Backtest Research
Simulated parameter analysis for FSD-X ORB PRO (Knightfall MK1) tracking 1,109 total execution cycles from June 18, 2019 to August 7, 2026. Calculated utilizing a grade-based risk model — risk is scaled dynamically by setup grade. Hypothetical results — past performance is not indicative of future results.
⚠ All data on this page reflects hypothetical simulated backtest results, not actual trading. Past performance is not necessarily indicative of future results. Figures are gross of costs — they exclude commissions, fees, and slippage, which vary by broker and reduce net performance. Results shown are from a specific risk profile and are not typical.
⚠ Hypothetical, simulated backtest results — not actual trading. Figures are gross of costs (exclude commissions, fees, and slippage). Past performance is not necessarily indicative of future results.
See the numbers for your account size
Pick your account size and base risk to see the full picture for each profile: how it performs getting funded (eval pass rates) and trading funded (7-year backtest). This is the same planner our members use — now open, so you can check it against the account you actually trade.
// GRADING LAYER METRICS — SIMULATED
Hypothetical backtest · $400 risk profile · grade-based dynamic sizing · gross of costs
// MULTI-YEAR ANNUAL LEDGER — BACKTEST DATA
The same 1,109 simulated trades, cut by month, quarter, weekday and week of month. Setups arrived at a similar rate in every month — about 11 to 15 a year-month across the sample. What each setup returned did not.
Hover any bar or cell for detail. Every chart has a table twin.
// AVERAGE RESULT PER TRADE, BY MONTH — SIMULATED
Simulated dollars per trade, all 1,109 trades pooled by calendar month. Setups arrive at a similar rate all year — about 11 to 15 a month in any given year. The return per setup does not stay similar.
Swipe the chart sideways — or use the table view.
// BY QUARTER
Simulated dollars per trade. Q1 to Q3 is the widest of the four.
// BY DAY OF WEEK
Simulated dollars per trade on comparable volume — 209 to 246 trades per day.
// BY WEEK OF MONTH — SIMULATED
Simulated dollars per trade. Week 5 is a partial bucket — only months with a 29th through 31st contribute to it, so it holds 70 trades against 240-odd in each of the others. Read Week 5 as a footnote, not a finding.
Swipe the chart sideways — or use the table view.
// EVERY MONTH, EVERY YEAR — SIMULATED
Simulated net result per calendar month. 2019 begins June 18 and 2026 ends August 7 — both are partial years. Empty cells are months with no simulated trades. Values are printed in every cell, so nothing here is carried by colour alone.
Swipe the grid sideways — or use the table view.
// WHAT THIS DATA DOES NOT SAY
Seven years is six to eight observations per calendar month, not ninety. Each monthly bar averages a handful of samples — six Novembers, eight Junes. Nothing here is tested for statistical significance, and none of these gaps is wide enough relative to the sample to rule out chance. The quarterly and day-of-week splits pool the most trades and are the most dependable; Week 5 pools the fewest and is the least.
This is not a forecast. Nothing here predicts what any month will do next. A seven-year average describes what the simulation did, not what the market will do.
It is not a filter we apply. The strategy takes every qualifying setup in every month. We publish this so members recognise a slow stretch as a slow stretch instead of a broken system — not so anyone sits out a quarter.
Dollars, not points. These figures come from the grade-based dynamic sizing model, so month-to-month differences blend how the setups performed with how many contracts the model allocated. A size-neutral points breakdown is not published here.
2026 Overlaps Our Live Tracking
2026 is a partial year here, and it covers the same stretch as our live tracking, which began May 1, 2026. Over the shared window (May 1 – August 7, 2026) this backtest shows $2,730 across 50 simulated trades at 58.0%. The live page shows what the strategy actually signalled over the same days, tracked independently.
The two figures are produced separately and are never combined into one total. They live on separate pages on purpose. Worth noting when you compare them: that window covers May through August — several of the slower months in this seven-year sample — and the simulated win rate over it (58.0%) sits below the full-sample 63.03%.
See the live track record →Method
Derived from the same TradingView Strategy Tester export that produces the equity curve on the Overview tab: 1,109 simulated trades on MNQ 5-minute, June 18, 2019 through August 7, 2026, production defaults, grade-based dynamic sizing at the $400 indicator setting. Trades are bucketed by close date. Win rate counts a trade as a win when its simulated result is above zero. “Week 1” is the 1st through 7th of a month, “Week 2” the 8th through 14th, and so on; “Week 5” is the 29th onward. Every bucket on this tab sums back to $104,230 across 1,109 trades. The gain/loss pair on the heatmap sits in the colour-vision-deficiency warning band, which is why every cell carries its printed value and a table twin rather than relying on green versus red.
This is the data. The next step is your own chart.
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