I was wrong about stop losses on 0dte SPX

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Summary

The author details their experience backtesting an automated 0DTE SPX credit spread strategy, focusing on the ineffectiveness of stop losses.
The author's thesis is that for their specific strategy (selling 0DTE credit spreads based on opening range breakouts), stop losses introduce more problems than they solve, leading to locked-in losses on positions that would have recovered. They conclude that a better approach is to sell higher delta spreads, risk a fixed percentage of capital (30%), and forgo stop losses entirely.
Quality assessment: This is a personal account of a backtesting experience, not well-researched due diligence (DD). It offers insights into the challenges of a specific, high-risk trading strategy but should be considered anecdotal evidence rather than a universally applicable conclusion.

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For context, I trade credit spreads on 0DTE with an automated system ([more info](http://ez-tradebot.com)).

I have a system that relies on detecting breakout moves from the opening range mechanically.

Delta is targeted dynamically from the OR and a fixed delta target. I experimented with many different possible combinations of delta target (3, 5, 10) that the optimizer uses for strike selection.

I reasoned that theoretically, a lower delta target with higher quantity would hold up better out of sample because of something called Skewness Risk Premium - the idea that further out of the money options have higher implied volatility to compensate for how skewed the risk/reward is of the position, making it highly undesirable for institutions to sell those options.

But when I ran the numbers, time and time again stops created more problems than they solved. For one, they locked in many, many losses that ended up recovering the same day. For another, they only worked at low deltas where the stop was never even hit in sample. Stress test scenarios found even setting the stop to a 5 point breach led to a 30-40% loss on the spread. And that's assuming QuantConnect modeled fills well - it honestly will probably be worse live.

Eventually, I reached the conclusion that from a risk management perspective, trying to harvest too much skew and compensating with quantity is not a good idea.

Fills end up being worse than the backtest modeled, fees end up eating most of the gains, and worst of all, there is the existential risk of having to risk the entire account and hoping that the code you wrote for the stop loss actually works that one day when it's all on the line.

Ultimately, I found stop losses just don't work in 0dte credit spread selling, the way I was doing it. Even set very, very far OTM, the stop loss ends up being more of a liability than anything. It turns out the extra Sharpe I found in my first iterations was just luck having to do with setting the starting capital to 10K.

When I changed the starting capital to 20k, it actually underperformed the more robust version I now use - risk 30% and use no stops, and sell higher delta.

Ideas

u/Right_Business9301 Reddit r/options

The author's backtesting of an automated 0DTE SPX credit spread strategy showed that using stop losses consistently underperformed a strategy without them. Stops locked in losses on positions that often recovered by the end of the day. This suggests that the intraday volatility of SPX makes tight stop losses on short-premium 0DTE strategies counterproductive. The author's revised, more "robust" strategy involves forgoing stops, selling higher delta spreads, and accepting a predefined maximum risk (30% of capital). The author advocates for a specific approach to selling 0DTE SPX credit spreads: no stop losses, higher delta strikes, and a fixed risk percentage. This is presented as a more robust system than trying to sell very low delta spreads with stops. This strategy carries extreme risk. A "no stop loss" approach on a 0DTE spread, even with a predefined capital risk, can lead to catastrophic, account-wiping losses in a black swan event or a sharp, sustained intraday trend. Backtest results may not reflect real-world execution (slippage, fills).

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