by Haochuan Wang
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Suggested foundations for monte carlo and numerical simulation and trading research and honest backtests. Specialist prerequisites vary by paper.
Understand convergence, sampling error and confidence intervals.
Generate reproducible samples and distinguish randomness from model assumptions.
Use only information available at the simulated decision time.
Separate model selection from the final evaluation.
Turn a discounted payoff into an estimator.
Study dependence and alternatives to independent sampling.
Reconcile signals, executions, positions and P&L.
Start in discrete time, move to Brownian motion, then read the original pricing argument and simulate it.
Choose a reproducible strategy, specify the trading rule, and test what remains after costs and estimation uncertainty.