This Shocked Us (High Probability vs Low Probability)

The Iron Condor Strategy and Initial Results [00:00:51]

• The strategy involves selling an out-of-the-money call credit spread above the market and an out-of-the-money put credit spread below the market.
• The goal is to collect premium while benefiting from time decay and a potential decline in implied volatility.
• Over six years, this strategy generated over $17,000 in profits after commissions and fees, using $25,000 in planned capital, resulting in a cumulative return of approximately 68% with minimal drawdowns.

  "Over six years of back testing this iron condor generated more than seventeen thousand dollars in profits and when we did that we did it with relatively low drawdowns"

Performance Fluctuation and Capital Context [00:02:09]

• Yearly performance showed significant variation, with nearly $12,000 in profits in 2021 but near losses in 2020 and 2025.
• A profitable strategy does not guarantee profit every month or year; managing drawdowns during difficult periods is crucial.
• Returns are measured against allocated capital ($25,000), not just premium collected or buying power, to provide context for strategy evaluation.

  "Making 17 000 sounds great but we also need to understand how much capital we're allocating to generate that return"

The Foundation: A Repeatable Trading Plan [00:03:23]

• Developing a strategy requires a robust trade plan with clearly defined rules for entries, adjustments, profit-taking, and exits.
• This plan must be backtested over different market environments to ensure positive expectancy.
• The plan's components include: entry (when, how far out, structure), adjustments (predetermined rules for market moves against the position), profit-taking (rules for exiting profitable trades), and maximum loss (defined before entry, with a time-based exit).

  "First is our entry we know when we're entering how far out we're going and how we're going to structure the position"

Seeking Additional Edge: Beyond Mechanics [00:05:21]

• The remaining 20% of strategy improvement involves finding more edge without altering the core mechanics.
• A common mistake is changing rules based on backtest results to make them look better, leading to curve fitting and potential future underperformance.
• Instead of changing mechanics, the focus is on understanding the environment where the strategy performs best, particularly looking at implied volatility.

  "The remaining 20 is looking for ways to improve the strategy without constantly changing the mechanics of the trade"

Analyzing Volatility's Impact [00:06:46]

• Trades were divided into three broad VIX groups: below 15, between 15 and 20, and above 20.
• VIX above 20: generated ~$7,900 profit with a 74% win rate.
• VIX between 15 and 20: generated ~$15,600 profit with a 73% win rate.
• VIX below 15: lost over $6,500, averaging a loss of $363 per trade with a 61% win rate.

  "but now look at vix below 15 those trades lost 6 500 that's an average loss of 363 dollars per trade"

The Power of Knowing When Not to Trade [00:08:36]

• Removing the low VIX trades (below 15) from the backtest increased total profits to $23,574, a 94% return on capital.
• This demonstrates that trading fewer, higher-quality trades can be more profitable than trading more frequently.
• The improvement came from filtering data where the strategy struggled, emphasizing that understanding when a strategy has an advantage is as crucial as knowing how to trade.

  "sometimes improving a trading strategy isn't about finding more trades it's about identifying the trade that might not be worth taking"