Why I Can't Show You My Risk Management (It Would Kill Prop Firms)

Why Risk Management Cannot Be Shared

Introduction to Risk Management

• The speaker addresses repeated requests from viewers for insight into their risk management strategies, stating that sharing this information is not feasible.

• Emphasizes that risk management involves specific parameters like stop-loss, profit targets, and position sizes tailored to individual accounts.

Complexity of Risk Management

• Highlights the multitude of prop firms and account types, indicating that there are numerous combinations of risk management strategies to consider.

• Discusses different states of funded accounts (new, in drawdown, in profit), further complicating the ability to share a universal strategy.

Personal Experience and Testing

• Shares personal journey of two to three years spent understanding these values and emphasizes the importance of testing one's own strategies.

• Advises viewers to backtest within the specific environment of their chosen prop firm rather than relying on generic equity curves.

Expected Payout Calculations

• Suggests calculating expected payouts based on past performance across multiple funded accounts to determine profitability.

• Introduces a bias-based trading strategy where entry criteria are less rigid but still aligned with overall account rules.

The Importance of Customization

• Explains that effective risk management is an entire system involving simulations for optimal take-profit and stop-loss settings tailored per account type.

• Warns against sharing detailed systems publicly as it could undermine the viability of prop firms due to widespread exploitation.

Different Account Environments

• Outlines three key environments: evaluation (eval), funded, and live accounts, each requiring distinct optimization approaches.

• Stresses that while net returns matter for live accounts, eval accounts focus on reaching targets without losing the account.

Tracking Performance Metrics

• Instructs traders on what metrics matter most at each stage: optimizing for cash withdrawals in funded accounts versus pass rates in eval stages.

• Encourages tracking balance changes relative to maximum loss limits and payout eligibility over time.

Optimization Strategies

• Discusses how thousands of data points can be simulated for various outcomes based on different balances and drawdowns.

• Mentions maintaining a small group actively trading under similar conditions as a way to preserve competitive advantage.

Cost-Benefit Analysis

• Provides an example using cost analysis for acquiring a funded account through evaluations with varying success rates.

• Illustrates how costs do not equate directly with value; instead, future payouts should be considered when assessing worth.

Expected Value Calculation Examples

• Demonstrates calculating expected value based on hypothetical payout scenarios using probabilities tied to win rates.

• Explains alternative methods for determining potential profits from multiple payouts across different states of funding.

Drawdown Considerations

• Compares risks associated with fresh versus profitable funded accounts highlighting differences in value post-loss.

Conclusion: Building Your Own System

• Urges viewers not just to copy others' strategies but rather develop personalized systems through rigorous testing tailored specifically for their circumstances.