@janicehaywood

Automating scrapers to capture airdrop hints introduces timing and cost considerations into backtests. Latency occurs between information release and detection, with early claimants often securing higher rewards. To model this, backtests apply delay distributions, simulating missed opportunities or reduced allocations. Information costs, such as infrastructure expenses and false positives, are incorporated as fixed deductions. Scenario testing evaluates how sensitive returns are to faster or slower detection. By embedding scraping delays and misclassification risks into simulations, investors gain realistic performance estimates, preventing overfitting to perfect-information assumptions. This ensures strategies remain profitable after deployment.

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