by Arati Uday Kamat
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Suggested foundations for probability and statistical reasoning and trading research and honest backtests. Specialist prerequisites vary by paper.
Read the distributions and expectations used in probabilistic arguments.
Interpret expectations after information is observed.
Use only information available at the simulated decision time.
Separate model selection from the final evaluation.
Assess uncertainty rather than treating an estimate as a fact.
Reconcile signals, executions, positions and P&L.
Include the costs that can erase a paper strategy.
Move from conditioning and expected values to timed problems with a defensible solution.
Choose a reproducible strategy, specify the trading rule, and test what remains after costs and estimation uncertainty.