
π Trade These SPX Setups With UsThe 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 SetupsLive trade alerts in the Alpha Crunching DiscordSPX trading tools and market statisticsStrategy discussion and live trading chatAutomation options for select strategiesThe goal is simple: data-driven SPX trading with repeatable rules and less time watching charts.π Learn more and join at AlphaCrunching.comWhat happens when you stop looking for the βbestβ 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 β without focusing on the actual strategy or setup.We compare:Trade frequencyWin rateAverage winnerAverage loserExpectancyRisk/rewardThe 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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198: How I Used Gamma Exposure to Build a Risk-Free 0DTE XSP Options Trade

197: XSP 0DTE Strategy: Better Risk-Reward With Credit Spreads

195: The Friday-to-Monday SPX Edge

194: Does Gamma Move the S&P 500? What SPX Traders Should Know
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