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Every major research team starts the day with the same data from the same terminals. ContextQuant adds an automated alert layer that flags companies whose filings changed in ways that historically predict underperformance, before the street has reacted. When a company's risk language becomes materially more specific than prior quarters and more specific than its peers, the system fires an alert with the historical evidence for what happens next.

The alert has a 6-12 month shelf life for risk specificity signals and a 0-30 day window for sentiment signals. Two different time horizons serving the same desk.

The 6.9% average spread between the top and bottom quintiles on risk specificity is directly relevant to a long/short strategy. The sentiment signal provides shorter-horizon positioning intelligence around filing dates. Both operate on public filing data and are uncorrelated with traditional quantitative factors, adding diversification to existing signal libraries.

The system knows when to trust which signal. During high-uncertainty markets, risk specificity is 2.7x more informative. During calm markets, sentiment drift takes over. Dynamic weighting is built into the architecture.

When a borrower's 10-K risk language becomes materially more specific, management is disclosing a concrete threat. If that company is in the loan book, the specificity alert fires months before traditional indicators like rating downgrades, covenant breaches, or CDS spread widening.

The 2023 result demonstrates this directly. During the regional banking stress period, the signal produced its strongest result (t = -3.48, p < 0.01). Companies writing specific risk language about interest rate exposure and deposit concentration were the ones that experienced stress. The information was public, sitting on EDGAR months before the market reacted.

High-net-worth clients are increasingly sophisticated. They have Bloomberg terminals. They read the same research. The retention problem in wealth management is not performance. It is perceived value.

Imagine telling a client: "Your company just filed a 10-K where the risk language became materially more specific than any of the past five years. They added detailed language about regulatory exposure in three markets where they previously used generic disclosures. Historically, when companies make this shift, they underperform their peer group by an average of 6.9% over the following year." That conversation is worth the advisory fee.

Signal weights adjust automatically based on the current macro regime. During tariff escalation or rate transitions, risk specificity signals are upweighted. During calm markets, sentiment drift takes priority. The CRO's dashboard reflects the current environment, not a static model.

When both signals fire together on the same company (high specificity AND deteriorating sentiment), the alert is high-confidence. When neither fires, the system stays quiet. That asymmetry is a feature, not a bug.