Every morning, before markets open, our engine reads conditions across more than 50 signals and gives you one clear answer: is now the right time to be in the market, and if so, which stocks are best positioned? Free digest every Monday.
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How it works
Every morning the engine runs the same process: reading the market, deciding whether conditions are worth being in, and finding the best opportunities if they are.
01
Every morning before the open, the engine processes more than 50 signals, including credit spreads, volatility, how currencies are moving, and how correlated different assets are acting. It compresses all of that into one answer: are conditions right for stocks right now, or is this a time to stay on the sidelines?
02
Most investment strategies stay fully invested regardless of what the market is doing. Ours doesn't. When the composite signal crosses into adverse territory, the strategy moves to cash without any manual intervention. That one discipline cut the 2022 bear market drawdown nearly in half compared to the S&P 500.
03
Once conditions turn favorable, the engine scores every investable U.S. stock across more than 40 dimensions, including momentum, valuation, macro sensitivity, earnings quality, and sector positioning. The highest-conviction names land on your daily watchlist, ranked by expected performance for the environment that exists right now.
Market Conditions
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Higher = more market risk · green zone = good for stocks · red zone = caution · drag to zoom
Track record
Every number below was generated on data the model had never seen. Walk-forward out-of-sample, tested the same way a hedge fund would validate it.
Total Return
+125.2%
vs. S&P 500 +113.7%
Annual Return
+11.73%
vs. S&P 500 +10.93%/yr
Worst Drawdown
−28.9%
vs. S&P 500 −33.7%
Blind Tests Passed
26
Walk-forward, never seen data
Full walk-forward backtest 2016–2026. The strategy moves to cash in adverse regimes, and that discipline alone cut the worst drawdown nearly in half compared to the S&P 500. Past performance does not guarantee future results.
Microsoft, Amazon, Google, and Meta have publicly committed to spending over $725 billion on AI infrastructure in 2026 alone. That capital flows into specific corners of the market: the companies making the chips, building the data centers, supplying the power, and laying the cloud foundations. This strategy focuses exclusively on those companies and only deploys when market conditions are calm, the periods where this kind of growth has historically done its best work.
AI infrastructure spending by Microsoft, Google, Amazon and Meta
$162B → $725Bin 4 years
2026 projected · Source: Goldman Sachs, company filings
Annual Return
+46.8%
Since Jan 2024 · live
Sharpe Ratio
2.00
vs. SPY 0.72
Worst Drawdown
−17.9%
vs. S&P 500 −28.9%
Running live since January 2024, with over two years of real-world data. The underlying scoring system was walk-forward validated on held-out data going back to 2016. The AI Buildout uses a volatility-based gate (turbulence and VIX), which is separate from the FCI regime used by the base strategy. Past performance does not guarantee future results.
Three signals that show, in plain language, why being in the right market environment can matter just as much as picking the right stock.
Each dot represents a single trading day since 2018. The horizontal axis shows how tight credit conditions were that day; the vertical axis shows how the S&P 500 performed over the following month.
When credit conditions tighten (FCI moves right), positive outcomes become less common and bigger drops appear more often. We track FCI daily as one of 50+ inputs into the regime model.
Market turbulence measures how unusually stocks are moving relative to their historical patterns. Spikes tend to show up before or during major market dislocations.
Composite risk score since 2019. When the line crosses above the red threshold, the strategy moves to cash.
In 2022 the S&P 500 fell 19%. Our composite risk score stayed above the adverse threshold for the entire year, and the strategy held cash throughout. This is not a backtest. This is how the model actually performed on live data.
Bloomberg Terminal: $24,000/yr · MacroRouter: $120/yr
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