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Quantitative Economics with Python — Lectures
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by QuantEcon
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econometricseducationnumerical methodspythonquantitative economics
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Build the foundations
Suggested foundations for financial time series and optimisation and numerical methods. Specialist prerequisites vary by resource.
Before you read
- Stationarity and Unit Roots
Check whether a relationship can be estimated consistently over time.
- Linear Regression
Read the fitted relationship and its residuals.
- Vectors, Matrices and Linear Systems
Read the linear algebra used to define a numerical problem.
- Constrained and Convex Optimisation
Identify the objective, constraints and conditions for an optimum.
Go further
- Cointegration and Error Correction
Study long-run relationships without confusing them with correlation.
- Regression Assumptions and Diagnostics
Check the assumptions behind reported estimates.
- Calibration as an Inverse Problem
Understand identifiability and fitted model parameters.
Explore a related reading path
- From trading ideas to honest backtests
Choose a reproducible strategy, specify the trading rule, and test what remains after costs and estimation uncertainty.