Every score on InsiderTrack is explainable. Here is exactly how we calculate trade confidence, buy/sell signals, and what each component measures.
Competitors charge significant monthly fees for black-box AI scores with no explanation of how they are calculated. We believe if you are making investment decisions based on a score, you should know exactly how it is derived.
Every component on this page maps directly to the scoring code running in production. The weights shown are the actual weights used. Nothing is hidden.
Not investment advice. Scores are informational tools derived from public data. Past signal performance does not guarantee future results.
The scoring model incorporates findings from academic research on insider trading patterns:
All scores run from 0 to 1 and share the same label thresholds throughout the app:
| Label | Range | Meaning |
|---|---|---|
| Strong | 0.75 and above | High-conviction signal with multiple corroborating factors |
| Good | 0.55 to 0.74 | Solid signal worth attention |
| Moderate | 0.35 to 0.54 | Some evidence but limited corroboration |
| Weak | Below 0.35 | Insufficient evidence or low-quality signal |
Each confirmed trade receives a confidence score from 0 to 1, computed from 14 weighted components that sum to a maximum of 1.0.
| Component | Max weight | What it measures |
|---|---|---|
| Inference | 0.20 | LLM extraction confidence, weighted by source reliability. SEC filings receive the highest multiplier; social media posts receive lower weights. |
| Evidence Count | 0.15 | Number of corroborating source documents. Saturates at 2 sources. |
| Discussion Sentiment | 0.15 | Ratio of positive to negative social discussion. Decays with signal age. |
| Cross-Connector Diversity | 0.15 | Number of distinct data sources (SEC, Reddit, HackerNews) mentioning the trade. Decays with signal age. |
| Trade Significance | 0.18 | Composite of transaction value tier, insider seniority, and ownership change magnitude. Rewards large, meaningful trades by senior insiders. |
| Corroboration | 0.10 | Logarithmic scale of cross-source mentions. Saturates around 8 mentions to prevent viral posts from overwhelming the score. |
| Keyword Signal | 0.10 | NLP-extracted trading signal strength from post text. Decays over 24 hours. |
| Transaction Scale | 0.08 | Dollar value tier: under $25K (low), $25K to $100K (moderate), $100K to $500K (notable), $500K to $2M (significant), $2M+ (exceptional). |
| Transaction Type | 0.08 | SEC Form 4 transaction code. Open-market purchases (P) score highest; tax withholding sales (F) and dispositions (D) score lowest. |
| Insider Title | 0.08 | Role seniority: CEO and President score highest, Directors score moderately, 10% owners score lower. |
| Source Context | 0.08 | Completeness of extracted data fields: source URL (0.03), trade date (0.02), insider name (0.02), company name (0.01). |
| Ownership Change | 0.07 | Percentage change in the insider's total holdings. A 10% position change signals higher conviction than a 0.1% change. |
| Filing Timeliness | 0.05 | Days between trade and SEC filing. 2 days or fewer scores the maximum; 30+ days scores zero. |
| Direct Ownership | 0.04 | Flat bonus for directly held shares. Derivative positions (options, RSUs) score zero on this component. |
Components that incorporate social signals (keyword, sentiment, cross-connector diversity) use exponential temporal decay with a 24-hour half-life. A Reddit discussion from 3 days ago contributes approximately 12% of its original signal weight.
The buy/sell signal measures directional conviction. It answers: how strong is the evidence that this insider is bullish or bearish on their own company?
| Component | Max weight | Description |
|---|---|---|
| Price Follow-Through | 0.34 | The largest single component. Did the stock price move in the expected direction after the trade? Centered at 0% return (neutral = 0.5). Buys need upward price movement; sells need downward movement. |
| Filing Timeliness | 0.14 | Same formula as trade confidence: faster filings indicate more deliberate trades. |
| Action Bias | 0.12 buy / 0.07 sell | Buys start with a higher base weight than sells. Insider purchases are rarer and historically more informative than sales, which can be driven by diversification or liquidity needs. |
| Transaction Scale | 0.09 | Same dollar-value tier system as trade confidence. |
| Ownership Change | 0.08 | Percentage change in the insider's holdings after the trade. |
| Transaction Type | 0.08 | SEC transaction code quality (P, S, A, M, F, D). |
| Insider Title | 0.05 | Role seniority of the filing insider. |
| Cross-Connector Diversity | 0.03 | Number of distinct data sources corroborating this trade. Decays with signal age. |
| Cluster Support | multiplier | 1.0x for a solo insider trade, scaling up to 1.5x when 4 or more insiders at the same company trade in the same direction within a window. Applied multiplicatively to the full base score. |
Cluster support is multiplicative, not additive. When multiple insiders at the same company trade in the same direction, the entire signal is amplified rather than having a flat bonus added. A solo trade scoring 0.60 with 4 concurrent cluster insiders becomes 0.90 (0.60 x 1.5).
Every company badge and every insider badge shows a directional signal in the range -1 to +1. Positive means net buying; negative means net selling; values near zero are mixed. We look at the last 180 days of open-market trades only, then weight each trade three ways before averaging: a 60-day half-life on recency, a square-root taper on dollar size, and the trade's own confidence score. Awards, option exercises, tax-withholding sales, 10b5-1 plan trades, and zero-notional entries are excluded because they reflect compensation mechanics rather than conviction.
On a company badge, the input is every insider's recent trade in that company; the hover tooltip names the insiders pushing the signal hardest. On an insider badge, the input is that insider's recent trades across every company they file on; the hover tooltip names the companies pushing the signal hardest. The formula is the same — only the trade set changes.
The number is a strength reading, not a probability. A signal of +0.42 means the buy side outweighed the sell side by a wide margin across recent activity. Hover any badge for the breakdown.
Why not a simple buy / sell count? Compensation events often produce many same-day rows (an option exercise plus the tax-withholding sale, for instance). Counting raw rows lets routine mechanics outvote a single conviction trade. Weighting by size and recency, and excluding non-discretionary categories, puts the badge back in line with the question users actually ask: are insiders buying or selling, on purpose, recently?
We also score insider identity confidence to ensure the person behind each trade is correctly resolved. This uses 11 components including role verification, trade history, alias matching, and cross-source corroboration. Low-confidence insiders are flagged for manual review and excluded from high-confidence signal feeds.
Each insider page shows a historical win rate and average return at three horizons (30, 90, and 180 days) computed from their own trades. Here is exactly what those numbers mean.
Caveat. The track record is descriptive, not predictive. Executives who sell on 10b5-1 plans into a rising stock will mechanically show a low sell-side win rate — that is the nature of programmatic selling, not a bad call. Treat the number as one signal among many, not as alpha attribution.
SEC filings are the primary source and receive the highest reliability multiplier in scoring. Social media signals are useful for corroboration and timing context but receive lower base weights and are subject to temporal decay.
This methodology is versioned (currently Trade Confidence v2.1.0, Buy/Sell Signal v2.0.0) and evolves as we incorporate new research and data sources. Score versions are stored alongside each computed score so historical data remains interpretable.
Questions about the scoring model can be sent to support@insidertrack.app.