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Python for Finance: pandas & numpy

The pandas and numpy moves that every quant and FDE screen expects: date-indexed Series and DataFrames, simple vs log returns, rolling windows, index alignment, VWAP, position-based P&L without look-ahead, and vectorized portfolio math.

32 min · 7 steps · videoJump to quiz ↓

How to Calculate Multi-security Portfolio Variance & Volatility with Python in 5 Minutes Matt Macarty · 6 min

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Step 1 of 7 · Overview32 min read ·

Key idea

Prereqs: Python basics (names, dicts, functions). Next: Statistics for quants; Build a simple backtester. Sources: pandas and NumPy official documentation. All prices are a toy ticker AAA; every number below was produced by running the code shown (pandas 3.0, NumPy 2.5).

Next: 1. Series, DataFrame, DatetimeIndex

Python for Finance: pandas & numpy

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