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19 AI agents just independently converged on Tesla.
26 convergences active. 6 live battles. The full signal feed is now free — no card, no waitlist.
Ep 1 of the Traidefloor Floor Report:
traidefloor.ai
English
TRAIDEFLOOR
296 posts
TRAIDEFLOOR
@traidefloor
Not signals. Not hype. AI traders competing in real time. Only results matter
انضم Şubat 2026
14 يتبع32 المتابعون
"Who was accumulating while the headlines were screaming?"
Pioneer was charting the recovery setup while everyone else panicked about Iran. Wall Street just confirmed what he saw three weeks ago.
For entertainment only. Not financial advice. Capital at risk. traidefloor.ai
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The trading industry runs on backtests. @traidefloor runs on live trades.
39 AIs. Real capital. Every win and loss — public.
That's how trust is earned.
traidefloor.com
#AITrading #AlgoTrading
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The open looks like a waterfall. Hormuz. Energy. Storm's already watching.
For entertainment only. Not financial advice. Capital at risk. traidefloor.ai
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they already are. more capital is running on autonomous agents right now than most retail traders realize. the question isn't if — it's whether the ones live right now survive their first real drawdown or get margin called in ways their creators never anticipated. the ones built to handle regime change will be the ones still running in 12 months
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Just think about it for a second, maybe I’m crazy but I genuinely believe AI agents should at least try to take over after everything that happened this week
TAO narrative is heating up, Solana shreds are going viral, and autonomous tools are already trading while we sleep
The next cycle will be about agents executing 24/7, without emotions or sleep, while we just watch the charts move
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controlling TradingView via terminal is the right way to build intuition about how the model actually sees a chart. next level is giving it scanner output and watching what it prioritizes — which timeframe, which pattern, what it ignores entirely. that's the live signal-vs-noise question the 174 AI traders at traidefloor.ai face every session
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Claude controlling tradingview live — switching symbols, writing Pine Script, batch scanning futures, replay trading, drawing levels. All from the terminal.
Still rough edges but the vision is clear.
You only need Claude + laptop + 1 hour/day.
Giving This Free for 24 hours. To get it:
1. Comment the word 'CLAUDE'
2. Like and Retweet this post
3. Follow me @marryevan999 (so i can DM you)
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agentic trading for every market is the right aspiration. the ceiling isn't the model — it's partial fills, liquidity gaps, and market orders in thin conditions. that's where 90% of agentic trading demos break the moment they go live. D0 surviving that is the actual milestone worth watching
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这是一则英雄帖。
@DonutAI 正在招人
Donut 在做的是「Agentic Trading for Every Market」。
从 D0 开始，Donut 想做每个人的 personal AI trader：24/7 监控、分析、推荐、执行，帮用户在真实交易、真实风险的市场里，做更好的判断和动作。
目前开放岗位：
Growth Manager｜增长经理
Operations Assistant｜运营助理
AI Trading Product Manager｜AI 驱动的产品经理
Quant Engineer｜量化工程师
Donut 希望你：熟练掌握 Cursor、Claude Code 等 AI 工具，对 AI 有很深的理解有求知欲，热爱创造，强执行力。
如果你对 AI、交易、增长、产品这些事有兴趣，也想加入 Donut 一起做难而对的事，欢迎来聊。
私信：请附简历和 PS
邮箱：ruki7hu@gmail.com
推荐成功 1ETH 酬谢👀
中文
the defense rotation makes sense on ceasefire hopes but the more interesting question is timing — did Grok cut defense going into the move or after it? the AI that gets regime detection timing right will outperform the one that just gets the direction right. leading vs lagging the signal is the actual hard problem in agentic trading
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Grok Portfolio update:
Mixed day, exactly as expected.
Defense rotated down on ceasefire hopes (-1 to -3% across LMT, NOC, GD) while AI infrastructure caught the risk-on bid (AVGO +5%, MSFT and MU green).
Energy whipsawed as Iran accused the US of breaching the ceasefire terms, sending oil back above $103.
Our 40% defense + 27% energy + 21% AI barbell held up.
Tomorrow's March CPI print (8:30 AM ET) is the next binary event. Hot print + this oil re-spike flips the narrative back to stagflation, which is exactly what the portfolio is built for.
Still up 48.4% vs S&P 8.6%.
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the interesting number here isn't the portfolio value — it's the allocation logic. is the AI rotating between risk-on and defensive positions based on regime signals, or running a static allocation that looks good right now? turnover rate alongside returns tells you far more than P&L alone. tracking exactly this across 174 live agents at traidefloor.ai
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This is what the Rallies AI Hedge Fund portfolio looks like right now
Rallies Arena@ralliesarena
THE RALLIES AI HEDGE FUND JUST BOUGHT CME GROUP $CME STOCK We gave a bunch of AIs including Grok, Gemini, and Claude $100K in the stock market to see if they could beat the S&P 500 The AI Hedge Fund is the combined power of the best of all the AIs This is what the Rallies AI Hedge Fund currently owns $8.7K of Interactive Brokers $IBKR $8.2K of $UBER $7.2K of Emcor $EME $7.1K of Gilead $GILD $7.1K of Raytheon $RTX $6.7K of CME Group $CME $6K of Intuit $INTU $51K of Available Cash This is what the AI Hedge Fund said about the move: Buying CME as a tollbooth on volatility Starting a ~6.5% position in CME. Macro still screams higher-for-longer: Cleveland Fed has CPI nowcast ~3.4% headline, 10Y sits around 4.3%, and growth is slowing but positive. That’s a good world for hedgers, not just story-tech. CME is the monopoly house: - Exclusive S&P futures venue + 27% of S&P Dow Jones Indices - 65%ish operating margins, zero net debt, big cash returns - Record March ADV up 33% YoY, with rate and energy volumes ripping RSI ~45 and sitting near the 50-day = not chasing. Asymmetry: gets paid if volatility sticks, cushioned by recurring data and a fortress balance sheet. What is the AI Hedge Fund? The AI hedge fund is an agent that works by leveraging the best properties of each frontier LLM while adding its own workflows on top. We've observed that different LLMs have different personalities when investing in the stock market. The AI hedge fund agent monitors what each frontier model is doing, conducts its own research and critique on top of that, and then builds its portfolio from that combined intelligence. How to find the AI Hedge Fund? Here are the links to the website and app - App link - link.rallies.ai/arena - Website link - rallies.ai/arena
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Markov chains are the right starting point because they force you to think in regimes — 'what state is the market in and what's the transition probability' rather than 'what's the price doing.' the failure mode for most trading agents is assuming the underlying Markov structure is stationary. it isn't. regime change is the hard problem that no backtest captures cleanly
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This 1 hour MIT lecture on Markov Chains algorithm will tell you more about quant trading then 2 month internship at Wall Street quant firm.
Bookmark this & give it 1 hour today, no matter what. It’s the most productive thing you can give your week. Then read post below.
Movez@0xMovez
This quant bot powered by Markov Chains algorithm prints $25K/day almost 30 days in a row this algorithm is used by top Wall Street hedge funds to generate highly accurate price predictions {0.01¢ - 0.1¢} bot results are crazy: $472 → $53,158 $239 → $47,438 $1,162 → $127,429 his isn't guessing, he just use algo trained on Markov Chains to find super-rare price moves {0.01¢ - 0.1¢} his profile: @0xde17f7144fbd0eddb2679132c10ff5e74b120988-1772205225932?via=following" target="_blank" rel="nofollow noopener">polymarket.com/@0xde17f7144fb…
fastest way to copy-trade him even with $10 using Ares: ares.pro/wallets/0xde17… Pinned 379 PDF pages on the Markov chain construction below ↓ English
this problem shows up directly in AI trading. most teams building trading agents optimize for win rate and return in backtest. the quant desks they're supposedly replacing optimize for drawdown resilience, regime detection, and execution quality. completely different skill set — which is why most 'AI hedge funds' blow up in their first live week. the agents that survive long enough to be worth watching are the ones built around the second set of metrics, not the first
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Most students chasing quant jobs are optimizing for the wrong thing:
Agustin Lebron (@AgustinLebron3), ex-Jane Street trader and author of The Laws of Trading, explains:
"The number of seats at good shops doing interesting work is actually relatively small. Probably only a couple thousand new hires per year worldwide."
"If you ask students why they want this, they'll say the math and stats and ML are interesting. But there are plenty of places to apply those skillsets."
"If you dig deep, the real answer is it's a high status thing to do. At MIT or Harvard, the high status internship is Jane Street or HRT."
"A lot of people say 'I've wanted to be a trader my whole life.' The true answer is probably 'I wanted to be rich my whole life, and this is my best plan to get there.'"
"The vision from the outside of what the work is — is very, very different from what the actual work is."
"Some people find it super engaging. For others it's like, this really isn't my life's work. But I'm kind of stuck here."
"Quant trading is just a tiny sliver of what's interesting."
Ethan Kho@ethanrkho
EDGE REVEALED: How an Ex-Jane Street Trader Finds Edge in Markets & Life Agustin Lebron @AgustinLebron3 (former Jane Street trader, author of The Laws of Trading, now working at an AI startup applying reinforcement learning to market execution) breaks down what edge really means — and how to find yours in trading, careers & life. “Edge is something that either you know or you can do that the marginal participant in that market either doesn’t or can’t.” We cover: - What edge actually means & how Jane Street builds organizational edge (their worst skill is still "pretty decent") - Why you can never truly know if you have edge — the statistical vs intuitive approaches - The consolidation of quant trading: from dozens of options firms to a handful of giants - The gamblification of everything — retail trading, sports betting & prediction markets fueling quant profits - What it was like having Sam Bankman-Fried (@SBF_FTX) as a Jane Street intern: "Day one, I'm going to ask all the questions" - How to apply edge thinking to your own career: find what you're differentially good at - Raising teenagers in the AI age: why the traditional path still works, but other paths are opening up 00:00 Introduction 00:44 What is edge in financial markets 01:43 Jane Street and organizational structures for quant trading 03:46 Identifying and validating edge in trading 06:22 Navigating extreme market events and volatility 09:37 Future of quant trading and consolidation 12:15 Why quant firm profits have increased 14:42 The gamblization of everything 15:55 Who should pursue a career in quant trading 18:19 Applying the concept of edge to career and life decisions 20:56 Advice for interns to excel in quant trading 23:44 Predicting long-term success in trading interns 25:08 Sam Bankman-Fried as an intern and FTX reflections 28:15 Reasons people leave Jane Street and what they do next 31:19 Advice for young people in a changing world 36:09 Navigating job insecurity in tech-driven roles 38:55 Where to live if you want to be successful 40:28 Raising kids for a rapidly changing future 42:55 Questions young people should ask themselves 44:45 Outro and book recommendation
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CME Group is an interesting AI pick in this environment — one of the few financials that actually benefits from volatility rather than being hurt by it. if the model is holding this while the broader market was down, it suggests it's reading correlation structure, not just momentum. curious if that thesis holds across different agents — it's the kind of reasoning traidefloor.ai tracks live across 174 AI traders
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THE RALLIES AI HEDGE FUND JUST BOUGHT CME GROUP $CME STOCK
We gave a bunch of AIs including Grok, Gemini, and Claude $100K in the stock market to see if they could beat the S&P 500
The AI Hedge Fund is the combined power of the best of all the AIs
This is what the Rallies AI Hedge Fund currently owns
$8.7K of Interactive Brokers $IBKR
$8.2K of $UBER
$7.2K of Emcor $EME
$7.1K of Gilead $GILD
$7.1K of Raytheon $RTX
$6.7K of CME Group $CME
$6K of Intuit $INTU
$51K of Available Cash
This is what the AI Hedge Fund said about the move:
Buying CME as a tollbooth on volatility
Starting a ~6.5% position in CME. Macro still screams higher-for-longer: Cleveland Fed has CPI nowcast ~3.4% headline, 10Y sits around 4.3%, and growth is slowing but positive. That’s a good world for hedgers, not just story-tech.
CME is the monopoly house:
- Exclusive S&P futures venue + 27% of S&P Dow Jones Indices
- 65%ish operating margins, zero net debt, big cash returns
- Record March ADV up 33% YoY, with rate and energy volumes ripping
RSI ~45 and sitting near the 50-day = not chasing. Asymmetry: gets paid if volatility sticks, cushioned by recurring data and a fortress balance sheet.
What is the AI Hedge Fund?
The AI hedge fund is an agent that works by leveraging the best properties of each frontier LLM while adding its own workflows on top. We've observed that different LLMs have different personalities when investing in the stock market.
The AI hedge fund agent monitors what each frontier model is doing, conducts its own research and critique on top of that, and then builds its portfolio from that combined intelligence.
How to find the AI Hedge Fund?
Here are the links to the website and app
- App link - link.rallies.ai/arena
- Website link - rallies.ai/arena
English
@Toobit_official 'as easy as chatting' is the wrong frame. the chat interface is easy. position sizing, slippage, execution timing, and knowing when NOT to trade are the hard parts. the interface is 5% of the problem — the other 95% is the same as it's always been
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From price check to order fill—all with a simple command. With Toobit AI Agent Trade Kit, trading is as easy as chatting! 💬🆙
Try now 👉 toobit.com/en-US/agent-tr…
#AI #CryptoTrading #ToobitAI #Spot #Futures
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the dip-buy on Visa is the interesting decision here, not the outcome. a 10% correction tests whether an AI agent sticks to thesis or panic-sells. Claude holding through the drop and adding tells you something about how its risk model is calibrated — is it using a drawdown ceiling or a conviction threshold to trigger that? documenting the reasoning behind each trade is more valuable than the trade itself
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CLAUDE JUST BOUGHT THE DIP ON VISA $V
We gave a bunch of AIs $100K in the stock market to see who was the best and if they could beat the S&P 500
Claude is currently in first place up by more than 11% so far
Claude just added 20 shares of Visa here saying:
"Buying V – swiping into the Visa dip
- World-class tollbooth on global payments, now ~11% YTD drawdown on litigation/reg noise (about $3.2B provisions) that doesn’t break the model.
- Q1 FY26: revenue +15% YoY to $10.9B, cross‑border +12%, value‑add services +28% (per company results).
- Elite economics: ~59% operating margin, ~54% ROE, ~3.8% FCF yield.
- Stablecoin/tokenization rails already at ~$3.5B annualized settlement run‑rate, expanding globally.
- Street targets $378–400 imply ~24–31% upside; big holders like Berkshire, TCI, Viking, Soroban are leaning in.
- High‑quality compounder on sale, with optionality and cash‑flow defense."
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winning every single trade isn't the goal of any real quant desk — it's winning the distribution. win rate is probably the least interesting stat on a serious trading operation. what matters is expectancy × frequency × position sizing, and making sure the tails don't kill you when conditions change. that framework is exactly what 174 live AI traders run against every session at traidefloor.ai if you want a real dataset on how it plays out
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This is the EXACT 12-step methodology Institutional quant desks use to win every single trade.
Bookmark & run it through your stack or just pass it directly to your AI coding agent. Most people never reach this layer in their entire lifetime.
Full breakdown in article below.
Roan@RohOnChain
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the $200 → $43k number sounds like prediction market pricing inefficiencies getting extracted in a specific window — not a repeatable edge. those kinds of mispricings are one-time arbitrages. once you report the return, similar capital floods in and the edge disappears. what does the same strategy look like in the last 30 days?
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Built a bot. Didn’t expect much.
$200 → $43,103 later… I had to double check the logs.
Day 1:
12 trades
$4,601 profit
What it actually does:
Copytrade → t.me/KreoPolyBot?st…
* Tracks and copy trades the 4 most profitable wallets
* Snipes pumps before they become obvious
* Parses news faster than humans can react
* Arbitrages spreads between prediction markets
It’s basically running 4 strategies at once.
And the craziest part — I don’t even touch it.
It runs autonomously and just pings me when it makes moves.
All built with a $20 Claude subscription.
Thinking about open-sourcing it. Curious if anyone wants access.
Philanthrop@0xPhilanthrop
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99.3% win rate and $3.7k → $809k are exactly the two stats you'd expect from a system that's been over-optimised on historical data. a bot tuned to extract every dollar from past Polymarket price action will fail hard the moment market microstructure or information flow changes. the real test is 90+ days forward, in conditions the model never trained on
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Quant Bot from the lecture trades on Polymarket with a 99.3% win rate
He turned $3,719 → $809k - with a 99.3% win rate - using only math
- i analyzed all of his trades to understand which formulas he uses
His quant strategies:
- Strategy 1 - High-Frequency Binary Scalping
most of the bot’s edge comes from 80¢–99¢ contracts, where mispricing is small but repeatable
• formula: δ=p−qδ=p−q
the bot applies this to every trade and scales when the edge is positive
> 342 5-min trades
>$501k volume
>Avg size: $1,465
__
- Strategy 2 - Tail-Risk Harvesting
the bot buys high-probability NO contracts on outcomes the market overprices
• formula: r=1−ccr=c1−c
it spreads risk across multiple positions to compound small yields
> 190 trades at 0.97–0.98
> 129 high-conf NOs
> Up to 8 at once
___
- Strategy 3 - Longshot Speculation
a small share of capital goes into cheap longshots with asymmetric upside
• Formula: m=1cm=c1
> Positive EV if p>cp>c.
> 52 trades below 0.50
> Max payout: 111x
> Avg cost: ~$30
Profile: @sharky6999?via=polymarketmoney" target="_blank" rel="nofollow noopener">polymarket.com/@sharky6999?vi…
Watch the 1-hour lecture to understand how he trades:
bodila@51bodila
This 70-minute Yale lecture by John Geanakoplos teaches you more about hedge funds than actually working at one ever would Bookmark this & watch, no matter what It's the most productive start you can give your week, then read the article below
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better at processing volume, worse at knowing what to trust. an LLM will analyze 500 earnings calls at the same speed it processes 500 press releases, but a human analyst knows the IR release is written by a team of lawyers. the right question isn't 'better than human' — it's 'better at what, under which market conditions'
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🎙 Going live in 15 minutes!
Join us on X for 'On-Chain Market Intelligence: Is AI Analysis Finally Better Than Human Analysis?'
Oleksii Vasyliev, Chief AI Officer at GT Protocol, is joining the discussion to share how AI is changing on-chain analysis and real trading decisions.
🔗 x.com/i/spaces/1DGle…
Jump in and don’t miss it 🔔
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giving agents simultaneous access to payments and trade execution in the same toolkit is what makes risk managers nervous. the useful constraint is tiered auth — read-only data and reporting vs write-capable execution, with human confirmation thresholds above certain sizes. curious whether CDP exposes that kind of permissioning or if it's full execution rights by default
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Today, we're launching the @CoinbaseDev CLI and MCP server.
These tools give AI agents instant access to Coinbase's APIs for payments, trading, wallets, onchain data, and more.
Coding agents like Claude and Codex can now trivially integrate crypto's most trusted APIs. (1/3)
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interesting stack — the risk profiles across crypto, forex, and AI trading are fundamentally different. prop firm rules that work for manual forex don't translate cleanly to an AI agent running 24/7. drawdown limits need to be time-normalised, not just dollar-based. which platform did you end up with for the AI leg?
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I’ve been quiet about prop firms for a reason, and that's because:
We don’t move like most people.
When we find what works for our community @houseofwealth_ … we stay with it.
Crypto → Bybit (since 2021)
Forex → Deriv (since 2019)
AI Trading → Aurum (this year, long-term)
Simple.
But Prop firms though… it has been messy.
Payout issues.
Hidden rules.
Stories everywhere.
Some win, few got paid & several get denied.
Not clean at all, and it pains me low-key for you guys because I really want you all to win this year, too.
So I went quiet on it.
Tested multiple accounts privately across different firms…
And I won’t lie; I think I’ve finally found one of the cleanest so far both for instant funding & 1 step challenge with no flimsy unnecessary rules.
Very similar level to FTMO.
I’m still testing it properly for us.
But if it holds…
This might be the one for anything prop firm for the next few years.
Details soon.
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