Equity Research Earnings Update Report
Create professional 8-12 page earnings update reports analyzing quarterly results with beat/miss analysis, updated estimates, and revised thesis.
Earnings drop after-hours and you have 24 hours to publish a credible update — building a professional post-earnings report from scratch under time pressure requires a structured framework that ensures nothing gets missed.
Who it's for: equity research analysts, sell-side associates, buy-side analysts, portfolio managers, hedge fund analysts
Example
"Create an earnings update for Nike Q2 FY24" → Professional 8-12 page DOCX report with beat/miss analysis, 8-12 charts, updated estimates table (old vs. new), revised price target, and complete source citations
New here? 3-minute setup guide → | Already set up? Copy the template below.
# Equity Research Earnings Update
Create professional **EARNINGS UPDATE REPORTS** analyzing quarterly results for companies already under coverage, following institutional standards (JPMorgan, Goldman Sachs, Morgan Stanley format).
**Key Characteristics:**
- **Length**: 8-12 pages
- **Word Count**: 3,000-5,000 words
- **Tables**: 1-3 summary tables (NOT comprehensive)
- **Figures**: 8-12 charts
- **Turnaround**: 1-2 days (within 24-48 hours of earnings)
- **Audience**: Clients already familiar with the company
- **Focus**: What's NEW - beat/miss, updated estimates, thesis impact
- **Font**: Times New Roman throughout (unless user specifies otherwise)
## When to Use
Use when the user requests:
- "Create an earnings update for [Company] Q3 2024"
- "Analyze [Company]'s quarterly results"
- "Post-earnings report for [Company]"
- "Q1/Q2/Q3/Q4 update for [Company]"
**Do NOT use if:**
- User requests "initiation report" -> Use different skill
- User requests "flash note" or "quick take" -> Different format
- Company is not already covered -> Need initiation first
## Critical Requirements
### 1. Speed & Timeliness
- Publish within 24-48 hours of earnings release
- Focus on NEW information only
- Don't rehash company background extensively
### 2. Beat/Miss Analysis
- Lead with whether company beat or missed estimates
- Quantify variances (e.g., "Revenue beat by $120M or 3%")
- Explain WHY results differed from expectations
### 3. Summary Format
- Keep tables to 1-3 (summary only, not comprehensive)
- No full P&L/Cash Flow/Balance Sheet (just key metrics)
- Assume reader has seen initiation report
### 4. Citations & Source Attribution
Properly cite all data with SPECIFIC sources and CLICKABLE HYPERLINKS.
Include specific citations WITH CLICKABLE LINKS in every figure and table.
### 5. Updated Estimates
- Update forward estimates based on results
- Show old vs. new estimates clearly
- Explain what changed and why
## High-Level Workflow
### Phase 1: Data Collection (30-60 minutes)
- Search for latest earnings release and transcript
- Verify dates are current (not training data)
- Collect consensus estimates for comparison
### Phase 2: Analysis (2-3 hours)
- Beat/miss analysis for each key metric
- Segment/geographic/product breakdown
- Margin and guidance analysis
- Update financial model and estimates
### Phase 3: Chart Generation (1-2 hours)
Create 8-12 charts focusing on quarterly trends and what's new.
### Phase 4: Report Creation (2-3 hours)
Create 8-12 page DOCX report with structured sections.
### Phase 5: Quality Check & Delivery (30 minutes)
Verify content, formatting, accuracy, and timeliness before delivery.
## Output Specification
**Primary Deliverable**: DOCX report (8-12 pages)
**File Name**: `[Company]_Q[Quarter]_[Year]_Earnings_Update.docx`
## Key Differences from Initiation Report
| Aspect | Earnings Update | Initiation Report |
|--------|----------------|-------------------|
| **Length** | 8-12 pages | 30-50 pages |
| **Words** | 3,000-5,000 | 10,000-15,000 |
| **Tables** | 1-3 summary | 12-20 comprehensive |
| **Figures** | 8-12 | 25-35 |
| **Turnaround** | 1-2 days | 3-6 weeks |
| **Scope** | Quarterly results | Complete company |
| **Focus** | What's NEW | Everything |
## Dependencies
**Required:**
- Python (matplotlib, pandas, seaborn) for chart generation
- DOCX skill for report creation
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What This Does
Generates institutional-quality earnings update reports (JPMorgan, Goldman Sachs, Morgan Stanley format) for companies already under coverage. Focuses on what's NEW — beat/miss analysis, key metrics, updated estimates, and revised thesis. Designed for 24-48 hour turnaround after earnings.
Quick Start
Step 1: Create a Project Folder
Create a folder for the company's earnings analysis and place the downloaded template inside as CLAUDE.md.
Step 2: Download the Template
Click Download above, then move the file into your project folder as CLAUDE.md.
Step 3: Start Working
"Create an earnings update for Tesla Q3 2024"
"Analyze Apple's quarterly results"
"Post-earnings report for Microsoft"
Connect a Live Data Source (Optional)
The template structures the update. It still needs the quarter's reported numbers and what management said on the call.
Option A: live data through MCP. Connect Claude Code to Fiscal.ai and Claude pulls standardized financials, ratios, filings and earnings call transcripts itself. Every plan starts with a 7-day free trial that includes the MCP connection:
claude mcp add --transport http fiscal https://api.fiscal.ai/mcp
The Fiscal.ai MCP earnings note walkthrough covers the setup and a full worked example.
Option B: free. Pull US company data from yfinance with the Financial Data Collector playbook, or paste the figures from the press release and filings yourself.
The Fiscal.ai link is an affiliate link: we may earn a commission if you subscribe, at no extra cost to you.
Output Specifications
| Spec | Details |
|---|---|
| Length | 8-12 pages |
| Word Count | 3,000-5,000 words |
| Tables | 1-3 summary tables |
| Charts | 8-12 figures |
| Format | DOCX with Times New Roman |
| Turnaround | 1-2 days |
Key Differences from Initiation Reports
Earnings updates are 8-12 pages (vs. 30-50 for initiations), focus only on what's new, use 1-3 summary tables (vs. 12-20), and assume the reader already knows the company.
Dependencies
- Python (matplotlib, pandas, seaborn) for chart generation
- DOCX creation capabilities for the final report