Areas of expertise
- Informed-trading detection in prediction markets (microstructure-grounded, Daubert-ready)
- Reference-price formation, disposition effects, retail behavior
- Execution quality and maker-taker dynamics (theta-epsilon decomposition)
- Prediction-market regulatory surveillance and market-design review
- Probability weighting, behavioral asset pricing, cross-market spillover analysis
Engagement applications
The detection framework, dataset, and methodology have direct application to:
- Statistical surveillance methodologies for prediction markets and binary-event contracts
- Microstructure-based detection of informed trading
- Market-structure analysis for regulatory rulemaking and comment letters
- Calibration and probability-weighting analysis in field markets
- Expert testimony in matters involving forensic data analytics on prediction-market trade data
- Methodology audits for compliance vendors, exchanges, and market-integrity teams
- Academic collaborations and consulting on market-design research
Surveillance suite
Eight market-integrity tests are published on the DV-PMI Surveillance Indices page. Four are live as of the most recent release (informed trading, insider timing, adverse selection, resolution surprise); four are in development (wash trading, matched orders, marking the close, concentration). Each index is reported as a pattern consistent with the named conduct rather than a legal conclusion, and each maps onto the Rule 702 factors below. Three classic FINRA tests (spoofing, layering, quote stuffing) require order-book and cancellation data that the on-chain trade record does not contain; they are listed on the surveillance page as not feasible rather than approximated.
Methodology and Daubert mapping
The detection framework is designed to map cleanly onto the four Rule 702 factors.
| Factor | How this work satisfies it |
|---|---|
| Testable | Formal null hypothesis (theta-epsilon orthogonality). The test statistic is recomputable from public data. |
| Known error rate | Permutation-validated false positive rate. Holm-Bonferroni and BH-FDR corrections reported. |
| Peer review | Documented in working papers and the published record; reproducible pipelines and pre-registered methodology log. |
| General acceptance | Built from Kyle (1985), Glosten-Milgrom (1985), Fama (1972), and Anand et al. (2012) primitives. |
Affiliations and disclosures
Joshua Della Vedova is an Associate Professor of Finance at the Knauss School of Business, University of San Diego. No financial interest in Polymarket, Kalshi, or any prediction-market venue. Consulting and expert-witness work is undertaken under institutional conflict-of-interest review.
Inquiries
Inquiries about consulting or expert-witness work are welcome by email at jdellavedova@sandiego.edu. A short note with the following three items helps me respond quickly:
- A one-line description of the matter (no privileged detail).
- Approximate timeline.
- Names of parties involved (for a standard conflict check).
Typical response within 2 business days. No engagement exists until a written engagement letter is signed.