Watch Insiders

Watch Insiders

Watch Insiders is a data-analysis platform built atop the publicly available stream of SEC Form 4 filings that corporate insiders must submit when they trade their own company's stock. Drawing on academic work by Nejat Seyhun at the University of Michigan — who documented that insider purchases tend to outperform the broad market by 8.9% over twelve months while insider sales tend to underperform by 5.4% — the service structures alerts around user-defined watchlists and pattern detection. The product is not a fund or an advisory firm; it is a subscription software tool. The platform's analytical architecture is built to reduce the noise inherent in daily SEC filing flows. Thousands of forms arrive each day, and Watch Insiders stores them, then applies proprietary algorithms to isolate clusters of trades by C-level executives within compressed time windows, which the firm views as stronger directional signals. The subscription tiers — a free Basic tier, a $14/month Premium tier with expanded screening, and a $19/month Pro tier promising advanced pattern detection and data overlays — are designed for self-directed investors rather than institutional capital-allocators. The service has no disclosed direct investment or co-investment activity. The company discloses no named principals, headcount, founding year, or geographic footprint on its public-facing pages. Its contact presence is limited to standard web-based authentication and registration flows, and there is no evidence of a LinkedIn organizational presence. No adjacent investment vehicles, family-office structures, or philanthropic arms are mentioned. Recent activity: No verifiable operational event from the prior 24 months has been published. Structurally, Watch Insiders differentiates by operating at the intersection of academic financial research and consumer SaaS, with no claim to managing third-party capital or providing bespoke investment counsel. The platform's value proposition is entirely dependent on the persistent predictive signal that Seyhun identified — a proposition that faces the same degradation risks as any widely disseminated factor.