Seeking Alpha alternative · transparent math
Seeking Alpha is a marketplace for analyst takes. Some are excellent; many are wrong; the lock-in is the paywall and the author you follow. DeepVane replaces the author with a Bayesian factor engine: twelve academic factors, eighteen confluence patterns, conformal prediction intervals, full methodology on a public page. Different product, same shelf.
One sells opinion behind a paywall. The other ships a math engine and a published track record.
On Seeking Alpha you pick an author and trust them. On DeepVane you read the methodology and audit the math. Both are valid mental models — but only one survives an author leaving the platform, and only one gives you the same answer no matter who you ask. We built the second one.
Quality is Novy-Marx 2013. Value is Fama-French. Momentum is Jegadeesh-Titman 1993. NLP tone is Loughran-McDonald 2011 + Li 2008. PEAD is Bernard-Thomas 1989. Insider flow is Seyhun 1986. Phase 3 base rate is Hay et al. 2014. The bibliography lives on /methodology. You don't need an author to summarise — you read the source.
A Seeking Alpha "Strong Buy" article is one author's thesis. A DeepVane score arrives with a Mondrian conformal interval that says "78 ± 14 at 90% coverage on this regime/sector cohort." The interval is the model telling you when to ignore itself, which a single article never does.
Pharma authors on Seeking Alpha can be excellent — but you're getting one person's read on enrollment, endpoints, and mechanism. DeepVane runs the Bayesian model on every Healthcare-sector ticker continuously: Hay 2014 base rate updated with log-likelihood-ratios from real ClinicalTrials.gov enrollment velocity, endpoint amendments, and PubMed mechanism evidence. Same input data, structurally consistent output.
The Seeking Alpha Quant Rating (A–F) blends five factors with proprietary weighting. DeepVane is a 0–100 composite blending twelve factors with publicly disclosed weighting and a Bayesian regime overlay. Plus we ship a confidence interval per score, eighteen confluence patterns with academic citations, and Phase 3 failure prediction for biotech. Different category — closer to a hedge-fund factor model than to a paid screener.
Yes during the early-access window. All twelve factor scores, all eighteen confluence patterns, all Phase 3 failure predictions, and all conformal prediction intervals are publicly readable without a paywall. The Pro tier launches 16 May 2026 once forward returns calibrate the model. Beta users keep free access.
For factor scoring and pattern detection, yes — that's what the engine does, and it does it consistently across 374 tickers. For long-form qualitative analysis on a single name, no — Seeking Alpha's author marketplace is unmatched there. The two are complements, not substitutes. Use DeepVane to find candidates; read articles for narrative; let your own judgment combine them.
Every signal we generate is logged to signal_history with a timestamp before any forward return is known. After 30 trading days we backfill the realised return — zero hindsight bias, no curve-fitting. The first publicly verifiable Day-30 returns land 16 May 2026. Until then /track-record shows the warming-up state with a counter, not synthetic numbers.
Type any of 374 tickers — you get the full APEX 12-factor breakdown, the regime context, every confluence pattern firing, and the conformal prediction interval. The same answer for everyone, derived from the same paper-cited factors.