u/OptionsJive

Hi, I saw this on arXiv this week (lead author at Carnegie Mellon) and figured this sub would have opinions.

They trained a 27B model to trade options on SPY and 9 big names like NVDA, TSLA and PLTR, the AI only picks the type of trade, like a long straddle, fixed rules pick the strikes, size it and delta hedge, the out-of-sample test ran March to August 2025, so it traded straight through the April tariff mess.

They trained two versions from the same starting point. One could read news and SEC filings, while the other only saw market data like IV vs realized volatility, term structure, skew and option flow.

	No news	With news
Return	+18.3%	-2.7%
Max drawdown	-9%	-31.7%
Win rate	29%	39%
Avg win / avg loss	4.7	1.4

The win rate is what got me; the news version won more often and still lost money. The other one lost on about 70% of its trades and still made 18%, because its winners were almost 5x its losers.

News did help earlier in the pipeline, when they used it to generate training examples from a bigger model. It only hurt once the model kept reading it while learning to trade for profit.

I sell premium and ignore headlines, because by the time news hits my phone it's already in the IV. Full paper: https://arxiv.org/abs/2610.10407

Anyone here have a trade where the news gave you an edge the options weren't already pricing?

Many people here trade options on leveraged ETFs.

I simulated TQQQ back to QQQ's inception in March 1999, with financing costs and the fund's expense ratio built into the model. Almost every leveraged ETF discussion eventually runs into assumption 3x daily leverage should produce something close to 3x the long-term return.

The pre-2010 series models 3x daily exposure to QQQ, with financing costs on the borrowed notional and the fund's expense ratio subtracted daily. Starting in 2010, the simulated series is spliced directly into TQQQ's real, traded adjusted price history, so everything after that point comes from actual market data.

The results, $10,000 invested in March 1999:

• QQQ: $10,000 → $167,265 (11% annualized)
• TQQQ (simulated pre-2010, real data after): $10,000 → $24,569 (3.4% annualized)

Maximum drawdown over the same 27 years:

• QQQ: -82.96%
• TQQQ: -99.98%

A -99.98% drawdown means every $10,000 at the peak fell to $2 at the bottom. TQQQ carried far more risk the entire way and still finished with $14,569 in total profit against QQQ's $157,265, under 10% of the unleveraged return.

The volatility drag (beta slippage) scales with the square of the leverage multiple. Double the leverage and the drag roughly quadruples, triple it and the drag runs close to nine times larger. That is why I don't trade options on leveraged ETFs. You would be layering theta and IV risk on top of an instrument that is already decaying by design and has never been tested by the environment that would break it.

Look at this: SpaceX options, day one, pure backwardation, front-month IV north of 100%, curve sloping into next year.

Now read the 424B4 - the lockup isn't a December cliff, it's staggered: 20% after Q2 earnings in August, then 7% tranches every few weeks, then 28% in a single shot after Q3 earnings in late October/November. December is just the leftovers.

There's also a conditional pull-forward nobody's talking about: another 10% unlocks early if SPCX holds 30% above the $135 IPO price, $175.50. It's at $216 now.

Clean backwardation makes sense when near-term uncertainty resolves into calm, but this supply schedule steps hard in August and then again in November. If you're selling December because lockup cliff, you might be trading the wrong expiry.

What are you guys playing and how are you positioning around November?