canonical/modules/M051-earnings-preview-and-post-earnings-procedure.md

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<!-- Module: 051 | Title: Earnings Preview and Post-Earnings Procedure -->

## PART XI - CATALYSTS AND EVENTS | MODULE 051

# Earnings Preview and Post-Earnings Procedure

> Mission. Define expectations, key debate variables, scenario reactions, and model update rules before the print.

## Decision output

Objective: Define expectations, key debate variables, scenario reactions, and model update rules before the print. The completed work product must be reproducible from evidence, show the downstream financial or decision effect when material, state the strongest contrary case, and define a dated update rule.

## Explicit operating procedure

1. Freeze the pre-earnings model, market price, consensus context, management guidance, and your own expectations before the release.

1. Write the three to five variables that matter most, expected ranges, and what result would change the thesis versus create only short-term noise.

1. After release, reconcile the filed/reported statements and KPI definitions before changing the forecast; do not react only to headline EPS or revenue beats.

1. Bridge revenue, margin, working capital, capex, cash, debt, shares, taxes, and guidance to the pre-quarter model and explain each material variance.

1. Compare prepared remarks and Q&A with prior wording for confidence, timing, KPI emphasis, and new qualifiers; management narrative remains a claim until reconciled.

1. Log forecast error, model changes, valuation change, and what the next quarter must show.

## Required evidence and model bridge

- Primary-source set: event filings, guidance, consensus context, transaction documents, covenant and liquidity data. Preserve exact document/version, date, period, and source location for every material factual input used in earnings preview and post-earnings procedure.

- For each key concept - consensus, guidance, key debate variables, precommitment, variance bridge, transcript changes - state whether it is a reported fact, analyst calculation, management claim, external estimate, or judgment. Quantitative concepts must retain raw components and units; qualitative concepts must retain the specific evidence and counterevidence.

- Map only economically relevant findings into the model or decision record. Process-control modules such as earnings preview and post-earnings procedure may have no direct valuation line; in that case document the downstream error or governance risk the control prevents.

## Metrics and calculation controls

| Metric / concept | Construction | Required validation |
| --- | --- | --- |
| expectation gap | Analyst forecast for a key driver minus the value or consensus-implied expectation, expressed in operating units and valuation impact. | expectation gap: Recalculate independently from cited source data; verify definition, period, units, scope, signs, and any reconciliation to reported financial or operating totals. |
| variance attribution | Actual minus prior forecast decomposed by driver, price, volume, mix, cost, timing, accounting, and assumption error; contributions sum to total variance. | variance attribution: Tie opening/closing balances or total change to primary-source financials; verify components sum exactly with no overlap, omission, or sign error. |
| estimate revision impact | Change in valuation or expected return caused solely by revised operating estimates, holding valuation framework and market inputs constant. | estimate revision impact: Reperform the count from the defined population, inspect every material exception, and confirm the denominator/universe did not change between periods. |



## Worked application

> Case: a revenue beat comes from low-margin mix while the thesis depends on margin recovery.

- Reconstruct the relevant reported fact from primary evidence before interpreting the case. For earnings preview and post-earnings procedure, show the raw components rather than only the resulting ratio or narrative.

- Build the causal chain through consensus, guidance, key debate variables, precommitment, then identify which link is directly observed and which link remains an assumption.

- Calculate expectation gap, variance attribution, estimate revision impact from sourced components under the reported/base interpretation and at least one skeptical alternative interpretation.

- Translate the difference between cases into the variable that matters for earnings preview and post-earnings procedure: evidence quality, revenue, operating profit/NOPAT, free cash flow, invested capital, financing/dilution, risk, or valuation. Mark non-applicable links instead of inventing them.

- Expert consistency test: define what matters before the print so headline beats cannot rewrite the thesis.

- Precommit the specific future filing, KPI, customer/supplier observation, regulator action, or market input that would materially invalidate the earnings preview and post-earnings procedure conclusion.

## Failure tests

- FAIL if consensus cannot be defined and reproduced from the source pack.

- FAIL if the analyst has not prewritten decision-relevant expectations and interpretations before the release, allowing the post-event narrative to fit any outcome.

- FAIL if the earnings preview and post-earnings procedure conclusion depends on an unstated assumption, unreconciled definition, or evidence that cannot be traced to its source/version.

- FAIL if evidence materially inconsistent with the earnings preview and post-earnings procedure conclusion is omitted, reclassified, or dismissed without a documented definition, materiality, causal, timing, and source-quality analysis.

## Completion test

A senior reviewer must be able to reproduce the earnings preview and post-earnings procedure conclusion, vary the most sensitive assumption independently, trace the change through the model, understand the strongest opposing case, and identify the next evidence that would force an update. If any link is missing, the module remains open.