The Almanac · Vol IProofVerified 2026-08-07
Every run published — winners and losers

The 5 runs — 2 trailed, 1 matched, 2 beat

Five Investing Engine backtests over one window — Dec 2019 – Aug 2026 — every figure transcribed from a captured table that renders its own settings header. Two beat, one matched, two trailed. The runs that trailed are published as prominently as the ones that beat.

Two of five published runs trailed, one matched, two beat. This page is the window, the configuration rules, the fill conventions, and those results — including the ones that trailed. How the models compute stays private: the mechanism is the product, and it stays private because you can verify without it — three of the five models ship a backtest engine you can run on your own assets.

The test protocol

  • One window, never a favourable slice. Every published run covers Dec 2019 – Aug 2026.
  • Portfolio settings are disclosed, not justified. $100,000 starting capital, LIFO exits, zero fees on every run. These change the accounting, not which signals fire.
  • Model settings require a rule stated before the result is seen. Configuration is required for correct use — the models execute a thesis, they do not predict direction. The line between configuring and curve-fitting: if the only justification for a setting is “it backtested best,” the run is not published. The rule for every run is printed below.
  • Settings are self-disclosing. Each screenshot renders its own configuration header. The header is never cropped.
  • Fill conventions are disclosed per run. “Bar open” fills at the signal bar's own open while the signal derives from that bar's close — lookahead, not a realism preference. The two weekly Trend Model runs used it; the other three filled at bar close.
Outcome thresholds — fixed so nothing reclassifies later
beatreturn strictly above buy-and-hold
matchedreturn within 5% relative below buy-and-hold
trailedreturn more than 5% relative below buy-and-hold

The 5 runs — 2 trailed, 1 matched, 2 beat

Trend · META · weekly

beat
Return
+221.57%
Buy & hold
+171.53%
Max drawdown
−19.79%
Exposure
63.66%
Trades
4B · 4S
Fill
bar open

Tightness Loose · bar open · 50% entry · LIFO · $100k · no fees

The rule, stated before the result: Tightness set to the swing end of its range, per the model's own guidance that Loose suits swing and position trading. Weekly bars leave no shorter horizon to trade, so the timeframe alone lands this run at that end. All other model settings shipped default.

Trend · AMD · weekly

matched
Return
+888.90%
Buy & hold
+903.55%
Max drawdown
−32.28%
Exposure
50.00%
Trades
6B · 5S
Fill
bar open

Tightness Loose · bar open · 100% entry · LIFO · $100k · no fees

The rule, stated before the result: Same tightness rule — weekly chart, position-trading horizon, so Loose rather than Tight. All other model settings shipped default.

Convergence · Russell · daily

beat
Return
+82.59%
Buy & hold
+81.65%
Max drawdown
−25.62%
Exposure
85.55%
Trades
10B · 4S
Fill
bar close

Bias Bullish · bar close · 30% entry · LIFO · $100k · no fees

The rule, stated before the result: Bias is chosen from what the asset structurally is, not from anything the chart has already done: a whole-market equity index drifts upward over long horizons, so this run leans toward buys rather than sells. All other model settings shipped default.

Deviation · BTC/USD · daily

trailed
Return
+349.82%
Buy & hold
+805.54%
Max drawdown
−65.10%
Exposure
87.60%
Trades
112B · 102S
Fill
bar close

Style Aggressive · bar close · 30% entry · LIFO · $100k · no fees

The rule, stated before the result: Style set to surface structure rather than suppress it: a 24/7 asset generates far more tradeable structure than a session-bound one. All other model settings, including noise suppression, shipped default.

Convergence · NVDA · 4-hour

trailed
Return
+827.85%
Buy & hold
+3,718.00%
Max drawdown
−43.60%
Exposure
73.66%
Trades
14B · 10S
Fill
bar close

Bias Bullish · bar close · 30% entry · LIFO · $100k · no fees

The rule, stated before the result: Same bias rule as the index run. The position is long-only in a growth name, so bias is set to the direction of intended participation. All other model settings shipped default.

Failure modes

Derived from the runs above, never invented: on assets in sustained parabolic advance, the engine underperforms holding. Every exit is a chance to miss the next leg, and the engine takes exits. NVDA on the 4-hour returned 22% of buy-and-hold; BTC daily returned 43%. Both were configured correctly under the rules above — neither is a strawman.

Longest losing streak, worst single trade, longest time in drawdown, and regime slices (2020 / 2022 / 2023–25) are not yet derived from the runs. They will be read off the artifacts or re-run — never invented. Until then, this is the only failure mode we publish, because it is the only one we have derived. Others are not yet derived — not absent.

The operating envelope

Each model is built for a market condition, and each has one it handles badly. Both halves are printed below for all 5 models, at the same weight.

This is stated design intent, not a measured result. The runs above cover the 3 models that ship the backtest engine; the other 2 have no published run at all. An envelope tells you when a model is the wrong instrument for what the market is doing — it does not tell you what any of them returned.

Convergence Model

Runs best in
High-volatility reversals on liquid assets
Degrades in
Low-volatility drift — signals go quiet

Deviation Model

Runs best in
Range-bound, mean-reverting markets
Degrades in
Parabolic trends — trims winners early

Trend Model

Runs best in
Sustained directional trends
Degrades in
Sideways chop — whipsaw entries

Adaptive Trend Model

Runs best in
Regime shifts between chop and trend
Degrades in
Ultra-short timeframes with thin volume

Peak Retracement Model

Runs best in
Any market — sizing overlay
Degrades in
Short price history — levels unstable

Known limitations

  • The backtest engine does not report buy-and-hold drawdown. We can print the engine's own drawdown and its market exposure, but not a measured drawdown delta against holding — so we never claim one.
  • There is no confluence backtest. “When all the models agree, how often is it right?” is a conditional probability that would have to be measured, and the instrumentation to measure it does not exist. We show the mechanism instead, and we do not multiply signal accuracies — the models read the same price series, so their accuracies are correlated.
  • All results are hypothetical backtests. Past performance does not guarantee future results.

Every figure on this page is transcribed from a captured backtest table, last verified 2026-08-07. The screenshots render on the sales page. Subscribe and run the same backtests yourself — change the asset, the timeframe, the parameters. Or break it.

Run the backtests yourself.

Three of the five models ship the backtest engine — change the asset, the timeframe, the parameters, and see what comes out. You do not need the mechanism to verify the result.