My quant system always destroyed by just buying TQQQ....
Author's complex AI quant system failed to beat simple DCA into TQQQ, now seeking ways to mitigate its massive drawdowns.
- TQQQ's long-term returns are so robust that even an advanced, adversarial AI quant system failed to generate alpha against a simple DCA strategy.
- TQQQ is subject to extreme volatility and devastating drawdowns (e.g., -80%), making it difficult to hold without a robust hedging or timing strategy.
I spent months building an AI quant system. It got destroyed by just buying TQQQ
Solo, paper only. I had two AIs adversarially review each other — one builds a strategy, the
other tries to STOP it. Ran it across 8 generations: factors, ML, leverage, market timing,
intraday, events.
All dead. Every signal that became verifiable turned out to be beta, not alpha — information
theory, the hard way. The whole thing lost to just DCA-ing TQQQ. (The AI caught my own look-ahead
bugs twice. Humbling.)
I've given up beating TQQQ on return. I just want to lose less in its −80% drawdowns — enough to
justify not just buying it and walking away. But every timing attempt lagged the crash.
Is there ANY robust way for a solo to cut a TQQQ-like drawdown without killing the upside? Or is
"you can't, just size down" the honest truth?
Everything's open — code, the AI validation pipeline, charts. Roast me:
are you projecting?
To be fair, I frequently write in 2-3 word sentences. So did Earnest hemmingway. Chuck Palahniuk. Cormack McCarthy.
👍🏻 the best thing I learned in college English was to trim your writing to its simplest, most direct form.
And you lose 80% of your port in choppy or prolonged bear market still
bro you need to get that checked by a doctor
thanks for the backtest, i would not be strong enough to hold this setup but it would probably feel awesome to reinvest my super sqqq gains in tqqq when the market turns back on!
I already did all that, spent years trying the same. Then I switched to QLD and been at peace with myself knowing I might no get the same results, but I'll recover from any drawdown.
Btw there are 2x Daily resets
2X? 1.5X? Both exist
Positive cashflow. I never need to sell shares to pay my bills. At some point that DCA will not meaningfully impact my average share price. Dec 2021 to DEC 2024 was just more time to pick up more shares cheaply. No real loss.
You're doing it wrong. Only buy tqqq when its low and sell when its high. test that!
It's called getting credit from a bank
2X? 1.5X? Both exist
This is a README read, not a code audit — so caveat everything below as an evaluation of what the repo claims about itself. With that said, it's an unusually honest artifact, and the honesty is also where the most interesting overclaims hide.
What's genuinely strong
The validation harness is the real contribution and they're right to say so. Next-bar fills (signal t → fill t+1), OOS plus a final holdout, after-cost and turnover accounting, pre-registered kill conditions, and a self-built survivorship-free S&P 500 at 0.998 correlation to SPY — that's a more disciplined setup than most retail and a fair amount of published quant. The detail that the adversarial review caught their own look-ahead bug twice, and that the intraday ORB/VWAP/RVOL "alpha" died the moment the leak was fixed, is the tell that the machinery actually bites. Most people never find those bugs because they're not looking; finding them and publishing the corpse is the opposite of the usual selection bias.
The separation of TQQQ (raw-return foil) from SPY/QQQ (risk-adjusted benchmark) is also correct and rarely done. And the −18% MDD vs TQQQ −80% framing is the only honest axis on which the survival core "wins," which they say.
Where the framing outruns the evidence
The slogan — "the moment a signal becomes verifiable, it's beta/factor, not alpha (information theory, in practice)" — is rhetorically clean and not true as stated. Verifiable to you in your own OOS is not the same as publicly known and arbitraged away. There's no information-theoretic theorem turning verifiability into beta. The defensible version is narrower: signals a solo can build from free/cheap data using standard factor and trend constructions tend to already be priced. That's a real and well-supported claim, but it's a statement about their search space, not about verifiability per se.
The "8 generations, all rejected" denominator is weaker evidence than the README's top implies. Those eight families are mostly correlated walks through the same conventional terrain — cross-sectional factors, trend, leverage, VRP, reversal, event drift — run through a single 2016–2026 bull with one COVID V-shape and no dot-com or 2008. Absence of alpha across eight correlated conventional approaches in one regime is strong evidence for the scoped claim and weak evidence for the universal one. To their credit, the bottom of the README retreats to exactly the scoped claim ("scope-conditional… not a universal claim," consistent with SPIVA). So the real problem is internal tension: the punchy headline asserts more than the careful footer is willing to defend.
"Dynamic market-timing = REJECTED, −113%p, 4-for-4, lagging-signal wall" is a strong, falsifiable result — but it's regime-conditional in a way the phrasing hides. In a low-vol grinding bull, any defensive overlay lags and costs you by construction. That's not a law about timing; it's what timing looks like in this specific sample. The "wall" is partly the regime.
The one thing I'd want a number on
The "avoid bad filings" 8-K survivor is the most interesting concrete finding, and it's consistent with the known asymmetry that negative information incorporates more slowly (short constraints, attention effects). But "survives" needs the receipts: OOS effect size, t-stat, after-cost, turnover, and crucially whether it's just a low-quality/short-side screen in disguise — i.e. beta again. Without that it's a qualitative claim sitting next to a quantitative apparatus.
Bottom line
The epistemics are better than the conclusions. As a validation OS and a negative-results record, it's credible and worth more than most repos claiming the opposite. As an argument that "there's no easy solo alpha," it has earned the scoped version and is borrowing against the universal one. The branding ceremony (PRAMANA / PYTHIA / council.sh / adversarial Codex) is orthogonal to whether the harness is sound — but heavy ritual around a search that found nothing is at least worth a raised eyebrow about effort-to-signal ratio.
If you want, I can clone it and actually audit the validation harness — specifically whether the next-bar logic and the PIT universe construction are leak-free, and whether the 8-K survivor holds up — rather than taking the README's word for its own rigor. That's the part worth verifying directly.
ai replying to ai lol

r/letfs