by Andrea Molent, Michel Vellekoop
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Suggested foundations for optimisation and numerical methods and financial machine learning. Specialist prerequisites vary by paper.
Read the linear algebra used to define a numerical problem.
Identify the objective, constraints and conditions for an optimum.
Preserve time order and avoid future information in training.
Establish an interpretable baseline before a flexible model.
Understand identifiability and fitted model parameters.
Separate model error from unstable numerical computation.
Account for dependence and overlapping observations.
Choose a reproducible strategy, specify the trading rule, and test what remains after costs and estimation uncertainty.