Stock Price Change
Retrieve comprehensive price change statistics across multiple time periods 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 for installation instructions.
Workflow
1. Identify the Stock
Determine the ticker symbol for the company you want to analyze (e.g., AAPL, MSFT, GOOGL).
2. Execute Query via Octagon MCP
Use the octagon-agent tool with a natural language prompt:
Get stock price change statistics for the symbol <TICKER>.MCP Call Format:
{
"server": "octagon-mcp",
"toolName": "octagon-agent",
"arguments": {
"prompt": "Get stock price change statistics for the symbol AAPL."
}
}3. Expected Output
The agent returns price change data across multiple timeframes:
| Time Period | Percentage Change |
|---|---|
| 1 Day | 4.06% |
| 5 Days | 4.80% |
| 1 Month | -0.37% |
| 3 Months | -0.13% |
| 6 Months | 33.42% |
| Year-to-Date (YTD) | -0.37% |
| 1 Year | 18.42% |
| 3 Years | 79.03% |
| 5 Years | 100.02% |
| 10 Years | 1,043.14% |
| All-Time High | 210,270.08% |
Key Insight: Strong long-term growth with 10-year return of 1,043.14%, but recent short-term performance slightly negative.
Data Sources: octagon-stock-data-agent
4. Interpret Results
See references/interpreting-results.md for guidance on:
- Evaluating short-term vs. long-term performance
- Understanding momentum signals
- Comparing to benchmarks
- Assessing trend consistency
Example Queries
Basic Query:
Get stock price change statistics for the symbol AAPL.Multiple Stocks:
Compare price change statistics for AAPL, MSFT, and GOOGL.Specific Focus:
What is the 1-year and 5-year return for TSLA?YTD Performance:
What is the year-to-date performance of NVDA?Long-Term Growth:
What is the 10-year cumulative return for AMZN?Understanding Time Periods
Short-Term Periods
| Period | Use Case |
|---|---|
| 1 Day | Daily momentum |
| 5 Days | Weekly trend |
| 1 Month | Recent performance |
| 3 Months | Quarterly trend |
Medium-Term Periods
| Period | Use Case |
|---|---|
| 6 Months | Half-year momentum |
| YTD | Calendar year performance |
| 1 Year | Annual return |
Long-Term Periods
| Period | Use Case |
|---|---|
| 3 Years | Business cycle |
| 5 Years | Market cycle |
| 10 Years | Secular trend |
| All-Time | Total return since inception |
Return Interpretation
Performance Classification
| Return (1 Year) | Classification |
|---|---|
| >50% | Exceptional |
| 25-50% | Very strong |
| 10-25% | Strong |
| 0-10% | Moderate |
| -10 to 0% | Weak |
| <-10% | Poor |
Long-Term Standards
| Return (10 Year) | Classification |
|---|---|
| >500% | Exceptional |
| 200-500% | Very strong |
| 100-200% | Strong |
| 50-100% | Moderate |
| 0-50% | Below average |
| <0% | Poor |
Momentum Analysis
Trend Consistency
| Pattern | Interpretation |
|---|---|
| All periods positive | Strong consistent uptrend |
| Short negative, long positive | Pullback in uptrend |
| Short positive, long negative | Bounce in downtrend |
| All periods negative | Consistent downtrend |
Momentum Signals
| Signal | Pattern |
|---|---|
| Accelerating | Returns increasing across periods |
| Decelerating | Returns decreasing across periods |
| Stable | Consistent returns across periods |
| Reversal | Sign change between periods |
Example Analysis
From AAPL data:
- 1 Day: +4.06% (strong daily)
- 1 Month: -0.37% (slight pullback)
- 1 Year: +18.42% (solid annual)
- 10 Year: +1,043.14% (exceptional long-term)
Interpretation: Long-term compounder with recent consolidation.
Annualized Returns
Calculation
Annualized Return = (1 + Total Return)^(1/Years) - 1Example
From AAPL data:
- 10-Year Return: 1,043.14%
- Annualized: (1 + 10.4314)^(1/10) - 1 = 27.3% per year
Annualized Benchmarks
| Annual Return | Rating |
|---|---|
| >25% | Exceptional |
| 15-25% | Very strong |
| 10-15% | Strong |
| 7-10% | Market-like |
| <7% | Below market |
Comparison Analysis
vs. Benchmarks
| Benchmark | What to Compare |
|---|---|
| S&P 500 | Market performance |
| Sector ETF | Industry performance |
| Peers | Competitive position |
Alpha Calculation
Alpha = Stock Return - Benchmark ReturnExample
If AAPL 1-year return is +18.42% and S&P 500 is +10%:
- Alpha: +8.42% outperformance
Time Period Relationships
Healthy Patterns
| Pattern | Interpretation |
|---|---|
| Long > Short | Healthy uptrend |
| Positive all periods | Consistent strength |
| Improving short-term | Momentum building |
Warning Patterns
| Pattern | Interpretation |
|---|---|
| Long << Short | Mean reversion risk |
| Long > 0, Short < 0 | Trend weakening |
| All negative | Fundamental issues |
All-Time High Analysis
Distance from ATH
Distance = (ATH - Current) / ATH × 100%ATH Context
| Position | Interpretation |
|---|---|
| At ATH | Maximum strength |
| 0-10% below | Near highs |
| 10-20% below | Correction |
| 20-40% below | Bear market |
| >40% below | Severe decline |
Common Use Cases
Performance Summary
What are the returns for AAPL across all time periods?Trend Analysis
Is MSFT in an uptrend or downtrend based on recent returns?Long-Term Growth
What is the 10-year cumulative return for the FAANG stocks?Momentum Check
Is NVDA showing positive momentum in the short-term?Comparison
Compare 1-year returns for major tech stocks.Analysis Tips
- Don't rely on one period: Use multiple timeframes.
- Compare to benchmarks: Returns mean more in context.
- Consider consistency: Smooth vs. volatile returns.
- Annualize long-term: For fair comparison.
- Watch for divergence: Short vs. long-term signals.
- Factor in dividends: Total return vs. price return.
Integration with Other Skills
| Skill | Combined Use |
|---|---|
| stock-quote | Current price context |
| stock-performance | Daily price data |
| stock-historical-index | vs. market returns |
| financial-metrics-analysis | Fundamentals behind returns |