13 quantitative models.
Zero black boxes.
8-signal z-score aggregation with per-signal Bayesian conviction weighting. Equal-weight outperforms optimized per research.
Mod-Z + ECOD + CUSUM + COPOD with 2/4 consensus voting. Dramatically reduces false positives vs single-detector approaches.
Gaussian HMM 3-state volatility classification with Kalman-filtered transitions. Calm, transitional, and stressed regimes.
Latent state estimation with confidence bands. A widening confidence interval signals degraded data coverage, not a change in health.
Three steps.
Every weekday morning.
Numbers that
speak for themselves.
Academic foundations.
Peer-reviewed models.
Every model in Sentinel is grounded in published research. No proprietary black boxes.
Li et al., "ECOD" (IEEE TKDE 2022). Adams & MacKay, "Bayesian Online Changepoint Detection" (2007). Modified Z-score with MAD.
Hamilton (1989) on regime-switching. Nystrup et al., "HMM for Financial Regime Detection." Kalman (1960).
Cohen, Malloy & Pomorski, "Decoding Inside Information" (JF 2012). Opportunistic vs routine classification.
Cohen, Malloy & Nguyen, "Lazy Prices" (JF 2020). Loughran-McDonald sentiment. Araci, "FinBERT" (2019).
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Research
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- Up to 10 companies
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- 13 quantitative models
- 21 data sources
- No API access
- No webhook alerts
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- Everything in Research
- Signal provenance chain
- Confidence intervals
- Interactive dashboard
- API access (JSON)
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- Everything in Pro
- Custom company universe
- Dedicated support
- SLA guarantee
- On-premise option
- Custom integrations
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