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Machine Learning · Medium

Lookahead Bias

Original interpretation · Match confidence: medium

Company use unverified
About this question’s source match

The title and ML subcategory identify this topic; the linked public reference supports its mathematical structure. This numerical exercise is newly authored. Trading Interview statement is unavailable. No exact original-question match is claimed.

A model predicts next-day close-to-close return using features stamped at 16:00 each day. A researcher joins each day to its final daily high and executes a trade at 12:00 that same day. Identify lookahead bias and propose a valid protocol. Is fitting a scaler on the full sample acceptable?

Assumptions and constraints

  • Use the explicitly stated data and conventions; no external dataset is required.
  • Explain each intermediate calculation and justify the conclusion.

Examples

Trade 12:00; feature finalized 16:00
→ Invalid causal ordering

Trade occurs before feature availability.

Company evidence · unverified

No company-specific source has been matched to this exercise. Its references support the topic or solution method; they do not establish employer use.

References

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Catalogue metadata captured 2026-10-12. Metadata source.