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Oct 7 11 tweets 4 min read Read on X
Build an End-to-End Python Algorithmic Trading System (complete roadmap + skills + tools)

Bookmark this. Image
1) Foundations (1–2 weeks)

Learn these:

1. Python basics → data/ML
2. Pandas (data wrangling)
3. Scikit-learn (ML)
4. SQLAlchemy (DB access) Image
2) Data & Storage (free+paid)

1. Prices: yfinance (free)
2. Fundamentals: FMP (paid)
3. DB: DuckDB (fast, file-based)

Tip: go from raw data ▶ cleaned ▶ features as separate SQL tables. Image
3) Quant Research Lab

1. Track & compare ideas: MLflow (free)
2. Core playbooks: Momentum, Mean-Reversion, Seasonality
3. Metric stack: Sharpe, Sortino, MaxDD, hit-rate, turnover

Here's what my quant research lab looks like: Image
4) ML in the Loop (8-step flow)

1. Universe selection
2. Feature engineering (momentum, quality)
3. Time-series CV (no leakage)
4. Model training (XGBoost)
5. Validation (IC, IC-IR, feat importance)
6. Signal creation (scores)
7. Backtest (Zipline/VectorBT)
8. Portfolio analysis Image
5) Execution & Automation

1. Orchestration: Prefect (free)
2. Broker: IBKR
3. Daily job: fetch → score → allocate → trade → log
4. Guardrails: position limits, slippage, stop rules

I use IBKR + Prefect (Orchestration) Image
Starter quant stack (copy/paste these tools + skills to replicate a $20,000 terminal):

1. Python, Pandas, Polars, Scikit-learn
2. DuckDB, SQLAlchemy
3. yfinance, FMP
4. MLflow, Prefect
5. IBKR API Image
I have one more thing before you go.

If you want to become an algorithmic trader in 2025, then I'd like to help.

This is how: 👇
🚨Free Training: How I built my hedge fund in Python

• QSConnect: Build your quant research database
• QSResearch: Research and run machine learning strategies
• Omega: Automate 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. - It took me 3 years to become confident in algorithmic trading.

So I spent 100 hours and made a free course to help others.

Join my free Algo Trading with Python Course + Roadmap here: startalgorithmictrading.com/beginners-algo…

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More from @quantscience_

Oct 7
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
Oct 1
Stock Prediction AI: Using Machine Learning and Deep Learning to predict stock price movements in Python.

The Python code is 100% free on GitHub.

Let's dive in (bookmark this): Image
1. The Python Machine Learning and Deep Learning Libraries:

- mxnet
- gluon
- sklearn
- xgboost Image
2. Stock Price Data (Train/Test)

The dashed vertical line represents the separation between training and test data.

GS is shown but will use 72 assets.

Daily prices for each asset. Image
Read 9 tweets
Sep 30
Things you don’t need to start quant trading:

• Complex algorithms
• PhD in math
• $10,000,000

Things you do need to start quant trading:

• A $500 laptop
• Interactive Brokers
• Python

Want to learn how? Image
🚨 LIVE Python Algo Trading Workshop: Learn how we built our hedge fund

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

👉 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
Read 4 tweets
Sep 30
OpenBB: A free alternative to the $20,000 Bloomberg Terminal

Available 100% free on GitHub: Image
Get OpenBB on Github here: github.com/OpenBB-finance…Image
🚨Want to become a pro algorithmic trader with Python?

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

👉 Join Our Free Workshop: learn.quantscience.io/become-a-pro-q…Image
Read 5 tweets
Sep 27
Python is wild for finance.

You can get FinViz in Python for free (this is how):

(a thread) Image
1. What is finvizfinance?

finvizfinance is a package that collects financial information from FinViz website. It has:

- Stock charts, fundamental & technical information
- Insider information
- Stock news
- Forex charts
- Crypto charts

Here's some examples of what you can do: Image
2. Stock Quotes, Charts & Fundamentals

Getting information (fundament, description, outer rating, stock news, inside trader) of an individual stock. Image
Read 9 tweets
Sep 26
🚨BREAKING: Microsoft open-sourced an AI Quant investment platform in Python

This is what you need to know:

(a thread) Image
1. What is Qlib?

Qlib is an open-source, AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing production. Image
2. How it works

Qlib provides an automated quant research workflow that builds the dataset, trains models, backtests, and evaluates the results. Image
Read 8 tweets

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