Blog
Data-driven insights on seasonal trading patterns, cycle timing, and market analysis.
We Ported the Most Popular ICT Strategy to Python. Its 17% Came From Fifteen Trades.
ICT Master Suite is open source and publishes its own backtest: +17.36% in fourteen weeks at a 66.20% win rate on Nasdaq futures. We exported all 71 trades, rebuilt the strategy from its library source, and matched 43 of its entries to the exact second. The profit comes entirely from 15 New York PM trades — the other 54 lose $13,165 — and commission took 49% of gross. Run long only to match that configuration, over 1,807 trades and 8.5 years at the same cost, it returns −0.393R per trade with a 0.407 profit factor — every killzone negative and not one profitable calendar year. We also found two bugs in the library, one of which forces every short onto the only code path that reads future data.
We Watched Trader Mane’s Entire ICT Course. Then We Backtested It.
We froze the choices left open by Trader Mane’s 20-video ICT course into four causal strategies and six controls, then tested them on 2.6 million Nasdaq minute bars and replicated on GBPUSD. The strict variants produced 0–3 trades each; the higher-sample controls lost after costs. None passed the registered evidence gates.
We Gave Four ICT Setups a Placebo Test. Three Failed. The Fourth Died at One Point of Cost.
Gross of costs, all four setups we tested made money — fair value gaps, Power of Three, inversion FVGs and breaker blocks, 8,443 trades across 8.5 years of Nasdaq 1-minute data, profit factors of 1.06 to 1.14. Then we built the control almost nobody runs: the same trade, same time of day, same direction, same ATR-scaled bracket, on a random date. Three of the four could not be told apart from it, and the placebo distributions were themselves positive — in a market that went from 6,700 to 29,500, doing nothing in particular pays. Breaker blocks cleared the 99th percentile on Nasdaq and the 25th on GBPUSD. The one setup that genuinely beat its placebo, a 15-minute FVG retrace with a displacement filter, turned negative at a single point of round-turn cost.
We Read All 620 ICT Videos. The “Codeable” Silver Bullet Wasn’t Actually Mechanical.
The Silver Bullet looked codeable until we audited the primary lecture: direction comes from a preselected draw on liquidity. ICT teaches ways to judge that draw, but the Silver Bullet material gives no universal mechanical tie-breaker when several eligible draws coexist. We tested all seven transcript-listed draw categories across 2.6 million Nasdaq 1-minute bars using causal fills and two points of cost. No literal draw produced a statistically defensible edge; the least-bad version still lost 0.021R per trade.
The Fed Crushed Stocks Wednesday. By Friday It Never Happened. We Tested All 24 Since 1952.
On July 29, 2026 the S&P 500 fell 1.52% on the Fed decision and had erased the entire loss by Friday’s close. That shape has occurred 24 times since 1952, and the Monday after closed higher 14 of them — 58.3%, the kind of stat that gets quoted all weekend. Then we ran the control: any Friday closing up 1.5%+ is followed by a 57.2% Monday. The edge is end-of-week momentum, not the Fed. Interactive table with a chart for every precedent.
ICT’s “Chain of Custody” Lecture, Turned Into Code
ICT’s July 2026 lectures use two graded ranges at the same time: a projection from an imbalance candle to a chosen liquidity draw, and a printed daily inefficiency graded from its own high to its own low. We encoded both. The levels are deterministic after their inputs are fixed, but selecting the projected target — and deciding which daily zone remains active — still requires a stated rule.
We Coded All Five Setups From a Viral ICT Strategy Guide. One Survived (Barely).
A popular TradingView guide teaches five ICT setups on Bitcoin — fair value gaps, Power of Three, inversion FVGs, breaker blocks, the Silver Bullet — with plenty of annotated charts and zero numbers. We mechanized all five and ran them over 10,000+ trades on BTC perpetuals and 1-minute NASDAQ futures with conservative fills and real costs. On Bitcoin, stop geometry hands 0.3–2.4R per trade to fees; on NQ, three setups land at breakeven and inversion FVGs lose at scale. The one survivor — 15-minute FVG retrace with a displacement filter — netted +0.155R over 249 trades, every one listed for review.
Mercury Combust AND Retrograde: We Tested the Double Condition on 76 Years of Data
If retrograde scrambles markets and combustion burns up Mercury's signal, the stretch where both hold should be the danger zone — and the 2008 crash week and the COVID crash both started inside one. We computed the combust-retrograde window of all 242 retrogrades since 1950 (it exists in every single one), tested drops after entering it and volatility inside it, with a clickable chart for every window. Inside vs. outside: daily range 1.19% vs 1.17%, up days 53.2% vs 53.1%. The market cannot tell the difference.
Does the Market Drop at Least 2% When Mercury Goes Retrograde? We Tested All 242 Since 1950
The claim: expect a ~2% drop in the days after Mercury stations retrograde — and again at the midpoint. The highlight reel is real: Mercury stationed the Friday before Black Monday 1987 and three days before the COVID crash. So we tested all 242 stations and midpoints since 1950 at four drop thresholds, with a clickable chart for every event. The base rate nobody mentions: 2% five-day drops follow 18.2% of ALL trading days. The stations manage 17.8%.
The Venus 225-Day Square-Out: We Projected One Venus Orbit From Every Major S&P Pivot Since 1950
A Gann-style call from a trading clinic: July 3, 2026 sat exactly one Venus orbit — 225 days — after the November 20 low, so the cycle had "squared out" and fireworks would start Monday. The arithmetic is perfect. We projected all 519 major S&P 500 pivots since 1950 forward 225 days, tested swing pivots and tradeable reversals against their base rates, and swept every offset from 30 to 400 days — Venus ranks #98 of 371. The market answered too: a five-week high a week later.
New Moon and Mercury Combust on the Same Day: We Found All 20 Since 1950
An astro-trading clinic asked for research: how often does the New Moon land on the same day as a Mercury-Sun conjunction, and are those large-range days? We computed every occurrence since 1950 — 20 events, about one every four years — and checked the S&P 500 on each, with an interactive chart for every date. The rarity is real. The volatility is not.
Does the Market Turn at the Midpoint of Mercury Retrograde? We Tested All 241 Since 1950
A trading-community claim: the exact midpoint of Mercury retrograde — the night of July 12 for the current one — marks a market direction change. The astronomy checks out; it is the inferior conjunction. So we ran the full battery on all 241 midpoints since 1950: swing pivots, tradeable 1.5% reversals, a walk-forward hot/cold cycle filter, and every astrological slice from combustion to Mercury-in-Leo — with an interactive table where you can open the chart for every single one. Nothing beats the random-day base rate.
Does the Market Really Reverse on Perihelion and Aphelion? We Checked 76 Years of Data
A claim from astro-trading circles: the S&P 500 "always" reverses when Earth is closest to or farthest from the Sun. We computed the exact dates for 1950-2026 and ran the base-rate test nobody runs — with an interactive table of all 153 events where you can open the chart for every single date. The streak is real — 10 of 11 recent perihelions "hit" — and so is the reason it means nothing.
We Coded Two “70% Win Rate” ICT Session Strategies. Neither Survived.
The follow-up to our fair value gap study: a NY 8:30 range-reversal on NASDAQ futures and a London-bias order-block setup on GBPUSD, coded exactly as taught and run over 523 trades with conservative fills. Win rates came out at 18–29% against 29–33% breakevens — the advertised 70% lives in the discretion, not the rules.
We Backtested ICT’s Fair Value Gap Rules on 53 Years of Dollar Index Data
A tick-perfect Dollar Index reversal call in June 2026 sent us to the code editor. We mechanized the fair value gap rules — volume imbalances, the validity filter, consequent encroachment — and ran 6,035 gaps and 3,986 trades since 1973. Win rate: 38%. Expectancy: +0.29R. The filter and the midpoint exit both earn their keep.
The Truth About 100% Win-Rate Seasonal Patterns
We stress-tested 37,430 patterns with a perfect 100% record across 1.4 million trades back to 1981. An early bad day doesn't predict failure, the 100% record falls to ~57% out of sample, and only two things actually hold up: the pattern's historical magnitude and the calendar month of entry.
"Sell in May" Is Wrong — But the Cycle Is Turning Down
For the last 10 years, buying the S&P 500 on May 20 and selling on June 9 has won 10 out of 10 times with an average return of +2.5%. But the equity curve cycle that has guided this pattern since 1950 is now rolling over.
The 60-Year Cycle: Trading the S&P 500 With Swing Pivots From 1960
Swing highs and lows from 60 years ago mapped onto today's S&P 500. Long-only, the strategy produces a 70.8% win rate, 4.35 profit factor, and +372% return over 16 years — but the current regime is COLD.
How to Use Equity Curve Regime Filtering to Avoid Cold Streaks
A seasonal pattern with an 80% win rate can still lose money for years. Equity curve regime filtering tells you whether a pattern is working right now — turning -8% into +128% with the same patterns.
What Is Seasonal Trading? A Data-Driven Guide
How recurring price patterns work, how to evaluate them with win rates and efficiency scores, and why some of the most well-known seasonal tendencies have persisted for decades.
How to Screen Stocks for Seasonal Patterns
Find high-probability seasonal setups in seconds — not hours. A data-driven walkthrough of systematic seasonal screening with a real DHL.DE example: 10 trades, 10 winners, 100% win rate.