The Signal Credibility Index for Prediction Markets: A Microstructure-Grounded Diagnostic with Weighted and Time-Varying Extensions

Maksym Nechepurenko · 2026 · Working Paper

Abstract

Prediction-market price moves are widely treated as informationally equivalent: a price jump is read the same way regardless of whether it reflects durable Bayesian updating, transient liquidity pressure, strategic position adjustment, or genuine disagreement. This paper formalizes the Signal Credibility Index (SCI) introduced in Nechepurenko (2026) as a stand-alone diagnostic. We make four contributions: (i) a revised persistence component using the persistence ratio PR(t, w) on logit prices, well-defined on short rolling windows; (ii) a weighted Cobb-Douglas form SCI^(α) with flow-based concentration HHI^flow; (iii) a time-varying specification SCI(t; w) for real-time monitoring; and (iv) Monte Carlo validation including an out-of-distribution stress test, coordinated multi-wallet manipulation, and a logistic-regression benchmark.

The validation establishes discrimination among designed microstructure regimes, not external evidence of downstream coordination effects. We document two failure modes consistent with the index targeting coordination credibility rather than pure information content: a Type II error on informed-but-concentrated whale repricing, and a Type I error on coordinated multi-wallet manipulation.

Related tracks

Forecasting & AI Microstructure

Cite this work

@misc{nechepurenko2026sci,
  title         = {The Signal Credibility Index for Prediction Markets: A Microstructure-Grounded Diagnostic with Weighted and Time-Varying Extensions},
  author        = {Nechepurenko, Maksym},
  year          = {2026},
  eprint        = {2604.27041},
  archivePrefix = {arXiv},
  primaryClass  = {q-fin.GN},
  url           = {https://arxiv.org/abs/2604.27041},
  doi           = {10.48550/arXiv.2604.27041},
  note          = {SSRN: \url{https://papers.ssrn.com/abstract=6676179}}
}