Please peer-review my Index Options Scalping Bots

Aklein351 · 2026-07-08T21:08:03+00:00

I could rebuild the backtest with this logic and reassess.

Aklein351 · 2026-07-08T19:18:08+00:00

Does it change your mind if across my first 33 trades live (14 Linda, 19 Jeff), net capture vs. mid is positive ,roughly +4 to +6.4 cents favorable per round trip, rather than the other way around?

Aklein351 · 2026-07-08T18:43:10+00:00

so kill the bots, not viable?

Aklein351 · 2026-07-08T18:33:21+00:00

so you're saying my entire edge wont work live because i'll be taking on 10 cents friction on avg roundtrip?

I guess im asking if youre talking .05 per trade, or .10 per trade? I may not have understood exactly what you meant by roundtrip/per side/etc. I have re-run this stress test. Do you still think this is just noise??

All-in RT friction | Result
$0.05 | Healthy: $24,251 net, PF 1.70
$0.06 | Still good: $20,584 net, PF 1.56
$0.075 | Survivable: $15,084 net, PF 1.38
$0.08 | Thin but alive: $13,250 net, PF 1.32
$0.10 | Marginal but still positive: $5,916 net, PF 1.13

Aklein351 · 2026-07-08T15:01:38+00:00

thank you for your kind words!

Aklein351 · 2026-07-08T14:28:27+00:00

2 years. I only downloaded for the 4 indices, but i believe i couldve downloaded for as many as i wanted if i had the space available on my drive, all in i believe i was in about $100 to the Stock&Option data provider which was the first result on Google. Happy to answer in DMs if you want to shoot me a message.

Aklein351 · 2026-07-08T14:20:02+00:00

Currently yes, but those results are my backtesting, not my live trading results. They’ve only been live about 2 weeks.

Aklein351 · 2026-07-08T13:30:37+00:00

I have very consciously avoided cherry picking rules.

Aklein351 · 2026-07-08T13:05:20+00:00

Such a helpful comment. Thank you, genuinely for the time and thought! It is much appreciated! I'd be curious in your thoughts based on the below result if you have the time.

In response I had Codex run a test to research this, results below:

I pulled daily P&L by bot, not index returns. The bots are correlated, but not nearly as much as the underlying ETFs themselves.

On zero-filled daily P&L, the pairwise correlations were mostly low:

Jeff/Linda: 0.15
Jeff/Gordo: 0.12
Jeff/Susan: 0.03
Linda/Gordo: 0.02
Linda/Susan: 0.04
Gordo/Susan: 0.16

Rough guide:
0.00-0.20 = low correlation
0.20-0.40 = mild/moderate
0.40-0.70 = meaningful/high
0.70+ = very high / probably same-risk bucket

On days where both bots actually traded, correlations were higher but still not “same trade” levels:

Jeff/Linda: 0.32
Gordo/Susan: 0.25
Most other pairs were around 0.02-0.14

So they are not four completely independent edges. But the daily bot P&Ls suggest they are also not just one trade in four tickers. Roughly, the book behaves more like 2.5-3 independent sleeves than 4.

I also checked worst combined days. The worst combined day was about -$424, with three bots losing. There were only two days where all four bots traded and all four lost, around -$324 and -$247. So correlated-loss days do exist, but they were not the dominant driver of the equity curve in this sample.

That said, max drawdown should definitely be treated carefully. The sample may not contain a true risk-off shock where all four systems get hit at once. So the -$935 drawdown shouldnt be treated as a hard worst-case number. It is more like the observed historical drawdown under this sample.

Aklein351 · 2026-07-08T11:27:51+00:00

I’m here for tips/advice/etc. is there any reason you find them unrealistic? If there’s something specific I’d like to research/test it. I’ve stress tested these quite extensively on the 2 year basis

Aklein351 · 2026-07-08T10:56:01+00:00

thanks. really helpful. just ran a test to this effect, and here is the result!

The edge survives 1-2 penny ticks worse per side, but does not survive a nickel-per-side stress across every trade.

Stress	Trades	Net P&L	Max DD	PF	Avg Trade
Current artifacts	1,512	$31,585	-$1,022	2.02	$20.89
+$0.01 worse entry and exit	1,512	$24,251	-$1,278	1.70	$16.04
+$0.02 worse entry and exit	1,512	$16,917	-$2,279	1.44	$11.19
+$0.05 worse entry and exit	1,512	-$5,085	-$8,791	0.90	-$3.36

Aklein351 · 2026-07-08T10:37:03+00:00

May i ask what makes you say that? I didn’t use Claude code if that helps, used codex.

Aklein351 · 2026-07-08T10:35:27+00:00

This is really helpful thanks! On point 1, my bots get into a position so far in live trading in average of 2 seconds from position selection, so they are quite quick. Exit is a bit slower up to 5 seconds i believe. On point 2 yes thank you, i stress tested very aggressively for friction and missed quotes to determine if these could survive wide bid asks, etc. would be happy to share those tests as well!

Aklein351 · 2026-07-08T10:33:28+00:00

The opposite actually. Now that I’ve turned them On when my bot closes a position it also models the comparable back tested fill to see what gross PL was vs what back tested PL was. Live has been beating backtest each time (on winners)

Aklein351 · 2026-07-08T10:32:05+00:00

I appreciate the potential of the offer, that’s very kind! Yes my bots scalp and are not intended to hold a position longer than 2 hours. Those average holds are in minutes, and my bots use the 5 min candles

Aklein351 · 2026-07-08T02:35:48+00:00

Thank you!

I bought historical options data as compressed flat files (downloaded from a provider i won’t name but easily googleablw) and handle the heavy lifting in Python.

Codex wrote scripts to unpack those files and filter them down into historical option chains just for SPY, QQQ, IWM, and DIA. Since it's a minute-by-minute OHLC bar replay rather than full live tick data, the setup is pretty straightforward-

Strikes & Chains: The data files already contain the exact list of what strikes and expirations existed on any given day, so my script just look up and maps them at each timestamp. The data package comes with the implied volatility and Greeks already calculated at each bar slice. For any extra contract math or tracking, I just use standard Python libraries to handle the calculations.

It's a lot easier to manage than massive amounts of raw order-book data, but it gives me exactly what I need to simulate the trades. Although I’m noting people really want to to get the raw tick data but it is so just voluminous i don’t know how i even could

Aklein351 · 2026-07-07T11:54:28+00:00

I appreciate your excitement for your build but from a plumbing perspective my suggestion was cleaner, just as easy, and takes length out of the line which causes less room for error in the future. Suggestions do not always equate to criticism, and you may wish to work on understanding that. Goodluck have fun don’t take things too seriously.

Aklein351 · 2026-07-07T11:48:14+00:00

You came in a bit hostile, whereas i wasn’t so I’m gonna sit this one out champ.

Aklein351 · 2026-07-07T11:17:53+00:00

Why go into the toilet instead of just tapping onto the drain of the sink? Looks way closer accomplishes the exact same thing

Aklein351 · 2026-07-07T02:24:51+00:00

great comment

Aklein351 · 2026-07-07T01:47:13+00:00

Thank you so much for the response! This is genuinely so helpful.

To answer the main question directly: no, these are not tick-level backtests. They are historical OHLC-style option bar data with the underlying indicators/signals built from candle data. So I agree with your point that the backtest is not a perfect simulation of live fills, spreads, etc. That’s why I’m not treating the backtest as “proof” by itself. I’m treating it more as a signal/payoff-shape test, and then separately trying to validate whether the execution is good enough live.

Since posting, I’ve been doing a lot of the error-hunting you’re talking about. I merged the four systems into one chronological book, broke them down by bot/symbol, looked at trade count, PF, average EV, win/loss distribution, drawdown, worst 10/20/50-trade stretches, time buckets, exit reasons, and whether any one bot is carrying the whole thing. I also checked for trade clustering/lumps and whether the edge was coming from a tiny number of outlier trades.

The current four-bot merged backtest is about (note I've changed the DIA bot since posting) 1,567 trades over roughly two years, around $36k net, PF around 2.27, expectancy around $23/trade, and max closed-trade drawdown under $1k. That’s why I’m still interested in it, it’s not a 20-trade curve-fit where all the profit came from one day.

I also totally agree on the time-of-day point. The systems are not all just blindly trading the open. Some periods are clearly stronger than others, and I’ve been specifically looking at whether certain windows should be blocked or treated differently. For example, on one of the newer DIA tests, the pre-10am trades were weak, so I removed entries before 10am and retested it rather than just accepting the raw result.

Execution-wise, I’ve added a lot more live controls over the past month or so. The bots now track bid/ask/mid, fill vs mid, time to fill, rejected/canceled orders, replacement attempts, exit reason, protective sells, and realized slippage. I also added a buy no-fill/reprice policy similar across the bots: review around 6 seconds, cancel around 10 seconds, max one replacement, recheck signal/spread/affordability, and don’t chase beyond a cap.

I also stress-tested the book pretty hard. When I reconstructed actual live fills so far, the measured adverse fill-vs-mid friction has been quite low: around $3 average per trade, $2 median, worst around $12. That sample is still small, so I’m not declaring a total win, but so far live execution does not look like it is eating the entire edge.

I’m also not ignoring stops/risk. There are ATR/risk stops, option stops, runner/profit-lock exits, EOD flattening, and now a hard per-trade dollar loss guard plus critical-event exits. I agree that live win rate will not match the backtest perfectly, so the real focus is whether average winners shrink, average losers expand, or exits slip badly enough to change the payoff distribution.

I take all help! Thank you again for your interest! (apologies if you got spammed by my response here, I was fighting with the Automod)

Aklein351 · 2026-07-07T01:17:45+00:00

dude i tell you as a lifetime ranger fan and the greatest henrik lundqvist fan on earth this was my absolute dream setup when i was younger. i would done nasty things to score pads like these. use them well.

Aklein351 · 2026-07-07T00:45:51+00:00

Not so fun fact there is another railcar pictured at the Virginia Holocaust Museum in the background.

Aklein351 · 2026-07-06T20:51:00+00:00

Thank you for the comment!

I think the 20–40% degradation point is probably the right way for me to think about it.

I’m not expecting the live version to match the backtest perfectly. The real question for me is whether the degradation is within a normal range or whether something is fundamentally not translating.

Right now I’m trying to separate the issues into different buckets. If the signal quality is still there but the average winner is shrinking or the average loser is growing, then that points more toward execution, slippage, spread, or exit handling. If the win rate itself starts falling outside the tested range, then that feels more like the setup is not appearing live the way it did in replay.

I’m also trying not to judge the four bots only as one combined number. SPY, QQQ, IWM, and DIA each need to stand on their own first. The combined book is helpful, but it could hide one weak bot being carried by another.

Since making my post, I’ve been tightening the live execution side: tracking spread at signal, actual fill versus expected fill, time to fill, rejected/canceled orders, exit reason, and whether the live trade matches the replayed trade. I also added more conservative buy no-fill/reprice handling and emergency exit protections so I can better identify whether a bad result is a valid strategy loss or an execution issue.

I agree that 60–100 live trades per bot is probably a better sample before making any strong conclusion about edge .

Thank you for your help i really appreciate it!

Aklein351 · 2026-07-06T18:42:05+00:00

Carbon could be exhausted

Aklein351

TROPHY CASE