Earnings Preview
description: Build pre-earnings analysis with estimate models, scenario frameworks, and key metrics to watch. Use before a company reports quarterly earnings to prepare positioning notes, set up bull/bear scenarios, and identify what will move the stock. Triggers on "earnings preview", "what to watch for [company] earnings", "pre-earnings", "earnings setup", or "preview Q[X] for [company]".
Workflow
Step 1: Gather Context
- Identify the company and reporting quarter
- Pull consensus estimates via web search (revenue, EPS, key segment metrics)
- Find the earnings date and time (pre-market vs. after-hours)
- Review the company's prior quarter earnings call for any guidance or commentary
Step 2: Key Metrics Framework
Build a "what to watch" framework specific to the company:
Financial Metrics:
- Revenue vs. consensus (total and by segment)
- EPS vs. consensus
- Margins (gross, operating, net) — expanding or contracting?
- Free cash flow
- Forward guidance vs. consensus
Operational Metrics (sector-specific):
- Tech/SaaS: ARR, net retention, RPO, customer count
- Retail: Same-store sales, traffic, basket size
- Industrials: Backlog, book-to-bill, price vs. volume
- Financials: NIM, credit quality, loan growth, fee income
- Healthcare: Scripts, patient volumes, pipeline updates
Step 3: Scenario Analysis
Build 3 scenarios with stock price implications:
| Scenario |
Revenue |
EPS |
Key Driver |
Stock Reaction |
| Bull |
|
|
|
|
| Base |
|
|
|
|
| Bear |
|
|
|
|
For each scenario:
- What would need to happen operationally
- What management commentary would signal this
- Historical context — how has the stock moved on similar prints?
Step 4: Catalyst Checklist
Identify the 3-5 things that will determine the stock's reaction:
- [Metric] vs. [consensus/whisper number] — why it matters
- [Guidance item] — what the buy-side expects to hear
- [Narrative shift] — any strategic changes, M&A, restructuring
Step 5: Output
One-page earnings preview with:
- Company, quarter, earnings date
- Consensus estimates table
- Key metrics to watch (ranked by importance)
- Bull/base/bear scenario table
- Catalyst checklist
- Trading setup: recent stock performance, implied move from options
Important Notes
- Consensus estimates change — always note the source and date of estimates
- "Whisper numbers" from buy-side surveys are often more relevant than published consensus
- Historical earnings reactions help calibrate expectations (search for "[company] earnings reaction history")
- Options-implied move tells you what the market expects — compare to your scenarios
Hermes Profile Notes
This skill was packaged from pi-financial-services source path plugins/vertical-plugins/equity-research/skills/earnings-preview for the Hermes financial-services profile. Use institutional data connectors first when available, cite sources, and stage outputs for qualified human review.
Common Pitfalls
- Do not present drafts as investment, legal, tax, or accounting advice.
- Do not use web search as the primary source when an institutional MCP/data connector is available.
- Do not execute transactions, contact clients, post to a ledger, or approve onboarding. Stage outputs for review.
Verification Checklist
1---2name: earnings-preview3description: Use when financial-services work requires earnings Preview.4license: MIT5---67# Earnings Preview89description: Build pre-earnings analysis with estimate models, scenario frameworks, and key metrics to watch. Use before a company reports quarterly earnings to prepare positioning notes, set up bull/bear scenarios, and identify what will move the stock. Triggers on "earnings preview", "what to watch for [company] earnings", "pre-earnings", "earnings setup", or "preview Q[X] for [company]".1011## Workflow1213### Step 1: Gather Context1415- Identify the company and reporting quarter16- Pull consensus estimates via web search (revenue, EPS, key segment metrics)17- Find the earnings date and time (pre-market vs. after-hours)18- Review the company's prior quarter earnings call for any guidance or commentary1920### Step 2: Key Metrics Framework2122Build a "what to watch" framework specific to the company:2324**Financial Metrics:**25- Revenue vs. consensus (total and by segment)26- EPS vs. consensus27- Margins (gross, operating, net) — expanding or contracting?28- Free cash flow29- Forward guidance vs. consensus3031**Operational Metrics** (sector-specific):32- Tech/SaaS: ARR, net retention, RPO, customer count33- Retail: Same-store sales, traffic, basket size34- Industrials: Backlog, book-to-bill, price vs. volume35- Financials: NIM, credit quality, loan growth, fee income36- Healthcare: Scripts, patient volumes, pipeline updates3738### Step 3: Scenario Analysis3940Build 3 scenarios with stock price implications:4142| Scenario | Revenue | EPS | Key Driver | Stock Reaction |43|----------|---------|-----|------------|----------------|44| Bull | | | | |45| Base | | | | |46| Bear | | | | |4748For each scenario:49- What would need to happen operationally50- What management commentary would signal this51- Historical context — how has the stock moved on similar prints?5253### Step 4: Catalyst Checklist5455Identify the 3-5 things that will determine the stock's reaction:56571. [Metric] vs. [consensus/whisper number] — why it matters582. [Guidance item] — what the buy-side expects to hear593. [Narrative shift] — any strategic changes, M&A, restructuring6061### Step 5: Output6263One-page earnings preview with:64- Company, quarter, earnings date65- Consensus estimates table66- Key metrics to watch (ranked by importance)67- Bull/base/bear scenario table68- Catalyst checklist69- Trading setup: recent stock performance, implied move from options7071## Important Notes7273- Consensus estimates change — always note the source and date of estimates74- "Whisper numbers" from buy-side surveys are often more relevant than published consensus75- Historical earnings reactions help calibrate expectations (search for "[company] earnings reaction history")76- Options-implied move tells you what the market expects — compare to your scenarios7778## Hermes Profile Notes79This skill was packaged from `pi-financial-services` source path `plugins/vertical-plugins/equity-research/skills/earnings-preview` for the Hermes financial-services profile. Use institutional data connectors first when available, cite sources, and stage outputs for qualified human review.808182## Common Pitfalls831. Do not present drafts as investment, legal, tax, or accounting advice.842. Do not use web search as the primary source when an institutional MCP/data connector is available.853. Do not execute transactions, contact clients, post to a ledger, or approve onboarding. Stage outputs for review.868788## Verification Checklist89- [ ] Inputs, assumptions, dates, and currencies are explicit.90- [ ] Numbers tie across tables, models, decks, and memos.91- [ ] Sources are cited and institutional data is preferred where available.92- [ ] Output is labeled draft / for human review where appropriate.