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Quants β€οΈ statistical arbitrage. Pairs trading is a great way to get started with algorithmic trading. Hereβs how to build a pairs trading strategy in Python. Step by step:
Portfolio managers talk a lot about alpha. But to find alpha, they hedge beta. Hereβs how with Python:
Finance is more exciting than a blockbuster thriller. But most people don't know where to look for the best stories. Here are 7 books you probably know nothing about:
Returns are not normally distributed. Why do your metrics assume they are? The Omega ratio considers the full distribution. Hereβs how in Python:
Finance Database 300,000+ symbols containing Equities, ETFs, Funds, Indices, Currencies, Cryptocurrencies, and Money Markets. Get it for free:
Jupyter Notebook is the most powerful tool Python developers have. But most people donβt know the hidden features. Need a quick web app? Or to create REST APIs? Here's the 6 wa...
Everyone talks about alpha. Clients pay a lot of money for it. Fund managers hire Ph.D.s to find it. But before you can have alpha, you need to hedge beta. Hereβs how you can do...
Want to get started with Python for quant finance? Set up your own custom quant lab. Start with these 14 (free) Python libraries:
Jane Street, Man Group, and Goldman Sachs all have one thing in common. They have teams of people managing internal data. Get started building your own quant database:
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: