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darts
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anomaly detectionforecastingmachine learningpythontime series
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Build the foundations
Suggested foundations for financial time series and financial machine learning. Specialist prerequisites vary by resource.
Before you read
- Stationarity and Unit Roots
Check whether a relationship can be estimated consistently over time.
- Linear Regression
Establish an interpretable baseline before a flexible model.
- Time-Ordered Train, Validation and Test Design
Preserve time order and avoid future information in training.
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.
- Finance-aware validation
Account for dependence and overlapping observations.
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.