Quant Science
@quantscience_
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Develop profitable trading strategies, build a systematic trading process, and trade your ideas with Python—even if you’ve never done it before.
Free Python newsletter 👉
Joined July 2023
🚨 Python Algo Trading Workshop on Wednesday: 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:
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P.S. - Want to learn Algorithmic Trading Strategies that actually work?. I'm hosting a live workshop. Join here:
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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.
In investing, your track record is everything. In 2 minutes, I'll uncover the secrets hedge funds use to track their portfolio performance: 🧵
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🚨 WORKSHOP: How I built an automated algorithmic trading system with Python. Hedge funds have an unfair advantage: better tools & faster execution. That ends on July 24th. 👉 Register here to learn how with Python (500 seats):
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Want to learn how we do this inside our hedge fund in Python?. In our new live workshop, we'll share everything (and you can ask any question).
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3. Drawdowns and Risks. Max Drawdown: 14.61%—peak loss to recover from. Ulcer Index: 2.80%—measures drawdown stress. Drawdown at Risk (5.21%)—likely loss duration. Use these to stress-test your strategy.
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2. Risk Measures. Std Dev: 12.41%—volatility is moderate. VaR (18.97%) & CVaR (29.76%)—expect losses up to 18.97% (95%) or 29.76% (worst cases). Worst Realization: 50.74%—a rare but brutal drop to watch.
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1. Profitability Insights. Annual Return: 22.44%—strong growth! . CAGR: 23.78%—compounded gains over time. MAR: 0% (minimum acceptable)—room to beat risk-free rates. Significance level (5%) sets the risk benchmark.
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There are 3 main areas that smart investors care about:. 1. Profits (Returns).2. Risks.3. Drawdowns. Let's break them down using the snapshot:.
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In investing, your track record is everything. In 2 minutes, I'll uncover the secrets hedge funds use to track their portfolio performance: 🧵
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P.S. - Want Algorithmic Trading with Python tutorials every Sunday?. Register here to join our Sunday Quant Scientist Newsletter (it's free):
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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.
How to simulate 20 different portfolios from an efficient frontier (in Python). A thread 🧵
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🚨 LIVE WORKSHOP: How I built an automated algorithmic trading system with Python. Hedge funds have an unfair advantage: better tools & faster execution. That ends on July 24th. 👉 Register here to learn how with Python (500 seats):
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Step 3: Optimize Sharpe Ratio & Compute the Efficient Frontier
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1. The step-by-step process. Step 1: Pull 2016–2019 data with yfinance (25 assets + 5 factors).
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How to simulate 20 different portfolios from an efficient frontier (in Python). A thread 🧵
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P.S. - Want to learn Algorithmic Trading Strategies that actually work?. I'm hosting a live workshop. Join here:
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