/stock-performance

name: stock-performance
description: Retrieve stock price data and performance metrics using Octagon MCP. Use when analyzing daily closing prices, trading volume, price trends, historical performance, and comparing stock movements over specific time periods.

Stock Performance

Retrieve daily closing prices, trading volume, and performance metrics for public companies 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 Analysis Parameters

Determine the following before querying:

• **Ticker**: Stock symbol (e.g., AAPL, MSFT, GOOGL)
• **Time Period**: Number of days or date range
• **Metrics** (optional): Price, volume, returns

2. Execute Query via Octagon MCP

Use the `octagon-agent` tool with a natural language prompt:

Retrieve the daily closing prices for <TICKER> over the last <N> days.

**MCP Call Format:**

{
  "server": "octagon-mcp",
  "toolName": "octagon-agent",
  "arguments": {
    "prompt": "Retrieve the daily closing prices for AAPL over the last 30 days."
  }
}

3. Expected Output

The agent returns structured price data including:

| Date | Closing Price | Volume | |------|---------------|--------| | 2026-02-02 | $270.01 | 73,677,607 | | 2026-01-30 | $259.48 | 92,443,408 | | 2026-01-29 | $258.28 | 67,253,009 | | ... | ... | ... |

**Data Sources**: octagon-stock-data-agent, octagon-web-search-agent

4. Interpret Results

See [references/interpreting-results.md](references/interpreting-results.md) for guidance on:

• Analyzing price trends
• Evaluating volume patterns
• Calculating returns
• Identifying support/resistance levels

Example Queries

**Daily Closing Prices:**

Retrieve the daily closing prices for AAPL over the last 30 days.

**Extended Historical Data:**

Get historical stock prices for MSFT for the past 90 days.

**Volume Analysis:**

Retrieve daily trading volume for TSLA over the last 2 weeks.

**Price Range:**

What are the high and low prices for NVDA over the past month?

**Multi-Stock Comparison:**

Compare the stock performance of AAPL, MSFT, and GOOGL over the last 30 days.

**52-Week Analysis:**

What is the 52-week high and low for AMZN?

Key Metrics

Price Metrics

| Metric | Description | |--------|-------------| | Closing Price | End-of-day price | | Opening Price | Start-of-day price | | High | Intraday high | | Low | Intraday low | | Adjusted Close | Dividend/split adjusted |

Volume Metrics

| Metric | Description | |--------|-------------| | Daily Volume | Shares traded per day | | Average Volume | Typical daily volume | | Relative Volume | Current vs. average | | Volume Trend | Direction over time |

Return Metrics

| Metric | Calculation | |--------|-------------| | Daily Return | (Close - Prior Close) / Prior Close | | Period Return | (End - Start) / Start | | Cumulative Return | Running return over period | | Annualized Return | Period return scaled to 1 year |

Price Analysis Framework

Trend Analysis

| Pattern | Characteristics | |---------|-----------------| | Uptrend | Higher highs, higher lows | | Downtrend | Lower highs, lower lows | | Sideways | Range-bound movement | | Breakout | Move beyond range |

Volatility Assessment

| Measure | Description | |---------|-------------| | Price Range | High - Low over period | | Daily Range | Average daily high-low | | Standard Deviation | Price dispersion | | Beta | Relative to market |

Support/Resistance

| Level | Description | |-------|-------------| | Support | Price floor, buying interest | | Resistance | Price ceiling, selling pressure | | Moving Averages | Dynamic support/resistance | | Round Numbers | Psychological levels |

Volume Analysis

Volume Patterns

| Pattern | Interpretation | |---------|----------------| | High Volume + Price Up | Strong buying conviction | | High Volume + Price Down | Strong selling pressure | | Low Volume + Price Up | Weak rally, may reverse | | Low Volume + Price Down | Lack of selling interest |

Volume Indicators

| Indicator | Usage | |-----------|-------| | Volume Spike | Unusual activity, potential catalyst | | Volume Dry-up | Consolidation, waiting mode | | Volume Trend | Confirms price trend | | On-Balance Volume | Cumulative volume direction |

Time Period Analysis

Short-Term (1-30 Days)

| Focus | Use Case | |-------|----------| | Recent Performance | Current momentum | | Trading Signals | Entry/exit timing | | News Impact | Event analysis | | Volatility | Risk assessment |

Medium-Term (1-6 Months)

| Focus | Use Case | |-------|----------| | Trend Identification | Direction confirmation | | Seasonality | Cyclical patterns | | Earnings Impact | Quarterly effects | | Sector Rotation | Relative performance |

Long-Term (1+ Years)

| Focus | Use Case | |-------|----------| | Major Trends | Secular moves | | 52-Week Range | Valuation context | | Recovery/Decline | Major shifts | | Dividend Yield | Income analysis |

Comparative Analysis

Peer Comparison

| Metric | What to Compare | |--------|-----------------| | Return | Relative performance | | Volatility | Risk comparison | | Correlation | Movement similarity | | Volume | Liquidity comparison |

Benchmark Comparison

| Benchmark | Usage | |-----------|-------| | S&P 500 | Large cap reference | | Sector ETF | Industry context | | Nasdaq | Tech comparison | | Russell 2000 | Small cap reference |

Analysis Tips

1. **Consider context**: Market conditions affect individual stocks.

2. **Adjust for events**: Earnings, dividends, splits affect prices.

3. **Use volume confirmation**: Price moves need volume support.

4. **Multiple timeframes**: Longer and shorter perspectives.

5. **Compare to peers**: Relative performance matters.

6. **Watch