Video summary

La NUEVA Estrategia que desarrollé para 2026 (80% winrate)

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Summary of Business-Specific Content from “La NUEVA Estrategia que desarrollé para 2026 (80% winrate)”

Strategy Overview

The strategy focuses on trading Nasdaq futures during the New York market open, specifically between 9:30 AM and 10:10 AM ET to maximize win rates. It centers on identifying a recurring market pattern involving liquidity inflows and the first Internal Fair Value Gap (IFBG) of the session.

Goal: Develop a mechanical, repeatable trading strategy with a high win rate (~80%) by exploiting early-session liquidity and price action patterns.

Key Frameworks and Processes

The “First IFBG of the Session” Theory

  • Trade only during the first IFBG appearing between 9:30 and 10:10 AM.
  • Requires a liquidity intake (liquidity grab from session high to low).
  • Confirm IFBG presence on a higher timeframe (e.g., 2-3 minute candles).
  • Target nearby swing highs or lows for profit-taking.
  • Manage risk by moving stop losses to break even after partial target achievement.
  • Avoid trading past 10:10 AM to maintain a higher win rate.

Risk Management

  • Typical risk per trade: 0.5% to 0.7% of capital.
  • Example position sizing: $350 per trade on a $50,000+ account.
  • Use risk-to-reward ratios of 1:1 or slightly better.
  • Adjust stop loss and take profit dynamically based on market structure.

Trade Execution

  • Trades should be mechanical, minimizing subjective judgment.
  • Entry based on liquidity and IFBG confirmation.
  • Exit at target or stop loss, with flexibility to move stop loss to break even.
  • Align trades with overall market direction when possible (initial testing was done without this filter).

Key Metrics and Results

  • Win Rate: Approximately 80% based on backtesting from November data.
  • Profitability: Around 6% account growth over 20 trading days (~$3,000 profit on a $50,000 account).
  • Trade Frequency: Limited to roughly 40 minutes of active trading per day.
  • Risk per Trade: 0.5% to 0.7% of account size.
  • Backtesting Period: Initial testing on November data; plans to extend to August, September, and October.
  • Account Size Mentioned: Approximately $50,000 to $53,000.

Actionable Recommendations

For Traders

  • Focus trading on the first IFBG of the session within the 9:30–10:10 AM window.
  • Use liquidity grabs and IFBG confirmation as entry signals.
  • Keep trades mechanical to reduce emotional decision-making.
  • Employ strict risk management with stop loss adjustments.
  • Backtest the strategy further across different months and market conditions.
  • Consider aligning trades with overall market direction to improve outcomes.
  • Document trades and results to refine the strategy over time.

For Strategy Development

  • Name and brand the theory to build community recognition (e.g., “First IFBG Theory” or “Half-Hour Theory”).
  • Engage the audience for feedback and improvements.
  • Potential to develop this into a formal trading manual or playbook.

Concrete Examples and Case Studies

  • Multiple live and backtested trades analyzed, showing entries at the first IFBG of the session.
  • Trades ranged from break-even to 1:1 risk-reward targets.
  • Examples included adjusting stop losses, moving take profits, and managing trades dynamically based on price action.
  • The presenter shared personal account performance and risk sizing to illustrate real-world application.

Presenter / Source

  • Presenter: “Fede” — trader and content creator sharing his personal trading strategy and market observations.

Summary

Fede developed a new trading strategy targeting the first Internal Fair Value Gap (IFBG) during the first 40 minutes of the Nasdaq session (9:30–10:10 AM ET). This mechanical approach focuses on liquidity grabs and defined entry/exit rules, aiming for an 80% win rate and consistent profitability with disciplined risk management. Early backtesting shows promising results with 6% monthly growth on a $50K account. The strategy emphasizes simplicity, mechanical execution, and ongoing refinement through backtesting and community feedback.

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