Your ICT Strategy Isn’t a System (Here’s the Test) | Pt. 2

Summary

The presenter distinguishes a discretionary trading strategy from a rule-based system. If decisions depend on subjective judgments such as “the market looks strong,” the rules are not yet precise enough for reliable coding, backtesting, or replication. The proposed test is whether a computer or another trader could apply the rules consistently and identify the same trades.

The presenter reports using automated systems built with Claude to trade funded and evaluation accounts. The following performance figures are self-reported:

• Purchased 4 Lucid accounts; 2 passed and 2 failed.
• Reported payouts totaled about $1,160 (also described as roughly $1,150), against approximately $200–$300 in evaluation costs, leaving the presenter net positive.
• Reported an approximately 50% account pass rate and a first automated-system payout of $500.
• Received a later payout around October 12; the video was recorded on October 16.
• On a $25,000 funded account, reported 18 trading days, 4 profitable days, and being close to the reserve required for another payout.
• On a $50,000 account, after receiving a payout, reported a $196 loss followed by $91 profit the next day. That day did not qualify as a winning day.
• Across two systems, the dashboard showed a 1.26 profitability ratio, 52% win rate, and a worst losing streak of 11 trades. The presenter attributed the streak to losses across both systems, including a system called Flipper running on evaluation at Tradeovate.
• A separate demo account had about $200 of drawdown remaining after six consecutive losses, which the presenter described as part of the process.

System-Building Framework

• Write down every rule and replace subjective language with measurable conditions.
• Define each trading concept precisely, including ICT concepts such as fair value gaps (FVGs), inverse FVGs, “macros,” and Power of Three.
  • A macro is defined here as the 10 minutes before and after each hour.
  • For Power of Three, specify measurable criteria for accumulation, manipulation, and distribution—for example, range duration and size, and what qualifies as a breakout or impulse.
• Build and test components separately, then combine them. The presenter suggests using Claude to generate Pine Script and checking indicators on multiple chart intervals, such as 15-minute, 5-minute, and 1-minute charts.
• Make entries objective. Alternatives to “buy when it looks strong” include a close above the 20-day moving average, a candle close exceeding 20 pips, or a close higher than those of the prior 3–4 candles.
• Specify exits mechanically. For example, replace “exit if it looks bad” with a stop one pip below a defined local low (or above a local high). Define what counts as a local high or low.
• Set explicit profit-taking rules. The presenter says the first system uses a fixed 1:1.5 risk-reward ratio and the second a 1:1 ratio, with stops based on local highs and lows. A fixed point target is another possible rule.
• Restrict trading to defined hours, rather than “only trade when conditions are good.” The presenter says one system trades for about 12 hours and another for 9–10 hours, and gives 9–11 a.m. and 5–9 a.m. as example windows.
• Iterate with Claude: generate code, test whether it reflects the intended rules, fix bugs, and refine through repeated questions and trial and error. The presenter cautions against assuming Claude understands unstated definitions.
• Test combinations of concepts and parameters rather than assuming all discretionary criteria must be included. Concepts mentioned include FVGs, ranges, macros, Power of Three, volume profile, moving averages, and VWAP.
• Evaluate consistency, not just recent results. The presenter recommends examining roughly 3 years of historical data and at least 1,000 trades, and describes holding out a 4-month period for out-of-sample testing. Alternatively, forward-test in real time for about a month.
• The presenter cautions that automated systems may have lower win rates or profitability ratios than discretionary trading, but can execute rules consistently. Some discretionary concepts—such as “low-resistance liquidity”—may be too difficult to code or may not be worth pursuing.

Assets, Instruments, and Platforms Mentioned

• No specific stock ticker, ETF, cryptocurrency, bond, or commodity is named.
• Trading references include funded and evaluation accounts, points and pips, and chart-based trading. The subtitles do not identify a specific traded contract or market.
• Concepts and tools include FVGs and inverse FVGs, macros, Power of Three, ranges, volume profile, VWAP, moving averages, and local highs and lows.
• Platforms and tools mentioned include Claude, TradingView, Pine Script, Lucid, and Tradeovate.

Cautions and Disclosures

The presenter emphasizes that coded rules cannot rely on “feel,” that losses and losing streaks are possible, and that a strategy should be tested across substantial historical and out-of-sample data. Results and account figures are the presenter’s own reported outcomes. No explicit financial-advice disclaimer appears in the provided subtitles.

Presenter/source: Full View Trading. The speaker mentions “Ruben,” though the subtitles do not clearly establish whether that is the presenter’s name. Claude, TradingView, Lucid, and Tradeovate are cited as tools or platforms.