The strategies discussed in this episode are part of the Alpha Crunching Trade Setups, where we use backtesting and market data to build a portfolio of mechanical SPX strategies.
Members get access to:
Weekly rules-based SPX Trade Setups
Live trade alerts in the Alpha Crunching Discord
SPX trading tools and market statistics
Strategy discussion and live trading chat
Automation options for select strategies
The goal is simple: data-driven SPX trading with repeatable rules and less time watching charts.
👉 Learn more and join at AlphaCrunching.com
What happens when you stop looking for the “best” SPX trading strategy and start thinking in terms of a portfolio of strategies?
In Episode 196, I break down four mechanical SPX strategies based purely on the math — without focusing on the actual strategy or setup.
We compare:
Trade frequency
Win rate
Average winner
Average loser
Expectancy
Risk/reward
The differences are significant. One strategy wins just 35% of the time, while others win more than 70%. But higher win rates come with their own trade-offs, including larger average losses.
The interesting part comes when we combine all four.
Instead of relying on one strategy that might go weeks without a trade or experience a losing streak, the different mathematical profiles can complement each other and produce a much smoother overall P&L curve.
The goal isn't necessarily to find the highest win rate or the perfect strategy. It's to build a collection of positive-expectancy trades that can work together over time.
Would you trade a strategy with only a 35% win rate if it improved the overall portfolio?
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