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Deflow After 11 Trading Days: Right on Small Caps, Wrong on Large Caps

Deflow, a volatility-regime options desk from the Alpaca AI Trading Agents Hackathon, is down $8,355 in its first 11 trading days on paper. Its IWM trades made money; bullish put spreads on QQQ and SPY ran into a sell-off. Here is what happened, and what we think it does and does not tell us.

Strategy by Ifeanyichukwu Onwo (@mrnetwork0001) · October 17, 2026 · Data as of the October 16 close · Strategy page

At a glance

Total P&L −$8,355 Oct 2 – Oct 16
Return −7.58% on $110,189 capital base
Realized +$4,424 closed trades
Open −$12,779 six spreads, marked to market

Most of the loss is still open. The closed trades are profitable, but the six spreads still on the book are marked $12,779 below where they were sold. Whether this turns into a realized loss depends on what the market does before those spreads are closed or expire.

What Deflow is designed to do

Deflow was built by Ifeanyichukwu Onwo as a finalist entry in the lablab.ai × Alpaca AI Trading Agents Hackathon (source on GitHub). It runs like a small options desk, cycling every five minutes during market hours across SPY, QQQ, IWM, NVDA, AAPL, MSFT, AMD and TSLA:

Exits are rule-based. A spread is stopped out at 50% of its maximum loss, profits are taken at 75% of maximum profit (sliding to 40% as expiry nears), and everything is closed with three or fewer days to expiry.

Results by underlying

UnderlyingRealizedOpenTotal
IWM+$9,691+$1,009+$10,700
QQQ−$5,267−$10,592−$15,859
SPY$0−$3,196−$3,196
Total+$4,424−$12,779−$8,355

Paper account, October 2–16, 2026. Realized P&L is from Alpaca fill activity; open P&L is each position at its current mark.

The desk only traded the three index ETFs in this period. None of the five single stocks produced a trade.

What happened

The open book tells the story. On IWM the desk sold bear call spreads, a bet that small caps would not rally. On QQQ and SPY it sold bull put spreads, a bet that large caps would not fall.

SpreadContractsCreditNowOpen P&LMax loss
QQQ Oct 30 725/710 bull put16$2.48$9.10−$10,592$20,032
SPY Nov 6 756/748 bull put29$1.20$2.15−$2,755$19,720
SPY Nov 6 752/737 bull put7$2.24$2.87−$441$8,932
IWM Nov 13 283/287 bear call35$0.98$0.72+$910$10,570
IWM Nov 20 286/290 bear call2$1.04$0.58+$92$592
IWM Nov 6 280/282.5 bear call1$0.66$0.59+$7$184
Total−$12,779$60,030

Credit and current value are per share for the spread as a whole. Max loss is the spread width less the credit received, times contracts × 100.

The QQQ spread is the problem. The short 725 put was sold for $7.02 and is now marked at $22.17. QQQ closed Friday at $709.80, below both strikes, so if it stays there the spread will be worth its full $15 width at expiry and the maximum loss will be realized. The spread sold for $2.48 is now worth $9.10. SPY closed at $763.25, still above its short strikes of 756 and 752, so its two spreads are down much less.

Taken together, the book was positioned for large caps to hold up and small caps to stay capped. From the October 9 close to October 16, QQQ fell 5.5%, IWM 3.1% and SPY 2.0%. Small caps fell, so the IWM bear call spreads worked. The bullish large-cap spreads did not, and QQQ, the most volatile of the three, fell the furthest.

The losing trades are not independent of each other. SPY and QQQ usually move together. Two bullish put spreads on them are close to one larger bet on the same outcome, and the per-symbol limit does not treat them that way. We look at this in more detail in Are SPY and QQQ Credit Spreads One Bet or Two?

Where the live book differs from the design

These are differences between the deployed configuration and the published description. They are not necessarily flaws in the strategy's logic. A desk that sizes as designed would have lost roughly a tenth as much on the same trades.

Limitations

What we will watch next week

Results are from a paper-trading account and do not reflect real money. Paper results may differ materially from live trading. Past performance does not guarantee future results. This note is research and education, not investment advice or a recommendation to trade any strategy or security. Options involve substantial risk and are not suitable for all investors.

Deflow was created by Ifeanyichukwu Onwo and is published on GitHub. AI Velocity Trading runs it on a paper account for research and evaluation.

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