Areas of engagement
- Quantitative and algorithmic trading. The structure of trading skill, forecasting accuracy versus execution quality, the valuation of trading systems and strategies, and how trading ability is measured.
- Trade secrets and skill portability. Industry norms and standard practices around knowledge and skill transfer when trading professionals move between firms; the distinction between portable general skill and firm-specific or proprietary advantage.
- Market microstructure and execution quality. Transaction-cost analysis, execution-quality measurement, and best execution.
- Market manipulation and informed-trading detection. Statistical detection methodologies and their reliability.
- Prediction markets and terminal-payoff instruments. Binary-settlement and performance-linked securities.
- Retail trading behavior and investor protection.
Engagement applications
Published methodology, datasets, and peer-reviewed findings have direct application to:
- Disputes over quantitative and algorithmic trading personnel, trade secrets, and employee mobility
- Valuation of trading systems and strategies, and the measurement of trading ability
- Transaction-cost analysis, execution-quality measurement, and best-execution review
- Statistical detection of informed trading and market manipulation, and the reliability of detection methodologies
- Market-structure analysis for regulatory rulemaking and comment letters
- Methodology audits for compliance vendors, exchanges, and market-integrity teams
- Prediction-market and terminal-payoff instruments, including binary-settlement and performance-linked securities
Surveillance suite
Eight market-integrity tests are published on the DV-PMI Surveillance Indices page. As of the most recent release, 6 are live (Informed Trading (PII), Insider Timing Concentration, Adverse Selection, Resolution Surprise, Wash Trading (Tier 1), Concentration / Pump Risk) and 2 are in development. 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 versioned methodology changelog (every construction change dated and documented). |
| 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.