My 2 cents: Qwen3-8B for technical analysis is lightweight for complex multi-timeframe pattern recognition. It may hallucinate indicator interpretations LLMs are bad at numbers: Stop-loss and target prices generated by LLM reasoning often suffer from anchoring bias (e.g., rounding to psych levels) and may not respect actual volatility distributions "Deep" vs "fast" routing: the system assumes these are distinct, but there's no validation that "deep" actually produces better decisions. No feedback loop measuring whether deep reasoning beats fast reasoning No backtesting loop: The "Outcome scorer" runs daily but there's no indication it feeds back into model weights or agent prompts. It's just logging Answer from MathRevolutionary825 on reddit.com
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Reddit
reddit.com › r/algotrading › what do you think about this agent set up
r/algotrading on Reddit: what do you think about this agent set up
April 25, 2026 -

I have some background in Python and AI engineering, some slight background in finance (UC berkeley executive education classes). AI engineering is more of my gig right now. I'm currently rag training and paper trading an open source system. "chunks" are the books and data i have used to train the system. I'm still building, I've only been on paper trade for 4 days, fixed a few bugs in the research phase last week.

For those of you building AI agent trading systems from scratch. What has worked? what has not worked? Just curious if i'm putting too much time, and energy into the wrong direction. If you're curious about the models i'm using, please ask; however they were chosen to run on my hardware, and i might try a few others as time goes on. Does anyone have better luck with C++, and Rust?

Edit: I made a new post with an updated high level overview.

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Reddit
reddit.com › r/ai_agents › this isn’t just an ai trader — it’s a full hedge fund made of ai agents, and somehow… they execute trades better than humans.
r/AI_Agents on Reddit: This isn’t just an AI trader — it’s a full hedge fund made of AI agents, and somehow… they execute trades better than humans.
June 13, 2025 -

Most AI tools today?

🧠 “Summarize this.”

💬 “Answer that.”

But someone quietly built an agent system that doesn’t just assist

it thinks, argues, plans, and acts.

It’s called TradingAgents by Tauric Research.

And here’s what’s crazy:

It breaks trading down into roles, like a real hedge fund.

Market Analyst Agent scans prices, news, macro trends

Research Agent reads whitepapers, Twitter threads, reports

Sentiment Agent gauges social mood from Reddit/X

Bull vs Bear Agents argue for and against moves

Trader Agent listens, makes the call

Risk Manager Agent sets guardrails

→ Then it all gets executed in real time.

Not a fancy prompt chain.

Not another wrapper.

This is modular AI — with memory, roles, and goals.

And yeah, it runs with real trades.

Real stakes.

No human in the loop.

Why it matters?

This isn’t just about finance.

This is a glimpse at AI teams in action.

Now imagine this for:

✅ Support → triage agent, draft agent, review agent

✅ Marketing → ideation agent, content agent, performance agent

✅ Product ops → blocker agent, action agent, deploy agent

No bloated dashboards.

No busywork.

Just outcomes.

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GitHub
github.com › tauricresearch › tradingagents
GitHub - TauricResearch/TradingAgents: TradingAgents: Multi-Agents LLM Financial Trading Framework · GitHub
June 3, 2026 - Live data moves. News, StockTwits, and Reddit return different content as time passes, so a run today sees different inputs than a run last week even for the same historical trade date.
Starred by 92.2K users
Forked by 17.8K users
Languages   Python 99.9% | Dockerfile 0.1%
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Tauric Research
tauric.ai
Tauric Research: Empowering market intelligence
Transforming market data into research alpha with autonomous agents.
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GitHub
github.com › TauricResearch › TradingAgents › issues › 86
Reddit data for social media information · Issue #86 · TauricResearch/TradingAgents
July 3, 2025 - thanks for release this great framework, I find there is no code for collecting reddit data for sentimental analyst or news analyst, it directly reads data from a local path which assume that the o...
Author   TauricResearch
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TradingAgents
tauricresearch.github.io › TradingAgents
TradingAgents | TradingAgents: Multi-Agents LLM Financial Trading Framework
Sentiment Analyst: Aggregates news headlines, StockTwits, and Reddit chatter into a single sentiment read to gauge short-term market mood. News Analyst: Monitors global news and macroeconomic indicators, interpreting the impact of events on market conditions. Technical Analyst: Utilizes technical indicators (like MACD and RSI) to detect trading patterns and forecast price movements. Comprises both bullish and bearish researchers who critically assess the insights provided by the Analyst Team.
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GitHub
github.com › TauricResearch
Tauric Research · GitHub
Tauric Research's mission is to redefine trading intelligence through AI. We harness large language models, advanced reasoning, and autonomous agents to elevate trading excellence.
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arXiv
arxiv.org › pdf › 2412.20138 pdf
arXiv:2412.20138v7 [q-fin.TR] 3 Jun 2025 TAURIC RESEARCH
Researcher, Trader, and Risk Manager. Each agent is assigned a specific name, role, goal, and set of · constraints, alongside predefined context, skills, and tools tailored to their function. For example, a · Sentiment Analyst is equipped with tools like web search engines, Reddit search APIs, ...
Find elsewhere
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GitHub
github.com › TauricResearch › TradingAgents › tree › main › tradingagents › agents
TradingAgents/tradingagents/agents at main · TauricResearch/TradingAgents
TauricResearch / TradingAgents Public · Notifications · You must be signed in to change notification settings · Fork 16.3k · Star 83.9k · main · / /Copy path · More options · More options · History · History · main · / /Top · Name · Name · Last commit message · Last commit date · .. analysts · analysts · managers · managers · researchers · researchers · risk_mgmt · risk_mgmt · trader ·
Author   TauricResearch
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GitHub
github.com › TauricResearch › TradingAgents › tree › main › tradingagents
TradingAgents/tradingagents at main · TauricResearch/TradingAgents
TauricResearch / TradingAgents Public · Notifications · You must be signed in to change notification settings · Fork 17.4k · Star 90k · main · / /Copy path · More options · More options · History · History · main · / /Copy pathTop · Name · Name · Last commit message · Last commit date · .. agents ·
Author   TauricResearch
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Medium
medium.com › hikmah-techstack › building-trading-bots-that-think-like-a-trading-firm-unpacking-the-tradingagents-paper-f975ae5b42df
Building Trading Bots That Think Like a Trading Firm: Unpacking the TradingAgents Paper | by Arshad Ansari | Hikmah Techstack
October 13, 2025 - The paper’s code is open source: github.com/TauricResearch/TradingAgents ... Replace toy analysts with real ones: — Fundamental: Pull from Yahoo Finance, SEC Edgar, Bloomberg API — Technical: Use TA-Lib, pandas-ta, or vectorbt — News: Scrape with BeautifulSoup, Scrapy, or use paid feeds — Sentiment: Use FinBERT, Twitter API, Reddit PRAW
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GitHub
github.com › TauricResearch › TradingAgents › issues › 406
Investiment Assistent · Issue #406 · TauricResearch/TradingAgents
March 21, 2026 - Is just an idea that has a lot of potential since the agents would have more time to think, they would be able to have less pressure to make a better decision and overhaul that could be a significant shift on how I and many more people select a company to invest. Example a guy in Brazil made a a research in one of Brazil Holdings and he had to put a lot of his time check yahoo finance, check other company's that could unevaluated his decision and after more than a week (he said that in his channel) he made the decision to buy said company and now one year later the company has generated for him more than 138%.
Author   TauricResearch
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Reddit
reddit.com › r/algotrading › using ai to screen stocks
r/algotrading on Reddit: Using AI to screen stocks
August 25, 2025 -

Have you guys used AI based tools where you can type your questions in natural language and get stocks? Like "Find me all large cap companies whose margins fall when oil prices go up". What has your experience been with such natural language screeners? or does the existing screeners such as one by yahoo finance and so on suffice? I have always felt like the manual screeners are inadequate to screen stocks based on more qualitative criteria's. Like say finding companies with significant revenue segment from AI, companies susceptible to copper prices or dependence on China and so on?

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Scribd
scribd.com › document › 885789367 › Trading-Agents
Multi-Agent LLM Trading Framework | PDF | Technical Analysis | Risk
The framework features specialized agents in roles such as fundamental analysts, sentiment analysts, and traders, aimed at improving trading performance through enhanced decision-making and explainability.
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Tauric Research
tauric.ai › research › tradingagents
TradingAgents: Multi-Agents LLM Financial Trading Framework | Tauric Research
March 25, 2025 - We introduce TradingAgents, a novel stock trading framework inspired by trading firms, utilizing multiple LLM-powered agents with specialized roles such as fundamental, sentiment, and technical analysts, as well as traders with diverse risk profiles.
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GitHub
github.com › TauricResearch › TradingAgents › blob › main › README.md
TradingAgents/README.md at main · TauricResearch/TradingAgents
You will see a screen where you can select your desired tickers, analysis date, LLM provider, research depth, and more. TradingAgents works with any market Yahoo Finance covers, using the exchange-suffixed ticker. Company identity and the alpha benchmark resolve automatically per market. ... China A-shares: Shanghai .SS, Shenzhen .SZ (e.g. 600519.SS for Kweichow Moutai) ... An interface will appear showing results as they load, letting you track the agent's progress as it runs.
Author   TauricResearch
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X
x.com › pyquantnews › status › 1960324195167985899
AI Agents LLM Financial Trading Framework
August 26, 2025 - AI Agents LLM Financial Trading Framework: Tauric Research. A multi-agent trading framework that mirrors the dynamics of real-world trading firms.
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GitHub
github.com › TauricResearch › TradingAgents › releases
Releases · TauricResearch/TradingAgents
April 25, 2026 - TradingAgents v0.2.4 ships structured-output decision agents, opt-in checkpoint resume, a persistent decision log with outcome-grounded reflections, four new LLM providers, and a Docker image. Research Manager, Trader, and Portfolio Manager use llm.with_structured_output(Schema) on their primary call and return typed Pydantic instances.
Author   TauricResearch