2014.
[pdf]

[29]

C. C. Moallemi, M. Sağlam, M. Sotiropoulos. Short-term trading skill: An analysis of investor heterogeneity and execution quality. Journal of Financial Markets, 42:1–28, January 2019.
[pdf] [doi]

2013

[28]

P. Collin-Dufresne, K. Daniel, C. C. Moallemi, M. Sağlam. Strategic asset allocation with predictable returns and transaction costs. Working paper. Initial version: August 2013. Revised: June 2015.
[pdf]

2012

[27]

N. Bhat, V. F. Farias, C. C. Moallemi, Andy T. Zheng. Non-parametric approximate dynamic programming via the kernel method. Stochastic Systems, 13(3):321–397, September 2023.
[pdf] [doi]

Preliminary version:

N. Bhat, V. F. Farias, C. C. Moallemi. Non-parametric approximate dynamic programming via the kernel method. In Advances in Neural Information Processing Systems 22, pages 395–403, 2012.

[26]

C. Maglaras, C. C. Moallemi, H. Zheng. Queueing dynamics and state space collapse in fragmented limit order book markets. Operations Research, 69(4):1324–1348, June 2021.
[pdf] [doi]

*Honorable Mention, INFORMS Financial Services Section Student Research Paper Competition, 2012

[25]

C. C. Moallemi, M. Sağlam. Dynamic portfolio choice with linear rebalancing rules. Journal of Financial and Quantitative Analysis, 52(3):1247–1278, June 2017.
[pdf] [doi]

2011

[24]

M. Broadie, Y. Du, C. C. Moallemi. Risk estimation via regression. Operations Research, 63(5):1077–1097, September–October 2015.
[pdf] [doi] [online supplement]

[23]

V. V. Desai, V. F. Farias, C. C. Moallemi. Bounds for Markov decision processes. Chapter in Reinforcement Learning and Approximate Dynamic Programming for Feedback Control (F. L. Lewis, D. Liu, eds.), IEEE Press, pages 452–473, December 2012.
[pdf]

[22]

M. Broadie, Y. Du, C. C. Moallemi. Risk estimation via weighted regression. In Proceedings of the 2011 Winter Simulation Conference, pages 3854–3865, December 2011.
[pdf] [doi]

[21]

C. Chen, G. Iyengar, C. C. Moallemi. An axiomatic approach to systemic risk. Management Science, 56(6):1373–1388, June 2013.
[pdf] [doi]

*Honorable Mention, INFORMS George Nicholson Student Paper Competition, 2011

2010

[20]

V. V. Desai, V. F. Farias, C. C. Moallemi. Pathwise optimization for optimal stopping problems. Management Science, 58(12):2292–2308, December 2012.
[pdf] [doi] [online supplement]

*Best Simulation Publication Award, INFORMS Simulation Society, 2014

[19]

M. Broadie, Y. Du, C. C. Moallemi. Efficient risk estimation via nested sequential simulation. Management Science, 57(6):1172–1194, June 2011.
[pdf] [doi]

[18]

K. Iyer, R. Johari, C. C. Moallemi. Information aggregation and allocative efficiency in smooth markets. Management Science, 60(10):2509–2524, July 2014.
[pdf] [doi]

Preliminary version:

K. Iyer, R. Johari, C. C. Moallemi. Information aggregation in smooth markets. In EC '10: Proceedings of the 11th ACM Conference on Electronic Commerce, pages 199–206, June 2010.
[doi]

2009

[17]

C. C. Moallemi, M. Sağlam. The cost of latency in high-frequency trading. Operations Research, 61(5):1070–1086, September–October 2013.
[pdf] [doi]

*1st Place, INFORMS Financial Services Section Student Research Paper Competition, 2011
Selected for publication in the Operations Research Forum

[16]

C. C. Moallemi, D. Shah. On the flow-level dynamics of a packet-switched network. Working paper. Initial version: November 2009. Revised: October 2012.
[pdf]

Preliminary version:

C. C. Moallemi, D. Shah. On the flow-level dynamics of a packet-switched network. In SIGMETRICS '10: Proceedings of the ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems, pages 83–94, June 2010.
[doi]

[15]

V. V. Desai, V. F. Farias, C. C. Moallemi. Approximate dynamic programming via a smoothed linear program. Operations Research, 60(3):655-674, May–June 2012.
[pdf] [doi]

*1st Place, INFORMS Junior Faculty Paper Competition, 2011

Preliminary version:

V. V. Desai, V. F. Farias, C. C. Moallemi. A smoothed approximate linear program. In Advances in Neural Information Processing Systems 22, pages 459–467, 2009.

2008

[14]

C. C. Moallemi, B. Park, B. Van Roy. Strategic execution in the presence of an uninformed arbitrageur. Journal of Financial Markets, 15(4):361–391, January 2012.
[pdf] [doi]

2007

[13]

C. C. Moallemi. A Message-Passing Paradigm for Optimization. Ph.D. thesis, Stanford University, September 2007.
[pdf]

[12]

V. F. Farias, C. C. Moallemi, B. Van Roy, T. Weissman. Universal reinforcement learning. IEEE Transactions on Information Theory, 56(5):2441–2454, May 2010.
[pdf] [doi]

Preliminary version:

V. F. Farias, C. C. Moallemi, B. Van Roy, T. Weissman. A universal scheme for learning. In Proceedings of the IEEE International Symposium on Information Theory, pages 1158–1162, Adelaide, Australia, September 2005.
[doi]

[11]

C. C. Moallemi, B. Van Roy. Resource allocation via message passing. INFORMS Journal of Computing, 23(2):205–219, Spring 2011.
[pdf] [doi] [online supplement]

[10]

C. C. Moallemi, B. Van Roy. Convergence of min-sum message passing for convex optimization. IEEE Transactions on Information Theory, 56(4):2041–2050, April 2010.
[pdf] [doi]

Preliminary version:

C. C. Moallemi, B. Van Roy. Convergence of the min-sum algorithm for convex optimization. In Proceedings of the 45th Allerton Conference on Communication, Control and Computing, pages 840–847, Monticello, IL, September 2007.

2006

[9]

C. C. Moallemi, B. Van Roy. Convergence of min-sum message passing for quadratic optimization. IEEE Transactions on Information Theory, 55(5):2413–2423, May 2009.
[pdf] [doi]

[8]

C. C. Moallemi, S. Kumar, B. Van Roy. Approximate and data-driven dynamic programming for queueing networks. Working paper. Initial version: December 2006. Revised: January 2013.
[pdf]

2005

[7]

V. F. Farias, C. C. Moallemi, B. Prabhakar. Load balancing with migration penalties. In Proceedings of the IEEE International Symposium on Information Theory, pages 558–562, Adelaide, Australia, September 2005.
[pdf] [doi]

[6]

C. C. Moallemi, B. Van Roy. Consensus propagation. IEEE Transactions on Information Theory, 52(11):4753–4766, November 2006.
[pdf] [doi]

Preliminary version:

C. C. Moallemi, B. Van Roy. Consensus propagation. In Advances in Neural Information Processing Systems 18, MIT Press, pages 899–906, 2006.

2003

[5]

J. M. Johnson, K. Mason, C. C. Moallemi, H. Xi, S. Somaroo, E. Huang. Protein family annotation in a multiple alignment viewer. Bioinformatics, 19(4):544–545, 2003.
[doi]

[4]

C. C. Moallemi, B. Van Roy. Distributed optimization in adaptive networks. In Advances in Neural Information Processing Systems 16, MIT Press, pages 887–894, 2004.
[pdf] [appendix]

Preliminary version:

C. C. Moallemi, B. Van Roy. Decentralized protocols for optimization of sensor networks. In Proceedings of the 42nd Allerton Conference on Communication, Control and Computing, Monticello, IL, September 2003.

[3]

K. Mason, N. M. Patel, A. Ledell, C. C. Moallemi, E. A. Wintner. Mapping protein pockets through their potential small-molecule binding volumes: QSCD applied to biological protein structures. Journal of Computer-Aided Molecular Design, 18(1):55–70, 2004.
[doi]

2000

[2]

E. A. Wintner, C. C. Moallemi. Quantized Surface Complementarity Diversity (QSCD): A model based on small molecule-target complementarity. Journal of Medicinal Chemistry, 43(10):1993–2006, 2000.
[doi]

1991

[1]

C. C. Moallemi. Neural networks in the computer analysis of voided urine cells for bladder cancer. IEEE Expert, 6(6):8–12, December 1991.
[doi]