Leversens Trading

Market context, summed up in one number.

All the news that matters, a battery of statistical models and machine learning, merged continuously into one clear bias: bullish, bearish or neutral, with the pillars' agreement, the measured accuracy and the explanation in English.

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Machine reading · NQ 1h – 4h
+1.2
slightly bullish
Nasdaq-100 futures, 1h-4h horizon: slightly bullish bias (+1.2/10), pillars aligned (3/3). Measured accuracy (historical replay of v2): 57.1% right direction over 105 calls, 95% confidence interval 48% to 66%, no better than chance so far. The news flow is within its recent norm; heaviest headline: “Stock Market Ends Week Higher Despite Spiking Yields; Jobs Report, Inflation Data Due” (Investor's Business Daily). Over the last 60 days, 52% of 4-hour periods closed higher (past frequency, not a forecast), within a typical range of -0.75% to +0.79%.
Read in production on Sep 26, 2026, 01:25 (Paris time)
45+
news sources
10
assets covered
8
quant models
24/7
continuous updates

How it works

You pick an asset (NQ, ES, YM, GC, CL in futures, or Nasdaq, Dow, S&P 500, CAC 40, DAX), a horizon (0 to 30 min, 1h to 4h, 1 to 4 days), and the machine does the rest:

01

It reads the news

45+ global feeds (Telegram squawk, Reuters, Bloomberg, WSJ, FT, official Fed/ECB/BLS/EIA sources). Each headline is scored: impact, surprise, reliability, corroboration, and direction for each asset.

02

It runs the statistics

GARCH, HMM, Kalman, Monte Carlo, bootstrap, VaR, Isolation Forest, Random Forest and XGBoost recomputed every 30 minutes on each asset.

03

It sums up, honestly

A score from −10 to +10 weighted by horizon, a comment in English that explains why, and alerts when the context is treacherous.

Eight models, each with its role

Click a model to see what it brings:

GARCH · Forecasts tomorrow's volatility from today's. It sizes the risk and the price cones, never the direction.

The honesty rule

Every directional model is tested walk-forward: trained on the past, evaluated on 60 points it has never seen. Below a 52% hit rate, it is excluded from the score and shown struck through. The overall bias faces the same rule (52%, and a confidence interval that excludes 50%). Here are its real figures on NQ:

Version 1, published · live tracking · Jul 18 → Sep 25, 2026

0 – 30 min49.6%1,698 calls
1h – 4h48.9%268 calls
1d – 4d45.2%42 calls

Version 2 · historical replay · Jul 22 → Sep 26, 2026

0 – 30 min54.4%371 calls
1h – 4h57.1%105 calls
1d – 4d44.7%38 calls

Bar: hit rate over non-overlapping windows; black line: 95% confidence interval; red mark: 50%, pure chance. Green only if the rate passes the rule and beats the naive baselines (always long, previous direction).

inclusion threshold: 52% · the overall bias accuracy is measured without overlap and recomputed every 6 hours · /api/accuracy data as of Sep 25, 2026, 21:04 (Paris time) · breakdown by asset and horizon

Built for real sessions

⏰

Context alerts

Imminent CME reopen (treacherous first print), high-impact release within 2 hours, a night of strikes in the Middle East (WTI is the referee), complacent VIX, equity/oil/dollar divergences, statistically abnormal day.

🗓️

Clickable macro timeline

7 rolling days, each event with its Paris time, its forecast and the expected impact on the asset you are watching, above or below expectations.

🔊

Voice squawk

Like the pro services: high-impact headlines are read aloud as soon as they arrive, so your eyes stay on the chart.

🤖

Machine reading

A comment in English, generated continuously: the verdict, the measured accuracy, the dominant catalysts, whether news and quant agree or disagree, and the discipline point of the moment.

Under the hood: how the machine reads a headline

The news pillar is not a black box. Here is the exact path of a headline, from its publication to its contribution to the score:

STEP 1 · COLLECTION

45+ feeds polled continuously (near-instant Telegram squawk, Reuters/AP/Bloomberg newswires, WSJ, FT, official Fed/ECB/BLS/EIA sources, geopolitics, energy/gold/Europe packs). Duplicates are merged: a story picked up by 30 outlets becomes ONE item corroborated 30 times. Everything is shown, but only relevant headlines count in the score: questions, opinions, lists, local prices and off-topic items stay visible in the feed, grayed out, with no weight.

STEP 2 · IMPACT (0-100)

impact = severity × surprise × reliability × freshness × corroboration. Severity ranks the event (FOMC/CPI = maximum, analyst noise = minimum). Reliability depends on the content as much as on the source: a verifiable fact (a figure, an official decision) counts in full, a reported event a little less, speculation (“could”, “warns”) barely more than half. Freshness decays exponentially, in market time: a weekend hour counts three times less than a session hour, so that a Saturday bombshell still weighs at the Sunday reopen (Gross-Klussmann & Hautsch, 2011).

STEP 3 · DIRECTION PER ASSET

The headline is projected onto macro axes (Fed policy, inflation, risk aversion, oil supply, dollar, tech, Europe) and then crossed with each asset's sensitivity matrix. “Oil soars”: bullish CL (supply) but bearish NQ (inflation → rates → tech). Only events give a direction, never a mere topic word: “war” or “Hormuz” alone say nothing, whereas “Iran offers to reopen Hormuz” is a resolution and reads the opposite way to an escalation. Negations (“denies”, “calls off”) and the conditional (“could”, “threatens”, at half weight) are taken into account. No asymmetry: good and bad news of the same importance weigh the same.

STEP 4 · ANTI-STACKING AGGREGATION

Items are grouped by theme: a theme's weight grows with the logarithm of the number of pick-ups, never linearly. 50 articles on the same CPI do not weigh 50 times more than the first one. The sum goes through a hyperbolic tangent that bounds the score between −10 and +10. That level is then compared with its recent norm (exponential average, 3-day half-life): an uninterrupted war news flow for weeks is already in the prices, only the deviation from that norm enters the score.

STEP 5 · THE UPCOMING CALENDAR

Upcoming events are shown, but no direction is drawn from the consensus: it is public and already in the prices. And in the 45 minutes before a major release, the score is deliberately flattened: a news bias just before a figure is dangerous noise.

STEP 6 · THE OFFICIAL RESULTS

Actual values (CPI, NFP, claims…) are fetched from official sources, FRED (Federal Reserve Bank of St. Louis) and the ECB, to compute the real surprise vs consensus, the one that moves prices.

References: Gross-Klussmann & Hautsch (2011), Journal of Empirical Finance · RavenPack/Bloomberg news analytics practices.

Full transparency

What is the data latency?

CME futures prices: regulatory delay of about 10 minutes (the price age is always shown). News: near-instant squawk, RSS feeds 1 to 5 minutes. The tool's speed comes from the news, on purpose: intraday, the headline makes the price.

Does the score predict the market?

No. It sums up the context. Price is always right in the short term: if the tape contradicts the bias, the tape wins. The bias's real predictive value is measured over non-overlapping windows, recomputed every 6 hours, and its results are shown in the tool's “Measured accuracy” block, good or bad.

Where do the bullish/bearish directions per asset come from?

Each news item is projected onto macro axes (Fed, inflation, risk, oil, dollar, tech, Europe) and then crossed with each asset's sensitivity. The same headline “oil soars” is bullish for CL and bearish for NQ through the inflation, rates, tech channel.

What does the tool not do?

No entry point, no stop, no position size, no financial advice. It is a decision aid: the context and fundamentals side. Execution remains your job.

See the market differently

The bias is already computed. Just open the page.

Open the tool →

Decision-support tool · nothing here is financial advice · delayed market data, news from public sources.