← Home

Bibliography

The literature behind each mechanism. A machine-readable version lives in research/bibliography.bib.

The conceptual spine is the survey Novel Statistical and Market-Inspired Mechanisms for the Elicitation, Aggregation, and Rewarding of Predictive Contributions (PDF); many entries below are drawn from its works-cited.

Proper scoring rules & distributional forecasting

• Brier, G. W. (1950). “Verification of Forecasts Expressed in Terms of Probability.” Monthly Weather Review 78(1).
• Good, I. J. (1952). “Rational Decisions.” JRSS-B 14(1).
• Savage, L. J. (1971). “Elicitation of Personal Probabilities and Expectations.” JASA 66(336).
• Matheson, J. & Winkler, R. (1976). “Scoring Rules for Continuous Probability Distributions.” Management Science 22(10).
• Schervish, M. (1989). “A General Method for Comparing Probability Assessors.” Annals of Statistics 17(4).
• Gneiting, T. & Raftery, A. E. (2007). “Strictly Proper Scoring Rules, Prediction, and Estimation.” JASA 102(477).
• Székely, G. & Rizzo, M. (2013). “Energy Statistics: A Class of Statistics Based on Distances.” J. Stat. Planning & Inference 143(8).

Market scoring rules & cost-function makers

• Hanson, R. (2003). “Combinatorial Information Market Design.” Information Systems Frontiers 5(1).
• Hanson, R. (2007). “Logarithmic Market Scoring Rules for Modular Combinatorial Information Aggregation.” J. Prediction Markets 1(1).
• Abernethy, J., Chen, Y. & Wortman Vaughan, J. (2013). “Efficient Market Making via Convex Optimization, and a Connection to Online Learning.” ACM TEAC 1(2).
• Othman, A., Pennock, D., Reeves, D. & Sandholm, T. (2013). “A Practical Liquidity-Sensitive Automated Market Maker.” ACM TEAC 1(3).

Parimutuel & dynamic parimutuel markets

• Thaler, R. & Ziemba, W. (1988). “Anomalies: Parimutuel Betting Markets.” J. Economic Perspectives 2(2).
• Pennock, D. (2004). “A Dynamic Pari-Mutuel Market for Hedging, Wagering, and Information Aggregation.” ACM EC'04.
• Lange, J. & Economides, N. (2005). “A Parimutuel Market Microstructure for Contingent Claims.” European Financial Management 11(1).
• Snowberg, E. & Wolfers, J. (2010). “Explaining the Favorite–Long Shot Bias.” JPE 118(4).

Automated market makers & DeFi

• Angeris, G., Kao, H.-T., Chiang, R., Noyes, C. & Chitra, T. (2021). “An Analysis of Uniswap Markets.” Cryptoeconomic Systems (arXiv:1911.03380).
• Angeris, G. & Chitra, T. (2020). “Improved Price Oracles: Constant Function Market Makers.” ACM AFT.
• Adams, H. et al. (2021). “Uniswap v3 Core.” Uniswap whitepaper.
• Milionis, J., Moallemi, C., Roughgarden, T. & Zhang, A. L. (2022). “Automated Market Making and Loss-Versus-Rebalancing” (arXiv:2208.06046).
• Moallemi, C. & Robinson, D. (2024). “pm-AMM: A Uniform AMM for Prediction Markets.” Paradigm (Nov 5, 2024).
• Chitra, T., Diamandis, T., Sheng, N., Sterle, L. & Yusubov, K. (2025). “Perpetual Demand Lending Pools” (arXiv:2502.06028). PDF

Order books, continuous double auctions & batch auctions

• Smith, V. (1962). “An Experimental Study of Competitive Market Behavior.” JPE 70(2).
• Gode, D. & Sunder, S. (1993). “Allocative Efficiency of Markets with Zero-Intelligence Traders.” JPE 101(1).
• Gjerstad, S. & Dickhaut, J. (1998). “Price Formation in Double Auctions.” Games and Economic Behavior 22(1).
• Budish, E., Cramton, P. & Shim, J. (2015). “The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response.” QJE 130(4).

Perpetual futures

• Shiller, R. J. (1993). “Measuring Asset Values for Cash Settlement in Derivative Markets: Hedonic Repeated Measures Indices and Perpetual Futures.” J. Finance 48(3).
• BitMEX. “Perpetual Contracts Guide” / “Funding” / “Fair Price Marking.”

Peer prediction (no ground truth)

• Prelec, D. (2004). “A Bayesian Truth Serum for Subjective Data.” Science 306.
• Shnayder, V., Agarwal, A., Frongillo, R. & Parkes, D. (2016). “Informed Truthfulness in Multi-Task Peer Prediction” (Correlated Agreement).

Forecast aggregation

• Genest, C. & Zidek, J. (1986). “Combining Probability Distributions: A Critique and an Annotated Bibliography.” Statistical Science 1(1).
• Wang, X., Kulkarni, S. et al. (2011). “Aggregating Large Sets of Probabilistic Forecasts by Weighted Coherent Adjustment.”

Microprediction & distributional crowdsourcing

• Cotton, P. (2022). Microprediction: Building an Open AI Network. MIT Press.
• Cotton, P. monteprediction.com — sample-based multivariate forecasting scored by the energy score.
• microprediction. github.com/microprediction — the open prediction network.

Working on a related mechanism or implementation? Open an issue on the mechanisms repo and it will be added.