[Update] Roast my options strategy again, now with 4 weeks of live data (19 trading days)

tuscan21 · 2026-05-09T09:22:30+00:00

=== SUMMARY === - The author presents 19 days of live results from a systematic short-dated options strategy (0–4 DTE) with high returns (+39%), extreme volatility (8.7% daily vol), and a low win rate (42.1%) driven by a few convex winning days. - The thesis is that the strategy may be harvesting a repeatable volatility/earnings edge, but the poster openly questions whether the returns are simply lucky outliers or a genuine, repeatable edge. - This is a well-documented self-analysis with detailed risk metrics and honest skepticism, but the sample size (19 observations) is still too small to draw statistically robust conclusions. === SENTIMENT === MIXED === TRADE IDEAS === No actionable trade ideas in this post. The author does not recommend or imply any specific ticker, direction, or trade. The post is a request for critique of a personal strategy, not a public trade alert. No ticker-based idea meets the minimum confidence threshold (≥0.5) or is explicitly stated/strongly implied.

AI Summary

Summary

The author presents 19 days of live results from a systematic short-dated options strategy (0–4 DTE) with high returns (+39%), extreme volatility (8.7% daily vol), and a low win rate (42.1%) driven by a few convex winning days.
The thesis is that the strategy may be harvesting a repeatable volatility/earnings edge, but the poster openly questions whether the returns are simply lucky outliers or a genuine, repeatable edge.
This is a well-documented self-analysis with detailed risk metrics and honest skepticism, but the sample size (19 observations) is still too small to draw statistically robust conclusions.

Score 15

Comments 12

Upvote % 83%

▶ Full Post Text

Original thread: [https://www.reddit.com/r/algotrading/s/5PYaN8YmIL](https://www.reddit.com/r/algotrading/s/5PYaN8YmIL)

A few weeks ago I posted my first 2 weeks of results and got deservedly roasted for small sample size, tail risk, overfitting concerns, and “this will blow up eventually.”  
Fair enough.  
Now I have 19 live trading days instead of 9, so I wanted to post an update with more metrics and get another round of criticism from people who actually know risk/statistics.  
Strategy trades mostly short dated options (0-4 DTE). Mix of intraday and overnight holds. Fully systematic execution through my own bot.  
Current live results after 19 observations:  
• Total return: about +39%  
• New NAV $110K from $95K  
• April: +18.6%  
• May so far: +18.7%  
• Mean daily return: +2.15%  
• Median daily return: -0.43%  
• Daily vol: 8.7%  
• Max drawdown: 12.87%  
• Sharpe (ann.): 3.93  
• Sortino (ann.): 10.06  
• Tail ratio: 2.5  
• RoMaD: 3.17  
• Win day %: 42.1%  
• Avg win day: +$8.2k  
• Avg loss day: -$3.1k  
• Best/Worst day ratio: 1.87  
• Worst3/TotalPnL: -0.68  
• Time underwater: 63%  
A few interesting things:  
Median day is still negative despite strong total returns.  
This immediately tells me the strategy is NOT “smooth alpha.” It’s driven by convex winners and a few outsized days. Fridays are massively dominant.  
Two huge Fridays account for a large part of total PnL:  
\+13%  
\+22%  
So one major concern is obvious:  
Am I actually harvesting a repeatable volatility/earnings edge, or am I just one lucky Friday away from flat performance?  
Beta to SPY/QQQ is statistically meaningless right now.  
R² is basically zero.  
Confidence intervals on beta are enormous.  
So I’m not claiming market neutrality or true alpha yet.  
Tracking error is absurdly high (\~140%).  
Which makes sense because this thing behaves more like a convex volatility strategy than an equity strategy.  
Distribution is positively skewed.  
Negative median, positive skew, low win rate, large winners &gt;&gt; losers.  
Main things I’m trying to figure out now:  
• Whether the edge is real or just concentrated randomness  
• Whether overnight holds are the actual alpha source  
• Whether intraday trades are mostly noise/whipsaw  
• Whether I should aggressively reduce Monday exposure  
• Whether position sizing is still too large for the observed variance  
• How to distinguish convexity from hidden fragility  
Biggest losing day so far:  
\-11.7%  
Biggest winning day so far:  
\+21.9%  
I know 19 observations is still statistically weak. I’m not pretending otherwise. What I’m looking for from experienced people here:  
• What metrics would you focus on next?  
• What would convince you this is NOT overfit garbage?  
• What hidden risks do you think I’m underestimating?  
• Does this profile look more like genuine convex edge or classic future blow-up material?

Summary

▶ Full Post Text

More from Reddit — r/algotrading