sector-pe-ratios
Retrieve sector P/E ratios using Octagon MCP. Use when comparing company valuations to sector benchmarks, analyzing sector valuations across exchanges, and understanding market-wide valuation trends.
What this skill does
# Sector P/E Ratios
Retrieve price-to-earnings ratios by sector and exchange using the Octagon MCP server.
## 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.
## Workflow
### 1. Identify Parameters
Determine your query parameters:
- **Date**: Specific date for the data
- **Exchange**: NYSE, NASDAQ, etc.
- **Sector**: Technology, Healthcare, Financials, etc.
### 2. Execute Query via Octagon MCP
Use the `octagon-agent` tool with a natural language prompt:
```
Retrieve the latest sector P/E ratios for <DATE>, filtered by exchange <EXCHANGE> and sector <SECTOR>.
```
**MCP Call Format:**
```json
{
"server": "octagon-mcp",
"toolName": "octagon-agent",
"arguments": {
"prompt": "Retrieve the latest sector P/E ratios for 2025-02-03, filtered by exchange NASDAQ and sector Technology."
}
}
```
### 3. Expected Output
The agent returns sector P/E data:
| Metric | Value |
|--------|-------|
| Sector | Technology |
| Exchange | NASDAQ |
| P/E Ratio | 58.77 |
| Date | 2025-02-03 |
**Data Sources**: octagon-stock-data-agent
### 4. Interpret Results
See [references/interpreting-results.md](references/interpreting-results.md) for guidance on:
- Comparing company P/E to sector P/E
- Historical sector valuation context
- Cross-sector comparisons
- Exchange-specific analysis
## Example Queries
**Specific Sector and Exchange:**
```
Retrieve the latest sector P/E ratios for 2025-02-03, filtered by exchange NASDAQ and sector Technology.
```
**All Sectors on Exchange:**
```
Get P/E ratios for all sectors on the NYSE.
```
**Sector Comparison:**
```
Compare P/E ratios for Technology, Healthcare, and Financials sectors.
```
**Historical Trend:**
```
What is the historical P/E trend for the Technology sector on NASDAQ?
```
**Cross-Exchange:**
```
Compare Technology sector P/E ratios on NYSE vs. NASDAQ.
```
## Understanding P/E Ratios
### Definition
```
P/E Ratio = Stock Price / Earnings Per Share
```
For sectors:
```
Sector P/E = Weighted Average P/E of all stocks in the sector
```
### Types of P/E
| Type | Description |
|------|-------------|
| Trailing P/E | Based on past 12 months earnings |
| Forward P/E | Based on estimated future earnings |
| GAAP P/E | Using GAAP earnings |
| Non-GAAP P/E | Using adjusted earnings |
## Sector Categories
### Major Sectors
| Sector | Typical P/E Range |
|--------|-------------------|
| Technology | 25-60 |
| Healthcare | 18-35 |
| Financials | 10-18 |
| Consumer Discretionary | 15-30 |
| Consumer Staples | 18-25 |
| Industrials | 15-25 |
| Energy | 8-20 |
| Utilities | 15-22 |
| Real Estate | 30-50 |
| Materials | 12-20 |
| Communications | 15-25 |
### P/E Characteristics by Sector
| Sector | P/E Tendency | Reason |
|--------|--------------|--------|
| Technology | Higher | Growth expectations |
| Financials | Lower | Mature, regulated |
| Utilities | Moderate | Stable, dividend-focused |
| Healthcare | Variable | Mix of growth/value |
## Major Exchanges
### Exchange Characteristics
| Exchange | Focus |
|----------|-------|
| NYSE | Large-cap, established |
| NASDAQ | Tech-heavy, growth |
| AMEX | Smaller companies, ETFs |
### Exchange P/E Differences
| Factor | NYSE | NASDAQ |
|--------|------|--------|
| Tech Weight | Lower | Higher |
| Average P/E | Generally lower | Generally higher |
| Growth vs. Value | More balanced | Growth-tilted |
## Using Sector P/E for Analysis
### Company Valuation Context
| Comparison | Interpretation |
|------------|----------------|
| Company P/E < Sector P/E | Potentially undervalued or issues |
| Company P/E = Sector P/E | Fairly valued relative to sector |
| Company P/E > Sector P/E | Premium valuation or overvalued |
### Premium/Discount Calculation
```
Premium/Discount = (Company P/E - Sector P/E) / Sector P/E × 100%
```
### Example
- Company P/E: 45
- Sector P/E: 58.77
- Discount: (45 - 58.77) / 58.77 = -23.4% (trading at discount)
## Historical Context
### Valuation Levels
| Sector P/E vs. History | Interpretation |
|------------------------|----------------|
| Above 10-year average | Potentially elevated |
| At 10-year average | Normal valuation |
| Below 10-year average | Potentially attractive |
### Cycle Considerations
| Phase | Typical Sector P/E Behavior |
|-------|----------------------------|
| Early Recovery | Rising from lows |
| Mid-Cycle | Moderate, stable |
| Late Cycle | Often elevated |
| Recession | Compressed or distorted |
## Cross-Sector Analysis
### Relative Value
| Comparison | Use |
|------------|-----|
| Tech vs. Financials | Growth vs. value |
| Cyclical vs. Defensive | Risk appetite |
| High vs. Low P/E | Market expectations |
### Rotation Signals
| Signal | Meaning |
|--------|---------|
| Tech P/E rising faster | Growth favored |
| Value sectors rising | Risk-off rotation |
| Convergence | Normalization |
| Divergence | Theme-driven market |
## Data Considerations
### Timing
| Factor | Consideration |
|--------|---------------|
| Earnings season | P/E updates with new earnings |
| Price movements | Daily fluctuation |
| Index rebalancing | Composition changes |
### Calculation Differences
| Source | May Differ On |
|--------|---------------|
| Weighting | Market-cap vs. equal |
| Earnings | Trailing vs. forward |
| Constituents | Index composition |
## Common Use Cases
### Stock Valuation
```
Is AAPL's P/E reasonable compared to the Technology sector?
```
### Sector Selection
```
Which sectors have the lowest P/E ratios currently?
```
### Market Timing
```
Are Technology sector valuations elevated compared to history?
```
### Portfolio Analysis
```
How do my holdings' P/E ratios compare to their sectors?
```
## Analysis Tips
1. **Compare apples to apples**: Same sector, similar companies.
2. **Consider growth**: High P/E may be justified by high growth.
3. **Check historical range**: Current vs. typical levels.
4. **Look at earnings quality**: P/E only as good as earnings.
5. **Cross-reference exchanges**: Same sector, different exchanges.
6. **Watch for outliers**: Negative earnings distort averages.
## Integration with Other Skills
| Skill | Combined Use |
|-------|--------------|
| financial-metrics-analysis | Company P/E vs. sector |
| income-statement | Earnings driving P/E |
| stock-quote | Current price context |
| analyst-estimates | Forward P/E calculation |
Related in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.