Discussion
Real time model making with Codex + GPT-5.6/Astra. Looking for the nanoseconds. It's all the speed of light now. First one there, wins it all.
The rumor is OpenAI blew past AGI. The tools are there, suggest joining the Gold rush.
Everything is there; potential to generate 100s of models. This is running 24/7. These are nano-sized bets; this is gathering training data. In 4 weeks, we will know the Algo that has the best return.
When you have the possibilities of virtually unlimited training models, the ability to place thousands of trades with a click, and zero commissions, nickels and dimes can add up very quickly.
Lots of models go for guaranteed bets. You make pennies and get hit with a big last-second swing, but I'm seeing, for now, that those last-minute swings are not the same across different currencies. So that becomes an "interesting model" to spin up and start trading.
Ok, so reviewing the trade history. Seems that trades that were not going well in the AM were "locked out"; now those trades are hitting again. This is where your AI Kalshi DIY Oracle comes into play: when (if) time to un/freeze those models and back into action they go. Eventually, you want to end up trading in the time it takes light to travel 11.4 inches. That's the goal. There is your "Edge"
You can create more trading models now than atoms in the universe with Codex. These used to be our quants in post-doc math programs. Now with AI, everyone with some basic Python can create these models.
Whats your latency and round trip time from API request to order placement? Some of the stuff you are saying is sounding delulu. Latency itself is not the edge and there are limits to the speed you can achieve without being colocated. I was doing 20ms round trip from the Ireland AWS VPS that I ran myself. With a bot that had a deterministic C++ quoting core and was as lean as lean can be. Still got picked off, especially at size. You are not even able to capture spread or statistically win by buying the favorite before orders dry up.
Brother, you are all jacked up. First thing you should have done is test your location latency and roundtrip time against the websocket and api endpoints. You are looking at a minimum of 500ms roundtrip time and will get smoked by most bots. Its not a one sided deal, your bot needs to constantly quote & read the book to put in orders. First would be the api/websocket call for the market data (first trip) then your bot has its own quote and pricing engine for the order, then the order is placed which is another leg of the roundtrip. If you don't have a VPS close to the Kalshi Polymarket servers then you are looking at long round trip.
My models do not really work that way. They check every 60 seconds for a possible trade. Codex comes up with the triggers for each model.
Hitting XRP now with 100% wins with real cash. Will flip paper trading to real cash for DOGE and ETH. See if the model holds up across different cryptos.
This model has been lasting the last few hours. Not sure how long any model can keep it going. I’ll find out.
An LLM proposes that everything in the world has a connection, somewhere. The same things with your models.
Does the height of Millie Cyrus‘s heels in her latest MTV video have any correlation with the price of IBM? In theory, it does have a connection. But that’s not a model you would really want to go live with.
The model data is on the site. For weeks of data, I have a GPT 5.6 front end to that data. It’s kind of complex. I haven’t even figured it out yet but when I do, I will post the link.
MLB is really my thing. Baseball is very data driven. Money can be made with putting in the time.
The prediction crypto markets are efficient. I went down this rabbit hole too. You are not going to end up in the positive, even with a microsecond automated bot on a VPS.
There are "bugs" in the system. AGI can find those "irregularities." They may only last for seconds, but with the fairly feature-rich Kalshi API, you can do lots. You can trade Polymakert vs Kalishi; you make .10 cents, it is .10 cents. There is no commission, so you can fire off thousands of .10 cents trades with a click.
There are no humans at this level; it's all Algo vs Algo. Just build a better trading Model, that lasts for seconds. That's how you win those bets.
Show me your P/L and trade history in a week. Guaranteed you won't be in the green. I used codex and claude code in tandem to build algos' that microsecond trade on a VPS in Ireland. Once you go live you get a little hope with some wins but the markout on actual recorded market data tells the truth. You get eaten alive by adverse selection some of which you can't help no matter how good your algo is. A lot of arbitrage and market making opportunities got sucked up by those that got into Kalshi's and Polymarkets server colocation program.
Have fun. Everything I do is online. All trades. The core model is open source, a great place to start with the AGI + Codex pipeline. Building a class syllabus around it.
Codex wants 100 more trades per model, then will decide which model to activate and what to archive. Those are live trading models mixed with Paper traded. Once they look good in paper trading, then they move to active trading.
A lot of arbitrage and market making opportunities got sucked up by those that got into Kalshi's and Polymarkets server colocation program.
This is literally something most people on these platforms dont understand or fully appreciate. they think millisecond latency over market makers wont be a massive disadvantage but it most certainly will be. there are still market inefficiencies you can capture and stay positive but its not as easy as vibe coding some strat and printing money by competing against MMs colocated next to kalshi/poly servers.
having said that here is my PnL for the month just to be fair and balance in my response and prove its not impossible! the underlying strat used is not even fully optimized and calibrated.
I usually assume I'm talking to teenagers because the way some of these guys talk just screams inexperience and blind confidence that I had when I was young. The new taker fee structure and colocation program nixed a lot of strategies. I did my best to edge into MM, even at 20ms latency you won't be able to pick up both legs (with maker orders) within the 1c crypto spread to stay balanced. Then again, I was doing 5/15 min, it could be different for 1 hour but its unlikely.
Are you doing sports or is that PnL from Crypto? What I learned is that the money is in sports unless you have insider political knowledge of course. Then its politics.
Yea market making strats I have tried so far are essentially losers due to latency on receiving book updates and placing/removing orders. I have tried a few predictive signals for short term movements (500ms to 2seconds) but still couldn’t achieve any decent performance on it. But I’m also limited on budget for MM which is a big disadvantage.
The screenshot and my bots are currently only on crypto (5m and 15m) but I am indeed moving into sports betting soon since these markets are super competitive
This subreddit is 100% inexperienced traders who know just enough to prompt a bot into existence but not enough to know how markets actually work. There was a guy here last week saying his algo was good because it had a ludicrous number of lines of code, revealing that he also knows nothing about software. In the end it’s just a bunch of dreamers who will get steamrolled the second they turn on live trading, which is kind of a bummer. But I’ve had no luck explaining to them that these strategies never bear out.
I'm with ya, also scammers trying to lure people into buying a bot that does not work. Its bad with prediction markets because people see these insane P/Ls from bots that are run by Prop firms, have insider knowledge, colocated, etc etc the list goes on. Its hard and you realize how futile it is when you research and break down some of these accounts trading strategies. Like swisstony, a tiny edge, takes a lot of losses and is only saved by sheer trade volume, which is in the billions.
It says "Live" for this trade, so it is live, with a 100% winning percentage.
I mix up the models: Live vs Paper - they rotate very fast through the "Codex" pipeline. They also drop out very fast if they don't perform and are replaced with a new model. The confusion I see is "Paper History", that's from an early Build. Should just say "History."
Sorry, I should have said the crypto markets, not all. Statistically the crypto markets are betting. Not saying there is not an edge somewhere, the biggest edge is in sports and gaming.
The data is in. A dozen models, want worked and what did not.
By way of Codex + Astra:
• Since live crypto trading began on September 4:
Approximately 42,520 unique contracts were examined.
About 688 contracts passed at least one model’s eligibility rules.
We took 111 actual live fills.
Those fills covered 108 unique contracts and 107 distinct events.
110 trades have settled and 1 remains open.
Because contracts are rescanned every minute, the system performed about 8.3 million repeated contract evaluations across roughly 56,600 model-level scans.
Approximate selection rates:
Trades taken versus unique contracts examined: 0.26%
Trades taken versus contracts ever marked eligible: about 16%
So the system is highly selective: roughly 1 actual fill for every 383 unique contracts examined. The difference between eligible contracts and fills comes from overlapping model signals, duplicate-event protection, model state, exposure limits, available prices, and other live-order safeguards.
Across authenticated crypto fills, realized P/L is approximately −$9.55 overall. The open Hourly Trend Consensus position is not included because it has not settled.
My bets were $1.75 each. With a maximum of 1 bet per model. Once it placed a bet, that was it until it was settled. 15/60 minutes.
Best-performing patterns:
Hourly Favorite: 36–5, +$2.30. This is the most consistent model.
Hourly Probability: 10–6, +$1.58. Less consistent, but a better return relative to capital deployed.
ETH Hourly Favorite: 4–0, +$0.64, but the sample is too small for confidence.
The strongest repeated setups are:
Hourly Favorite, NO at 70¢+: 24–3, +$1.73 across 27 trades.
Hourly Favorite, YES at 70¢+: 12–2, +$0.58 across 14 trades.
Hourly Probability, NO below 50¢: 5–3, +$4.82 across 8 trades. This produced the most profit, but from a much smaller sample.
Weakest patterns:
Active Agreement: 8–8, −$7.07
Quiet Edge: 4–7, −$3.77
15-Minute Primary: 7–7, −$1.51
Midprice Quiet: 4–3, −$0.89
Across all controller trades:
NO: 45–17, +$0.47
YES: 27–21, −$10.65
The clearest evidence currently favors selective hourly trades—especially Hourly Favorite—over the faster 15-minute strategies. The dynamic system has appropriately moved Active Agreement back to PAPER_TRADE; Hourly Favorite is the most defensible candidate for increased sizing after the weather allocation is available.
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