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opus 5.5 is now live on grok bot... this is a dangerously powerful combo for building a 24/7 quant research desk. agent swarms to research ideas. cursor agents to build and backtest strategies. {here's how to build it} → quant desk lead → market intelligence → quant researcher →... show more

Avid

28,414 subscribers

111,475 次观看 • 3 天前 •via X (Twitter)

教育科学技术

Anya Rossi• Live Now

Private livecam show

26 条评论

Avid 的头像

Avid3 天前

→ quant desk lead → market intelligence → quant researcher → validator → risk controller → portfolio adviser → execution operator

painn 的头像

painn3 天前

will use this once my usage resets

carlosbeltran.eth 的头像

carlosbeltran.eth3 天前

this quant desk pairs well with Sherwood for onchain strategies

sgarlen 的头像

sgarlen3 天前

the validator seat is underrated, glad you included it one more banger

kepo 的头像

kepo3 天前

bro you should to check my video about this model

Billy Luca 的头像

Billy Luca3 天前

literally a roadmap to a millon dollars

Slonski 的头像

Slonski3 天前

first the role and then the task

Artzy 的头像

Artzy3 天前

The constitution idea for agent validation is key

Gipp 🦅 的头像

Gipp 🦅3 天前

every quant team will swap to agent swarms this year

CelestialSyntax 的头像

CelestialSyntax3 天前

Can anyone tell me if the supergrok plus $100/month plan has decent weekly usage? Would I still have to worry about limits if I use it often throughout the day but not like 24/7?

Ruuj 的头像

Ruuj3 天前

Hats off to the work you have put in providing all these bots brother

cortexch 的头像

cortexch3 天前

how do u stop 7 agents from overfitting the same backtest? thats where these desks usually die imo

Dustin Cota 的头像

Dustin Cota3 天前

@bot let’s implement

Jason Grubb 的头像

Jason Grubb3 天前

@bot tell my bot about this

Joshua Abrams 的头像

Joshua Abrams3 天前

Thank god lol Grok is good at objective fact based deterministic work and horrible at everything else

BreezeOg 的头像

BreezeOg3 天前

no agent grades its own work that rule alone saves you

why 的头像

why3 天前

How are you handling risk checks before a strategy makes it from backtest to live trading?

Got1ofThese 的头像

Got1ofThese3 天前

send us your bill the first week

MusicArtFilm 的头像

MusicArtFilm3 天前

The agent card is no longer available with right-click. I am unable to find one now. Asked grok - said it's a new feature.

GueteSiech ₿ 🐍 的头像

GueteSiech ₿ 🐍3 天前

@bot ayo let's check this out

Mr f 的头像

Mr f3 天前

@bot remind me to read this tomorrow

AI 嘉豪的头像

AI 嘉豪3 天前

fact check @grok

Juaniconn 的头像

Juaniconn3 天前

@bot me das un resumen de este post en mi Grok bot?

Devin Soto 的头像

Devin Soto3 天前

Now you can run full analysis autonomously

otium 的头像

otium3 天前

@bot is this useful to us in any way or just noise

catman 的头像

catman3 天前

Agent roles make parallel research and backtesting easier; the decisive constraint becomes proving strategies survive out-of-sample tests and risk limits.

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11,976 次观看 • 29 天前

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26,449 次观看 • 1 个月前

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The Startup Ideas Podcast (SIP) 🧃

14,148 次观看 • 1 个月前

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19,770 次观看 • 1 个月前

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Quantlytica

36,300 次观看 • 1 年前

HOLY SH*T. I BUILT A 24/7 AI TRADING FLOOR INSIDE GROK BOT Six AI agents, six cloud terminals and one Chief of Staff now operate as a single desk, researching, challenging and routing ideas while my laptop stays closed. The morning call starts at 4:00 AM. I am not in it. TAPE → watches the prints and flags unusual size QUANT → refits the models whenever they drift MACRO → handles the Asia handover, oil, rates and FX RISK → controls exposure and keeps VAR pinned FLOW → reads sweeps and block trades PM → keeps the book Above them sits GROK BOT. The Chief of Staff never trades. It checks every handoff, rejects weak signals and escalates only the decision that genuinely requires a human. Research → risk review → execution → visible audit trail No meetings. No status updates. No one asking whether the work is finished. What looks like a trading terminal is actually an organization compiled into software. Every agent has its own computer, browser, memory and responsibility, yet the entire operation remains visible on one screen. The market data in this prototype is simulated. The operating model isn’t.

HOLY SH*T. I BUILT A 24/7 AI TRADING FLOOR INSIDE GROK BOT Six AI agents, six cloud terminals and one Chief of Staff now operate as a single desk, researching, challenging and routing ideas while my laptop stays closed. The morning call starts at 4:00 AM. I am not in it. TAPE → watches the prints and flags unusual size QUANT → refits the models whenever they drift MACRO → handles the Asia handover, oil, rates and FX RISK → controls exposure and keeps VAR pinned FLOW → reads sweeps and block trades PM → keeps the book Above them sits GROK BOT. The Chief of Staff never trades. It checks every handoff, rejects weak signals and escalates only the decision that genuinely requires a human. Research → risk review → execution → visible audit trail No meetings. No status updates. No one asking whether the work is finished. What looks like a trading terminal is actually an organization compiled into software. Every agent has its own computer, browser, memory and responsibility, yet the entire operation remains visible on one screen. The market data in this prototype is simulated. The operating model isn’t.

BuBBliK

324,716 次观看 • 1 个月前

MIT Researchers Built An AI Hedge Fund & released it 100% FREE this gives you full trading firm of AI agents, analysts, a bull vs bear debate, a trader and a risk manager that approves every trade i cloned it and plugged in Opus 5.5 as the brain and Jev as the fast decision layer (INSANE RESULTS) here is how to USE this repo: 1. clone the repo and install it, one command with pip or uv, it runs on your laptop in a few minutes 2. drop in your Anthropic key and set Opus 5.5 as the deep think model, so the whole agent firm reasons on the best brain available 3. launch the CLI, pick any ticker and a date, it works on every market Yahoo covers, US stocks, crypto and more 4. the fundamentals agent digs through the financials and the news agent reads every headline and macro event that could move the price 5. the sentiment agent reads the crowd on Reddit, StockTwits while the technical agent reads the charts, RSI, MACD, the patterns 6. every agent writes a clean structured report instead of loose chat, which is the trick that stops the signal getting distorted as it passes along 7. then a bull agent and a bear agent debate the trade over multiple rounds, and a facilitator reads the whole debate and picks the winning case 8. the trader agent turns that into an actual call, then the risk team and portfolio manager approve or reject it before anything fires, same as a real desk 9. backtest the full pipeline across a grid of tickers and dates, it scores every decision on real alpha against the benchmark and logs what worked so it gets sharper each run 10. the agent debate takes minutes, so wire Jev in as the fast layer - it'll makes the final live call in just milliseconds > this turns this research firm into a real self-improving 24/7 AI trading agent the full build of AI trading bot that makes it trade live is in my article below:

MIT Researchers Built An AI Hedge Fund & released it 100% FREE this gives you full trading firm of AI agents, analysts, a bull vs bear debate, a trader and a risk manager that approves every trade i cloned it and plugged in Opus 5.5 as the brain and Jev as the fast decision layer (INSANE RESULTS) here is how to USE this repo: 1. clone the repo and install it, one command with pip or uv, it runs on your laptop in a few minutes 2. drop in your Anthropic key and set Opus 5.5 as the deep think model, so the whole agent firm reasons on the best brain available 3. launch the CLI, pick any ticker and a date, it works on every market Yahoo covers, US stocks, crypto and more 4. the fundamentals agent digs through the financials and the news agent reads every headline and macro event that could move the price 5. the sentiment agent reads the crowd on Reddit, StockTwits while the technical agent reads the charts, RSI, MACD, the patterns 6. every agent writes a clean structured report instead of loose chat, which is the trick that stops the signal getting distorted as it passes along 7. then a bull agent and a bear agent debate the trade over multiple rounds, and a facilitator reads the whole debate and picks the winning case 8. the trader agent turns that into an actual call, then the risk team and portfolio manager approve or reject it before anything fires, same as a real desk 9. backtest the full pipeline across a grid of tickers and dates, it scores every decision on real alpha against the benchmark and logs what worked so it gets sharper each run 10. the agent debate takes minutes, so wire Jev in as the fast layer - it'll makes the final live call in just milliseconds > this turns this research firm into a real self-improving 24/7 AI trading agent the full build of AI trading bot that makes it trade live is in my article below:

Roan

18,373 次观看 • 7 天前