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Where finance practitioners get started with Python for quant finance, algorithmic trading, and data analysis | Tweets & threads with free Python code & tools.
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9 technical trading strategies everyone should know (with Python code):
Options models are wrong. Implied volatility is not the same over the life of an option. Prove it with volatility surfaces. Here's how to do it in Python (step by step):
13 Python libraries for free market data everyone should know:
Quants use the volatility surface to price exotic options, calibrate models, and find mispricings. You can build your own volatility surface with Python:
A Bloomberg Terminal costs $27,660 per year. It's the portal to all the world's financial data. Unaffordable for 99% of us. Reserved for the Wall Street elite to outfox the norm...
The most-used analytics software of the last 37 years: Excel But Excel on your resume is no longer enough to get a quant job. Because Python is the new Excel. But with 533,000,...
99% of beginners get backtesting wrong: Build backtest, get poor results. Tweak backtest, get positive results. Then they wonder why they lose money. Here's the dead-simple fram...
Introducing Getting Started With Python for Quant Finance. A cohort-based course and community that will take you from complete beginner to up and running with Python for quant fi...
Skip the quant finance degree. Dive into 17 code repos that will teach you more than all your professors at school. All without costing you $90,000:
My rocket scientist professor told me to learn Octave during my master's degree ("it's free MATLAB"). So I watched 197 YouTube videos to learn Python instead. 94.4% of them were...
Professional investors know returns are not normally distributed. So they use the Omega ratio to capture the full distribution. You don’t need to be a professional to do it too....
Myth: You need a PhD to get started with Python for quant finance. Reality: You need Jupyter Notebooks pre-built with quant code. Get 20 with Getting Started With Python for Qu...