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All Journal Jurnal Media Computer Science
Al Berlant Ghulam Fania Akhmad
Universitas Negeri Surabaya
Computer Science & IT

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Does CFTC Regulation Reduce Prediction Market Anomalies? A Benford’s Law And DiD Analysis Al Berlant Ghulam Fania Akhmad; Ridka Dhenabayu
Jurnal Media Computer Science Vol 5 No 3 (2026): Juli
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v5i3.11900

Abstract

The rapid growth of prediction markets raises concerns about data integrity and susceptibility to manipulation. This study examines whether Commodity Futures Trading Commission (CFTC) regulation of Polymarket reduces market anomalies measured through Benford's Law conformity. Employing a quasi-experimental nonequivalent control group design with a difference-in-differences (DiD) estimator, the study exploits the CFTC Amended Order of 25 November 2025 as the treatment on Polymarket, with Kalshi (regulated since 2020) as the control group. Daily price and volume data for both platforms were retrieved from Dune Analytics for January 2023–June 2026 (over 1.4 billion observations) and transformed into monthly Mean Absolute Deviation (MAD) per platform per category; the volatility index (VIX) serves as a covariate. DiD estimates on the theoretically valid volume outcome reveal no significant regulatory effect (β = +0.0038; p = 0.073); thus the hypothesis that regulation reduces anomalies is not supported, as Benford conformity was already high and improved on both platforms due to market maturation. Placebo and pre-trends robustness tests confirm the validity of the design. This study constitutes the first Benford–DiD quasi-experimental test in prediction markets.
Co-Authors Ridka Dhenabayu