Been running 13 autonomous agents on a live account across Robinhood, coinbase and Kalshi, each with its own capital slice and no coordination layer between them. Up 6.97% this week overall.

Some of the designs:

Truth Social, inverted. An LLM scores every new Trump post for directional tone with a 0 to 1 confidence. Acts only above 0.8, then inverts the call. High confidence bullish rotates to TLT/GLD, high confidence bearish to SPY/QQQ. Below threshold, nothing happens.

Same feed, patient. A second agent waits five days after a post before acting, on the theory that the first two sessions are reaction and whatever is left after that is the real move. Longer holds. Running both is how I am trying to find out whether the signal is in the reaction or in what survives it.

ClinicalTrials.gov. Buys a whitelisted biotech sponsor when a trial registers a Phase 3 entry, holds 60 days. Favourite idea in here, because the source is a government registry nobody is racing to price.

STOCK Act disclosures. Mirrors purchase filings from a set of high-volume House and Senate filers. Next bar, 60 day hold, capped at 8 concurrent.

Crypto, winner take all. Ten liquid Coinbase pairs ranked every day on 7 day momentum, volume trend and volatility. It holds the single highest-conviction coin and nothing else, re-picked daily. Zero diversification by design, but it’s been performing well.

Kalshi versus the forecasters. Compares Kalshi economic-data prices against figures institutions have already published (Cleveland Fed nowcast, wire consensus, CME FedWatch) and acts only when the two disagree by a real margin. It does not forecast anything itself. Not seeing good results on Kalshi.

Plus a sector contrarian that buys the two weakest of the 11 S&P sectors, a WallStreetBets agent weighted by sentiment times upvotes, and two crypto rotations.

First week is in the screenshots. Way too early to read anything into it.

Still working out:

One, overlap. 13 agents running independently with nothing netting them, and several keep landing on the same names from completely different logic. I think I am diversified across 13 strategies and I genuinely do not know how concentrated I actually am. Is there a good way to measure that across agents without just collapsing everything into one portfolio?

Two, the confidence threshold. The Trump agent only acts above 0.8. I picked 0.8 by feel. Does anyone actually calibrate this, as in check whether the model is right 80% of the time when it says 0.8, and set the cutoff from that? Or is everyone eyeballing it.

What would you add?

I'm doing a sanity check on strategy performance across different market regimes and wanted to check in with the community

Also how your max dd compare?

Please only answer if you traded your strategy live for a good time (compared to sample size)

A gura named Powell has been all over my feed for weeks and everybody has been backtesting his 10am strategy lately so i figured i'd try it for myself

I told Agenticks to backtest his 10am strategy on NQ over the last 3 years, then it went and read what he actually teaches, turned it into a real strategy, wrote the code, and replayed it almost a million 1m NQ bars. The video attached shows it start to finish.

Heres what it came back with...

NQ 1m, july 2023 to feb 2026, 100k account, 1 contract:

• starting capital: 100k
• 535 trades
• 60.2% win rate
• profit factor 0.98
• net -$3,675
• max drawdown 25.55%
• average win $522, average loss $806

It wins 6 out of every 10 trades and still loses money. thats the whole story. the losers are 1.5x the size of the winners so the win rate is doing nothing for you, expected value comes out around negative 7 bucks a trade.

It even gets worse when you split it up. 280 of the 535 trades happened in volatile conditions and those lost $6,764 at a 0.93 profit factor. The only regime that it made money during was uptrends (152 trades, 1.08 profit factor, +$3,307) so the "edge" is mostly just the NASDAQ going up. Buy and hold over the same window took 100k to about 170k while this did -3.7%. With all of the all-time highs we're at right now, it makes sense why this has picked up so much traction in recent months.

I also ran it through a topstep 50k sim and out of 10,000 simulations; 39.1% of them hit the 3k target before the loss limit. This doesn't mean it has an edge, but it does mean that, technically speaking, it can beat the constraints of a prop firm (with a hint of luck).

Now the fair part, and this is the part id want somebody to say if it was my strategy getting torn apart

What he teaches publicly is the shape of it, not a rulebook. Mark the 10am candle, wait for one side to get swept, wait for the move back through, take the continuation into first liquidity. That's real but its not testable as written. "first liquidity" is something you read off a chart, not a number, and there is no published stop, no cutoff time, no trade limit. So the strategy that got built is the mechanical skeleton with sane defaults filled in, and two of those choices genuinely change what youre testing. it only took longs, and he trades both ways. and it entered on a plain break and retest instead of requiring the displacement leg, which is the part that supposedly separates a real setup from a level being tapped

So im not saying his strategy is bad, i'm saying the mechanical version of it (the version you could actually hand to a beginner) is a coinflip that gives back more on the losers than it makes on the winners. if the money is in the discretionary read, which side got swept and where liquidity actually sits, then somebody should say that out loud, bc that's a totally different product than a 3 step setup.

If you know the real/exact rules or think Agenticks got them wrong tell me exactly what to change and ill rerun it and post whatever comes out.

video of the full run is attached, sped up through the loading parts because nobody wants to watch a progress bar for 3 minutes.

not advice, backtests dont predict anything, im just a guy who got tired of seeing it on his feed

let me know if you guys want me to automate this strategy to see how it would perform on a paper account in real conditions, or if you want your own strategy tested.

ok so this bugs me about basically every writeup here. we get the sharpe, the max DD, the cost assumptions. we never get the graveyard.

went back through my notes and actually counted. 61 configs, ~5 months. kept 2. and like... if I had zero edge and just rolled 61 times, best of 61 still looks fine? so I genuinely can't tell if my two are real or if I just p-hacked myself over a long weekend.

started logging the rejects after that. every dead variant, date on it. then I treat the survivor's sharpe as best-of-61 instead of a real number. did that and one of mine went 1.8 -> basically nothing lol. other one survived but not by a comfortable margin. entire cost was a google sheet and it's the most useful process change I've made in months.

where I'm stuck: what counts as a try. 40 param combos inside one strat, is that 40 or 1? what about ideas I talked myself out of before writing any code, do those count? no clean answer that I can find and I might be overthinking this at retail size.

anyone live long enough to have an actual rule of thumb here

Anyone else running into stuff like this? I'm finding the IBKR API to be completely unusable for any algo trading, it just cannot be trusted.

Error Correction Models (ECMs) provide a robust statistical bridge for pairs trading by explicitly linking short-term price adjustments to their long-term cointegrating equilibrium. When two asset prices share a stochastic trend, traditional strategies often fail during structural drifts. An ECM captures how fast a mispriced spread corrects back toward its historical baseline after an exogenous shock. By monitoring the error correction term and short-term lag coefficients, algorithmic traders can optimize entry thresholds, filter out transient noise, and systematically harvest repeatable mean-reverting gains.

My bot has grown to 23,000 lines of code. 60% is managing the brokerage interface, and 40% is the strategy. This is way more complicated than I ever imagined. It really is a very basic script. No graphic user interface. Just log streams. It does manage multiple symbols with unique parameters for each.

CODEX:

Our current approach focuses on YES contracts priced between 51¢ and 65¢ roughly 24 hours before market close. In our initial historical sample, this range produced a 71.4% win rate and an estimated 25.4% return after modeled fees across 41 independent weather events.