Cem Peker's Resarch Homepage

I'm a postdoctoral researcher at New York University Abu Dhabi. My research uses quantitative methods and AI tools to study individual and collective judgments, with applications in Behavioral Economics and Wisdom of the Crowd.

I'm on the job market for 2025-2026. My job market paper investigates the efficiency of information aggregation in markets. I analyze data from an online betting community, and show that self-reported picks can predict outcomes beyond market odds. Furthermore, I find that LLMs can simulate such informative picks! So, "silicon crowds" have wisdom beyond markets as well.

My CV is available here. You can contact me at cem.peker@nyu.edu 

Job market paper

• Can we improve market forecasts with community predictions? Evidence from betting markets (Working paper)

Publications

• Peker, C., & Wilkening, T. (2025). Robust recalibration of aggregate probability forecasts using meta-beliefs. International Journal of Forecasting, 41 (2), 613-630. https://doi.org/10.1016/j.ijforecast.2024.09.005

• Peker, C. (2024). Incentives for self-extremized expert judgments to alleviate the shared-information problem. Decision, 11 (1), 150172. https://doi.org/10.1037/dec0000198

• Peker, C. (2023). Extracting the collective wisdom in probabilistic judgments. Theory and Decision, 94 (3), 467-501. https://doi.org/10.1007/s11238-022-09899-4

Work in Progress

• Peer betting to elicit unverifiable information (joint with Aurélien Baillon and Sophie van der Zee) (Working paper)

• Optimal linear aggregation of correlated expert judgments (Under review, Working paper)

• Expert decisions under pressure: Evidence from professional tennis (joint with John Wooders) (Abstract)

• How many experts should you consult? Optimal stopping using peer predictions (Abstract)

• Using prediction interval skewness to improve forecast accuracy (joint with Yael Grushka-Cockayne, Victor R.R. Jose, Jacob Rittich and Jack Soll) (Abstract)