I figured a way to totally remove emotions from trading (5 exact frameworks).

Summary

In this insightful video, Roy discusses how traders often struggle with emotional decisions such as overthinking, greed, and doubt. He emphasizes the importance of backtesting data to remove confusion and make informed decisions, especially when determining take-profit levels and handling losing streaks. By relying on data rather than emotions, traders can avoid impulsive moves and optimize their systems. Roy also stresses that whether a trading system is profitable or not, continuing to use and analyze it over time is key to improvement. His approach is a mix of discipline, data, and understanding the psychology behind trading.

Takeaways

• 🧠 Your brain defaults to your heart/emotions when it lacks an intellectual framework to answer a decision.
• 📊 Create clear, data-driven frameworks so your brain won't seek emotional guidance for trading decisions.
• 🔁 To stop revenge trading: backtest 100 trades, then backtest the same 100 but re-enter after every loss — the P&L difference shows the real cost of re-entering.
• 💸 Quantify the cost of emotional actions (e.g., re-entering) — a concrete number makes it easier to avoid them.
• 🛑 Stop moving stops mid-trade by backtesting stop-placement options (e.g., below 1st low vs 2nd low) and choose the one that produces better results over 100 trades.
• ⏱️ Hesitation/overthinking is usually confusion, not psychology — resolve it by backtesting the specific setup (e.g., entries with nearby liquidity) to know what works.
• 🎯 Decide take-profit levels with backtested, strategy-specific R:R results (e.g., 1:2–1:3 may outperform 1:7–1:8) instead of greed-driven guessing mid-trade.
• 🔍 Ignorance — not character flaws like greed or overthinking — causes most emotional trading mistakes; information and testing fix it.
• 📈 During losing streaks or underperformance, continue using the system: profitable systems generate money, unprofitable ones can be fixed only by using them long enough to generate loss-pattern data to analyze and optimize.
• 🧩 Fixing an unprofitable system requires collecting real trade data, identifying loss patterns, and then avoiding or adapting to those patterns.
• ⚠️ Beware of scammers: the speaker will never DM first and applications are only via the link in the description.
• 🛠️ The overall method: convert confusion into confidence by replacing emotional decision-making with repeatable, numerical frameworks built from backtesting and analysis.

Q & A

What is the main theme of the video?

The video discusses five intellectual frameworks that help traders eliminate emotional decision-making in trading, such as revenge trading, moving stop-losses mid-trade, hesitation, greed during take-profit decisions, and doubting their trading systems during losing streaks.

According to the speaker, why does the brain refer to the heart when making decisions?

The brain refers to the heart when it lacks an intellectual framework or clear logical answer to a question, leading to emotional decision-making based on feelings rather than data.

What is the proposed framework to stop revenge trading?

The framework involves backtesting 100 trades normally, then backtesting the same 100 trades but re-entering after each loss. By comparing the P&L of both tests, traders can identify the cost of revenge trading and avoid it once they see how much it reduces profitability.

How does the backtesting framework help prevent revenge trading?

By quantifying the cost of revenge trading (e.g., losing an additional 4% profit per 100 trades), it gives the brain concrete data to rely on instead of emotions, removing the urge to re-enter trades impulsively.

What causes traders to move their stop-loss during a trade?

Traders move their stop-loss due to confusion about where to place it initially. This confusion leads them to rely on emotions, such as the desire to avoid loss or correct a perceived mistake, resulting in poor decisions.

How can traders build confidence in their stop-loss placement?

Traders should backtest different stop-loss placements, such as below the first low or second low, and compare which performs better over time. The data then becomes their intellectual framework, eliminating confusion and emotional adjustments mid-trade.

What framework helps traders overcome hesitation when taking trades?

Traders should backtest 100 trades with the specific setup they hesitate about—such as trades with liquidity below entry—to determine whether it is profitable. Knowing the data-based outcome removes uncertainty and overthinking.

How does the speaker suggest handling greed when adjusting take-profit targets?

The speaker advises backtesting trades with different risk-to-reward ratios, such as 1:2, 1:3, and 1:7. If the data shows that lower ratios (e.g., 1:2 or 1:3) yield more consistent profits, traders can channel their greed productively by choosing the most profitable strategy based on data.

What does the speaker recommend traders do when their system is underperforming?

Traders should continue using their trading system regardless of performance. If it’s profitable, it will make money over time. If it’s unprofitable, continued use generates data to analyze and improve the system.

What overarching lesson does the speaker emphasize throughout the video?

The speaker emphasizes that emotional trading problems stem from confusion and lack of information. The solution is to replace emotion-driven decisions with data-driven frameworks through consistent backtesting and analysis.

Why does the speaker call emotional trading an 'information issue' rather than a 'psychological issue'?

Because emotions arise when the trader is uncertain or lacks data. By providing concrete information and results through testing, the trader eliminates confusion and no longer needs to rely on emotions to make decisions.

What is the benefit of using intellectual frameworks in trading?

Intellectual frameworks provide logical, data-based guidance for decision-making, preventing emotional reactions like fear, greed, and doubt, and leading to more consistent and profitable trading outcomes.