3 minmethodologyproofbaselines
Beating random isn't enough: we pitted the engine against three dumb strategies
Saying "68% accuracy" is refutable in one sentence: the market rises 55% of the time. So we compared the engine to random, to "always up" and to naive momentum, matched on the same assets and dates. Honest result: we beat two out of three.
3 minmethodologyproofbacktest
Beyond accuracy: why we measure P&L in units of volatility
A high hit rate can hide huge losses. We measured the average gain of each bet in units of volatility (σ) — the real judge — and found that accuracy told an incomplete story. A pre-registered analysis, published whatever the result.
2 minmethodologyproofsignals
Losing families: how we bench some signals without quietly deleting them
Some signal families lose structurally. Rather than quietly erasing them from the record, we put them "under observation" — measured but out of the traded flow — and their only way back is the counterfactual, never an editorial call.
3 minmethodologyproofsealing
We can't rewrite our predictions: how every signal is sealed
Anyone can say "I called it" after the fact. So we publish the cryptographic fingerprint of every signal the moment it's issued, reveal the content later, and anchor the whole thing outside our own servers. Here's how — and, more importantly, what it doesn't prove.
3 minmethodologyproofbacktest
The only backtest we trust: parity with the live engine
You can make almost any strategy shine in the past — just let a little of the future leak in. Our backtest replays the exact live pipeline, dated to the day: reconstructed market context, walk-forward weights, news frozen at its own date. It's slower, less flattering, and that's the point.
5 mintransparencymethodologypost-mortem
We audited our own engine: 7 defects, and a track record reset to zero
Our displayed accuracy was stalling, our virtual portfolio was bleeding. Instead of massaging the numbers, we put the engine under the scalpel: a full forensic audit, 7 root causes, retroactive corrections — and a public counter reset to zero. Here is everything, unfiltered.
4 mingeopoliticsVIXregime
VIX at 16 while the Strait of Hormuz burns: why markets ignore crises
Threats over Hormuz, Iran-Israel escalation, nuclear tensions: the most geopolitically loaded quarter in years… and the S&P 500 gained 11%. This paradox has a name — the complacency regime — and numbers. Ours, measured across 341 signals.
8 minmethodologytransparencysignals
The half-life of a signal: why "WTI ↑5% over 14d" doesn't mean the same thing on day 1 and day 12
A financial signal isn't a frozen object. Its informational value decays over time like a radioactive isotope. Here's how we imported the half-life concept from physics to make our signals honest — and why your Kelly allocation should follow.
7 minmethodologycomposite-indexvix
Anatomy of the GeoPulse composite index: how to summarise the markets in a single 0–100 score
Behind the dashboard's main gauge, five aggregated sub-scores. VIX, yield curve, fear & greed, geopolitics, momentum — exactly what we measure, why, and how to tune it to your style.
6 minmethodologytransparencyai
Anatomy of a failed signal: what AI taught us from 4 botched WTI calls in a row
Four different rules predicted oil up during the Iran crisis. The market dropped -8%. We asked Mistral Large to dissect each error, and the pattern that emerged changes how we build our signals.
5 minormuzgoldbitcoin
Oil, gold, Bitcoin: who actually benefits from the Ormuz crisis?
The Ormuz crisis doesn't only produce losers. Oil soaring, gold paradoxically falling, Bitcoin in free fall — analysis of the winners and losers across financial markets.
4 minormuzoiliran
The Ormuz Crisis: how it's hitting your investments in real time
The blockade of the Strait of Hormuz isn't just about oil. Fertilisers, helium, aluminium — a cascade analysis of what's rippling through financial markets and your portfolio.