Video summary

World Champion reveals: The PERFECT risk-reward ratio (RRR) in trading!

Main summary

Key takeaways

Finance

Core idea / framework (risk & money management)

The presenter argues that sustainable trading returns come from mathematical expectancy, driven by:

  • Hit rate (win probability)
  • Risk-reward ratio (RRR)
  • Position sizing / account risk per trade

He emphasizes the distinction between:

  • Money management: how much of total capital to deploy (risk capital per trade)
  • Risk management: how to limit losses to preserve capital

Step-by-step “setup math”

  1. Define in advance:

    • Entry level
    • Stop-loss level
    • Target/exit level (take-profit)

  2. Compute RRR

    • Compare the distance to the stop vs. the distance to the target.

  3. Choose capital risk per trade

    • Examples: 1%, 0.8%, 0.5%, 2%

  4. Convert risk into position size

    • Determine how many contracts are allowed so the stop distance corresponds to the chosen % risk.
    • Include tick value/points and fees in the calculation.

  5. Check feasibility

    • If the stop is so large that the resulting contract size is too small (can’t trade, e.g., 0.X contract), switch to a different instrument/product.
    • Example given: DAX futures → FTXM

  6. Test with an equity curve / simulator tool

    • Maximum drawdown
    • Outcome distribution over repeated trials (e.g., 100 trades, 20 runs)

Key explicit recommendation / risk limit

  • Set a maximum drawdown of 20% for the entire trading business/portfolio.
  • Rationale: as drawdown grows, the amount needed to recover rises nonlinearly (large drawdowns require very high percentage gains to return to breakeven).

Key numbers & examples mentioned

Break-even / recovery math examples

  • If you lose 20%, you must earn 25% to return to breakeven.
  • If you have a 35% drawdown, he claims you need roughly 42% to 66% to recover; summarized as needing about ~50% (average) to get back to zero.
  • If you lose 80% of assets while still risking 2% per trade, he illustrates that you’d need to earn ~400% to break even (extreme example to show the danger of large drawdowns).

“Do you need a high hit rate?” argument

He claims hit rate is not the decisive factor by itself; RRR and drawdown constraints dominate.

Example A (intraday breakout / momentum-like trade)

  • Hit rate: 70%
  • RRR: about 1.1
  • Trades simulated: 200
  • Risk per trade: 1%
  • Reported result:
    • Drawdown ~10–11%
    • “Awesome equity curve”
    • Average/estimated earnings shown via simulation: about 170K (given as a midrange between 290K and 90K)

Example B (swing trading / lower hit rate with higher RRR)

  • Hit rate: 50%
  • Risk per trade: 0.7%
  • Max drawdown cited:
    • one example: ~6.8%
    • another example: ~14%
  • RRR: 2.5 to 1
  • Reported result:
    • Average earnings cited: about 250K
    • Range around 90K to 370K
    • Average ~180K mentioned

Simulation tool outputs / drawdown constraint driving risk

  • Scenario:
    • Hit rate 35%, RRR 3.5:1
    • 100 trades, 20 simulation runs
    • 1% risk per trade
  • Largest drawdowns cited: 17.3%, 20.3%, up to 26%
  • Conclusion: this can exceed the 20% max-drawdown rule

Risk reduction attempts:

  • With 0.8% risk, drawdown still over 20%
  • He arrives at 0.5% risk as the level where it becomes acceptable (for that scenario)

“Low hit rate can still work mathematically”

  • Example setup:
    • Target: 100 points away
    • Stop-loss: 20 points away
    • RRR = 5
  • He argues the trade could be mathematically profitable even with 20% hit rate.
  • Emotional caution: such low hit rates are hard to endure psychologically, even if mathematically valid.

Instruments / tickers / markets mentioned

  • DAX futures (explicitly referenced)
  • FTXM (used when sizing/feasibility breaks down)
  • S&P (mentioned generally; no specific ticker/ETF provided)

No other specific equities tickers, ETFs, bonds, commodities, or crypto tickers were provided.

Cost-of-living / feasibility calculator (wealth vs living expenses)

A cost of living calculator is used to test whether trading can fund lifestyle.

Assumptions mentioned:

  • Living expenses require income over 18 full trading days
  • Contract value described as: $5 per point (or €5 per point in another scenario)
  • Initially described using one contract
  • With a realistic 20% drawdown, he states you won’t earn enough for living costs under these assumptions
  • Lifestyle break-even requires:
    • about 12 points per day (from “one instrument per day”)
  • To build wealth, he says you need:
    • about 20 points per day
  • Another scenario:
    • Trading 4 contracts each with $5/€5 per point
    • Still tied to meeting sufficient daily points targets
  • Disclaimer note: “I haven’t included any taxes here.”

Disclosures / cautions

  • The transcript does not include an explicit “not financial advice” statement.
  • Repeated cautions include:
    • Drawdowns must be kept ≤ 20% or recovery becomes extremely difficult.
    • High hit-rate traders often still fail if targets/stops and RRR aren’t defined.
    • Low hit rates with high RRR may be emotionally hard to stick with.

Presenter / sources

  • Presenter: “Tom” (referred to as Tom throughout; full name not provided in the subtitles)

Original video