The LPMT Strategy: The Undiscovered Pattern That Crushes The Market

Key Concepts

Base Rate Fallacy: A cognitive bias where individuals focus on specific, visible signals or results while ignoring the underlying frequency (base rate) of an event occurring naturally.
LPMT (Lunar Phase Market Timing): A hypothetical, ineffective strategy used to illustrate how "scientific-sounding" theories can mask poor performance.
Base Rate: The underlying frequency or probability of an outcome occurring without the application of any specific strategy or intervention.
Survivorship Bias: The logical error of concentrating on the people or things that "survived" some process and inadvertently overlooking those that did not, leading to false conclusions.
Expectancy: The average amount a trader can expect to win or lose per trade, which is more critical than win rate alone.
Leverage: The use of borrowed capital to increase the potential return of an investment, which often creates the illusion of skill.

1. The LPMT Strategy and the Illusion of Skill

The author introduces the Lunar Phase Market Timing (LPMT) strategy as a case study in deceptive financial modeling. The strategy suggests leaning bullish during a waxing moon and bearish during a waning moon, based on the theory that lunar gravity influences stock movements.

Performance: In 2025, the strategy returned 25%. While this sounds impressive, the S&P 500 returned 18% in the same period.
The Fallacy: A 2:1 leveraged portfolio should have returned 36% based on the market benchmark. The LPMT strategy actually underperformed the benchmark, yet it was framed as a "scientific" breakthrough. This demonstrates how leverage is often mistaken for trading skill.

2. The Base Rate Fallacy in Finance

The core argument is that traders frequently fail because they ignore the base rate—the natural tendency of the market to produce certain outcomes regardless of the strategy applied.

Definition: The fallacy occurs when one assumes that because an event happened after "X," "X" must have caused it.
The "Compared to What?" Framework: This is the most critical question a trader can ask. Without comparing a strategy’s performance to the baseline (what would happen if you did nothing or traded randomly), a high win rate is meaningless.
Example: A "crystal ball" that predicts roulette outcomes with 95% accuracy is useless if the bet is simply "not landing on zero or double zero," as that is the natural probability of the game. Accuracy is not synonymous with insight.

3. Why Win Rates are Deceptive

The transcript argues that win rates are the most dangerous metric in trading.

High Win Rate Trap: Strategies with high win rates (e.g., 80%) often harvest "base rate noise" while exposing the trader to catastrophic tail risk (large, infrequent losses).
Strategy Comparison:
- Strategy A: 80% win rate, occasional large losses.
- Strategy B: 40% win rate, occasional large gains.
- Insight: Traders often prefer Strategy A due to psychological comfort, but Strategy B may be superior because it exploits a genuine edge rather than just harvesting baseline probability.

4. Backtesting and Survivorship Bias

Backtesting is identified as a primary vehicle for the base rate fallacy.

Data Mining: If one performs enough random tests (e.g., 1,024 coin flips), some will inevitably produce a "10-heads-in-a-row" streak. Claiming this streak is a "validated strategy" is a statistical error.
The "Not in a Row" Problem: Referencing a joke by Steven Wright, the author notes that many trading strategies are like a store that is "open 24 hours, just not in a row." A strategy might show significance once, but it lacks the persistence required to be a true edge.

5. Actionable Defenses Against Bias

To avoid falling for trading folklore, the author suggests:

Measure the Baseline: Always ask, "What happens if I do nothing?" If the strategy does not improve results relative to the base rate, it is not an edge.
Identify Leverage: If a trade returns 400%, determine if that return is simply the result of leverage or a repeatable signal.
Demand Repeatability: Distinguish between a one-time "lucky" backtest result and a persistent, repeatable market phenomenon.

Synthesis and Conclusion

The main takeaway is that the financial industry often packages "base rate behavior" as proprietary, high-probability trading edges. Traders are encouraged to stop obsessing over win rates and "scientific" indicators, and instead focus on whether their strategy provides a genuine, repeatable advantage over the market's natural baseline. True competence in trading is found by stripping away the noise of visible signals and understanding the underlying statistical reality of the market.