Analyst Estimates

Analyst Estimates

Retrieve analyst financial estimates for public companies using Octagon MCP.

Prerequisites

Ensure Octagon MCP is configured in your AI agent (Cursor, Claude Desktop, Windsurf, etc.). See [references/mcp-setup.md](references/mcp-setup.md) for installation instructions.

Query Format

Retrieve analyst financial estimates for  for the annual period, limited to  records on page 0.

MCP Call:

{
  "server": "octagon-mcp",
  "toolName": "octagon-agent",
  "arguments": {
    "prompt": "Retrieve analyst financial estimates for AAPL for the annual period, limited to 10 records on page 0"
  }
}

Output Format

The agent returns a table with analyst estimates across future periods:

| Fiscal Year Ending | Revenue Estimate (Low to High) | Revenue Avg | EPS Estimate (Low to High) | EPS Avg | # Revenue Analysts | # EPS Analysts | |-------------------|-------------------------------|-------------|---------------------------|---------|-------------------|----------------| | 2030-09-27 | $540.64B - $600.88B | $566.24B | $12.01 - $13.78 | $12.77 | 9 | 6 | | 2029-09-27 | $520.95B - $578.99B | $545.62B | $10.62 - $12.17 | $11.28 | 13 | 6 | | 2028-09-27 | $515.19B - $520.48B | $517.84B | $8.96 - $11.18 | $10.20 | 18 | 15 | | 2027-09-27 | $474.27B - $531.94B | $490.97B | $8.41 - $9.77 | $9.23 | 31 | 30 | | 2026-09-27 | $445.03B - $483.54B | $460.35B | $7.84 - $8.92 | $8.42 | 24 | 29 |

Data Source: octagon-financials-agent

Key Observations Pattern

After receiving data, generate observations:

1. Growth trajectory: Calculate implied revenue and EPS CAGR
2. Estimate dispersion: Analyze spread between low and high estimates
3. Analyst coverage: Note number of analysts covering each period
4. Near vs far-term: Compare confidence in near-term vs long-term estimates
5. Historical comparison: Compare estimates to actual historical performance

Metrics Reference

| Metric | Definition | |--------|------------| | Revenue Estimate (Low to High) | Range of analyst revenue projections | | Revenue Avg | Consensus average revenue estimate | | EPS Estimate (Low to High) | Range of analyst EPS projections | | EPS Avg | Consensus average EPS estimate | | # Revenue Analysts | Number of analysts providing revenue estimates | | # EPS Analysts | Number of analysts providing EPS estimates |

Analysis Tips

Implied Growth Rate

Implied CAGR = (Future Estimate / Current)^(1/Years) - 1

Example: ($566B / $416B)^(1/5) - 1 = 6.4% revenue CAGR

Estimate Dispersion

Dispersion = (High - Low) / Average × 100

• Narrow dispersion (20%) = Significant uncertainty

Analyst Coverage Quality

• More analysts = more reliable consensus
• Declining coverage = less institutional interest
• <5 analysts = thin coverage, use caution

Forward P/E Calculation

Forward P/E = Current Price / EPS Estimate

Use for valuation relative to growth expectations.

Estimate Revisions (with follow-up)

Track changes over time:

• Upward revisions = positive momentum
• Downward revisions = negative momentum
• Frequency of revisions matters

Valuation Applications

DCF Inputs

Use estimates for:

• Revenue projections
• Margin assumptions (with historical data)
• Terminal growth rate guidance

Relative Valuation

Compare:

• Forward P/E to historical average
• Forward P/E to peers
• PEG ratio (P/E / Growth rate)

Earnings Surprise Potential

Compare estimates to:

• Management guidance
• Historical beat/miss rate
• Recent operating trends

Confidence Assessment

High Confidence Estimates

• Near-term (1-2 years out)
• Many analysts covering
• Narrow dispersion
• Stable business model

Low Confidence Estimates

• Long-term (5+ years out)
• Few analysts covering
• Wide dispersion
• Rapidly changing industry

Follow-up Queries

Based on results, suggest deeper analysis:

• "What factors are driving the projected revenue growth from [YEAR1] to [YEAR2]?"
• "How do these estimates compare to [COMPANY]'s historical financial performance?"
• "What are the key risks to achieving the upper end of these revenue estimates?"
• "Retrieve analyst price targets and ratings for [TICKER]"

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: OctagonAI
• Source: OctagonAI/skills
• License: MIT
• Homepage: https://octagonai.co

Install and usage instructions live in the source repository linked above.