By the time you read the headline, someone already quantified it. The edge isn't in the news — it's in how fast you can structure it.
Raw news is noise. Black-box sentiment scores are opaque. Human-speed interpretation is too slow. You react — you don't lead.
Every article is evaluated for sentiment, impact strength, and temporal intent — proactive catalysts separated from reactive noise. You act on data, not gut feeling.
A research-first framework that transforms unstructured market narratives into structured, testable data. Users define the "physics" of the market by adjusting multipliers for each news type.
Thousands of crypto news articles are ingested in real-time, each evaluated by AI for sentiment direction (positive/negative) and impact strength.
Each article is classified as Proactive (future catalyst — leads price) or Reactive (past commentary — follows price). Most tools skip this step entirely.
Weighted aggregation across configurable coefficients produces a continuous narrative trend — a quantified measure of information pressure over time.
Structured, timestamped trend data is available via GET /api/v1/trend. Query by coin, interval (1h–1d), and date range. Plug directly into your models.
Most systems fail to distinguish between news that predicts the future and news that describes the past. Quant Lambda separates both.
News about planned actions, upcoming events, and confirmed future developments that haven't been priced in yet. These signals lead price movement.
Post-factum reports, opinions, and discussions about events that already happened. These signals follow price and confirm existing trends.
18 months of historical backtesting across major cryptocurrencies using the Narrative Trend crossover model with Dynamic Weighting. Real data, no curve-fitting.
Institutional Integration. Select strategies from this framework are currently deployed under NDA by institutional partners via API integration.
View Full Evidence →Configure parameters on the left — watch the response update in real time. Same endpoint powers our NDA institutional deployments.
{
"asset": "BTC",
"interval": "4h",
"type": "all",
"price_ref": 98421.4,
"last_updated": "2026-04-18T10:24:00Z",
"data": [
{
"t": 1776507840,
"trend": 0.114,
"proactive": 0.229,
"reactive": -0.046,
"articles": 40
},
{
"t": 1776493440,
"trend": -0.462,
"proactive": -0.174,
"reactive": -0.219,
"articles": 53
},
{
"t": 1776479040,
"trend": -0.234,
"proactive": -0.014,
"reactive": -0.15,
"articles": 66
},
{
"t": 1776464640,
"trend": 0.21,
"proactive": 0.297,
"reactive": -0.017,
"articles": 79
}
]
}From individual trader signals to institutional API integration.
Private Telegram + full dashboard + all backtested assets.
Structured trend data straight into your models.
Real entries from our backtest archive — same engine, same methodology, same results you get as a subscriber.
Quant Lambda exists because I wanted to build a system that explains markets instead of simplifying them.
Start with a $20 signal subscription. Upgrade to API when you're ready to plug it into your models.