Market Replay & Performance Analytics Lab

Clear learning outcomes.

• ✓ Historical replay without future leakage sits inside the module 'Replay Protocol and Information Control'. The analytical objective in this lesson is measurement discipline. Start by defining the object being measured, the timestamp at which it becomes observable, and the unit in which it will be compared. Do not move from an observation to a directional claim unless the rule explicitly defines that inference and the evidence supports it.
• ✓ Decision timestamps and frozen information sets sits inside the module 'Replay Protocol and Information Control'. The operational objective is repeatability. Another analyst using the same data, rule version and sequence should be able to reproduce the classification. Ambiguous cases are not forced into a preferred category; they are tagged unresolved and retained in the evidence set.
• ✓ Evidence capture and screenshots sits inside the module 'Replay Protocol and Information Control'. The review objective is robustness. The method is evaluated across ordinary, adverse and boundary cases. A result that appears only after hindsight selection, favorable fill assumptions or post-outcome rule changes is treated as weak evidence.
• ✓ Required journal fields sits inside the module 'Journal Schema and Setup Taxonomy'. The analytical objective in this lesson is measurement discipline. Start by defining the object being measured, the timestamp at which it becomes observable, and the unit in which it will be compared. Do not move from an observation to a directional claim unless the rule explicitly defines that inference and the evidence supports it.
• ✓ Setup codes and context tags sits inside the module 'Journal Schema and Setup Taxonomy'. The operational objective is repeatability. Another analyst using the same data, rule version and sequence should be able to reproduce the classification. Ambiguous cases are not forced into a preferred category; they are tagged unresolved and retained in the evidence set.
• ✓ Rule versions and change control sits inside the module 'Journal Schema and Setup Taxonomy'. The review objective is robustness. The method is evaluated across ordinary, adverse and boundary cases. A result that appears only after hindsight selection, favorable fill assumptions or post-outcome rule changes is treated as weak evidence.

Structured modules.

1. 01Replay Protocol and Information ControlLessons, practical work and knowledge checks
2. 02Journal Schema and Setup TaxonomyLessons, practical work and knowledge checks
3. 03MAE, MFE and Trade Path AnalyticsLessons, practical work and knowledge checks
4. 04Execution Assumptions and Slippage ReviewLessons, practical work and knowledge checks
5. 05Rule Adherence and Error TaxonomyLessons, practical work and knowledge checks
6. 06Setup-Level Expectancy and Sample ReviewLessons, practical work and knowledge checks
7. 07Monthly Review and Decision QualityLessons, practical work and knowledge checks
8. 08Capstone Performance Analytics DossierLessons, practical work and knowledge checks