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Awesome-Quant-Machine-Learning-Trading
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by grananqvist
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algorithmic tradingfinancial machine learningquant researchresource list
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Build the foundations
Suggested foundations for financial machine learning and trading research and honest backtests. Specialist prerequisites vary by resource.
Before you read
- Time-Ordered Train, Validation and Test Design
Separate model selection from the final evaluation.
- Linear Regression
Establish an interpretable baseline before a flexible model.
- Point-in-Time Data
Use only information available at the simulated decision time.
Go further
- Finance-aware validation
Account for dependence and overlapping observations.
- Feature importance
Examine which information contributes to predictions.
- Positions, Trades, Fills and P&L
Reconcile signals, executions, positions and P&L.
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.