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Quant Science Profile picture
@quantscience_
Aug 9, 2025 β€’ 9 tweets β€’ 3 min read β€’ Read on X
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A 23-page research paper reveals the number 1 method Hedge Funds use to beat the market:

Time Series Momentum

This is how: 🧡 Image
1. What Is Time Series Momentum?

Time Series Momentum (TSMOM) bets on trends continuing. If a stock’s up, buy more; if down, sell. A 2011 study of 58 assets proved it works! Image
2. The Data Behind the Strategy

The TSMOM paper analyzed equities, currencies & more. T-stats showed consistent profits across 1-month lookbacks! Image
3. Coding TSMOM with Python

Code TSMOM in Python:
- Use yfinance to get data
- Then momentum = price[-1] / price[-20] - 1.

Positive? Buy
Negative? Sell Image
4. Real-World Performance

TSMOM outperforms passive investing.

We're using a modified version of TSMOM in our Hedge Fund.

One backtest shows 3500% return vs 450% S&P500. Image
We are using TSMOM in our hedge fund.

And we'd like to share exactly how it works.

Want to see how we built our hedge fund in Python?

Then join us for our free training:
🚨 FREE Python Algo Trading Workshop: Learn how we built our hedge fund

β€’ QSConnect: Build your quant research database
β€’ QSResearch: Research and run machine learning strategies
β€’ Omega: Automate trade execution with Python

πŸ‘‰ Get the system: 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 to learn Algorithmic Trading Strategies that actually work?

I'm hosting a live workshop. Join here: learn.quantscience.io/qs-register

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More from @quantscience_

Quant Science Profile picture
May 9
A 23-page research paper reveals the number 1 method Hedge Funds use to beat the market:

Time Series Momentum

This is how: 🧡 Image
1. What Is Time Series Momentum?

Time Series Momentum (TSMOM) bets on trends continuing. If a stock’s up, buy more; if down, sell. A 2011 study of 58 assets proved it works! Image
2. The Data Behind the Strategy

The TSMOM paper analyzed equities, currencies & more. T-stats showed consistent profits across 1-month lookbacks! Image
Read 9 tweets
Quant Science Profile picture
Apr 30
🚨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
Read 8 tweets
Quant Science Profile picture
Apr 27
A Bloomberg Terminal costs $30,000 a year.

Here's how to build 90% of it for free.

Wall Street doesn't advertise this. But every function that matters has a free alternative in Python.

Here's the DIY version (with Python): Image
━━━━━━━━━━━━━━━━━
πŸ”Ή REAL-TIME PRICES & CHARTS
━━━━━━━━━━━━━━━━━
Bloomberg: GP
Python: yfinance + Plotly

yfinance pulls live and historical price data for any ticker in seconds. Plotly turns it into interactive charts. Add your own indicators, overlays, and alerts. No subscription needed.
━━━━━━━━━━━━━━━━━
πŸ”Ή FINANCIAL STATEMENTS & RATIOS
━━━━━━━━━━━━━━━━━
Bloomberg: FA
Python: yfinance + pandas

yfinance exposes full income statements, balance sheets, and cash flow statements directly. Pull any company's financials into a DataFrame, calculate your own ratios, and build custom models β€” all in a notebook.
Read 10 tweets
Quant Science Profile picture
Apr 27
The secret of hedge funds is revealed in a 41-page PDF:

This paper analyzed 464 stocks that 10X-ed over a 24-year period.

Here are the best factors that drive outperformance: (number 3 is the best 🧡) Image
1. Size Effect

"Small-cap stocks outperform medium and large companies in 11 out of 12 cases"

Smaller stocks tend to perform better, but it's not the only contributor. Image
2. Value Effect

"A low book-to-market value (B/M < 1), i.e., low equity and relatively high market cap, implies that investors are paying more for a company than its net assets are worth."

Don't overpay - Overpaying tends to drive underperformance. Image
Read 8 tweets
Quant Science Profile picture
Apr 20
A 23-page research paper reveals the number 1 method Hedge Funds use to beat the market:

Time Series Momentum

This is how: 🧡 Image
1. What Is Time Series Momentum?

Time Series Momentum (TSMOM) bets on trends continuing. If a stock’s up, buy more; if down, sell. A 2011 study of 58 assets proved it works! Image
2. The Data Behind the Strategy

The TSMOM paper analyzed equities, currencies & more. T-stats showed consistent profits across 1-month lookbacks! Image
Read 9 tweets
Quant Science Profile picture
Apr 14
🚨BREAKING: Python's Newest Algorithmic Trading Tool.

Introducing Nautilus Trader. 100% free.

Here's what it does (and how to get started in under 3 minutes): Image
Nautilus Trader is an open-source Python library for production-grade algorithmic trading.

- Fast: made with Rust for blazing speed
- Natively runs with Python
- Risk management
- Backtesting
- Highly extendable
Nautilus Trader includes a full trading platform with these core components:

- Portfolio
- Trader: Accounts + Trading Strategies
- Caching
- Data Engine: Data providers
- Risk Engine
- Execution Engine Image
Read 9 tweets

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