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Quant Science Profile picture
@quantscience_
Jan 7 • 8 tweets • 3 min read • Read on X
🚨BREAKING: A new open-source multi-agent LLM trading framework in Python

It's called TradingAgents.

Here's what it does (and how to get it for FREE): 🧵 Image
1. What is TradingAgents

TradingAgents is a multi-agent trading framework that mirrors the dynamics of real-world hedge funds.
2. How it works

By deploying specialized LLM-powered agents: from fundamental analysts, sentiment experts, and technical analysts, to trader, risk management team, the platform collaboratively evaluates market conditions and informs trading decisions
3. The research

TradingAgents: Multi-Agents LLM Financial Trading Framework

Get the 38-page paper: arxiv.org/pdf/2412.20138Image
4. They Open Sourced It!

Get it on GitHub here (must know Python to use it):

One more thing before you go...👇github.com/TauricResearch…
🚨Want to become an algorithmic trader with Python in 2026?

• QSConnect: Quant research database
• QSResearch: Research & machine learning strategies
• Omega: Automated trade execution

👉 Join Our Free Algorithmic Trading Workshop:  learn.quantscience.io/become-a-pro-q…Image
That's a wrap! Over the next 24 days, I'm sharing my top 24 algorithmic trading concepts to help you get started.

If you enjoyed this thread:

1. Follow me @quantscience_ for more of these
2. RT the tweet below to share this thread with your audience
P.S. - Want Algorithmic Trading with Python tutorials every Sunday?

Register here to join our Sunday Quant Scientist Newsletter (it's free): learn.quantscience.io/quant-scientis…

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More from @quantscience_

Quant Science Profile picture
Jan 8
Automate your trading strategies in Python

How to build your first trading bot:

(a thread) Image
1. What is a trading bot?

A trading bot is a software program that automates buying and selling financial assets like stocks and cryptocurrencies based on pre-defined strategies and rules.

These automated systems can manage portfolios without human intervention, operating 24/7.
2. Let's make a Bitcoin Trading bot

We'll use investing-algorithm-framework in Python Image
Read 11 tweets
Quant Science Profile picture
Jan 6
🚨 BREAKING: I just stumbled upon this Machine Learning Python library for Algorithmic Trading that looks insane.

It's called AlphaPy.

This is what it does: Image
AlphaPy is a machine learning framework for both speculators and data scientists.

It is written in Python with the scikit-learn and pandas libraries, as well as many other helpful libraries for feature engineering and visualization.

Here's some of what it does:
1. Run machine learning models using scikit-learn and xgboost.

2. Create models for analyzing the markets with MarketFlow.

3. Predict sporting events with SportFlow.

4. Develop trading systems and analyze portfolios using MarketFlow and Quantopian’s pyfolio.
Read 12 tweets
Quant Science Profile picture
Jan 4
How to make a simple algorithmic trading strategy with a 472% return using Python.

A thread. 🧵 Image
This strategy takes advantage of "flow effects", which is how certain points in time influence the value of an asset.

This strategy uses a simple temporal shift to determine when trades should exit relative to their entry for monthly boundary conditions. Image
The signals for when to go short, when to cover shorts, when to go long, and when to close longs are all linked to these recurring monthly cycles.

This periodic "flow" of signals—month-in, month-out—creates a systematic pattern. Image
Read 10 tweets
Quant Science Profile picture
Jan 1
According to Ray Dalio, the easiest way to adjust for risk is to seek uncorrelated returns.

Ray's made billions from a simple idea.

Here's how to do it in a few lines of Python code: Image
Step 1: Collect Stock Data

Run this code to download free stock price data from Yahoo Finance. Image
Step 2: Convert Prices to Returns

Using pandas code, we can get returns (just run this code): Image
Read 9 tweets
Quant Science Profile picture
Jan 1
Top 10 Algorithmic Trading Strategies (and how they work) 🧵 Image
1. Pairs Trading

Trades two correlated instruments simultaneously. It goes long on one asset and short on the other to profit from deviations from their historical relationship, expecting the correlation to eventually resume.
2. Scalping

Involves making numerous small trades to capture minimal price differences over a short time. For example, tape reading is used to analyze order flow and timing, enabling scalpers to profit from very brief price fluctuations.
Read 16 tweets
Quant Science Profile picture
Dec 31, 2025
12 Python libraries for free market data everyone should know: Image
yfinance

Data for stocks (historic, intraday, fundamental), FX, crypto, and options. Uses Yahoo Finance so any data available through Yahoo is available through yfinance.

github.com/ranaroussi/yfi…
pandas-datareader

pandas-datareader used to be part of the pandas project. Now an independent project. Includes data for stocks, FX, economic indicators, Fama-French factors, and many others.

pandas-datareader.readthedocs.io/en/latest/
Read 18 tweets

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