stock-historical-index（股票历史指数）

Stock Historical Index

Retrieve full historical end-of-day price data for market indices 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 Parameters

Determine your query parameters:

• Index Symbol: ^GSPC (S&P 500), ^DJI (Dow), ^IXIC (NASDAQ), etc.
• Start Date: Beginning of date range
• End Date: End of date range

2. Execute Query via Octagon MCP

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

Retrieve full historical end-of-day price data for the <INDEX> index from <START_DATE> to <END_DATE>.

MCP Call Format:

{
  "server": "octagon-mcp",
  "toolName": "octagon-agent",
  "arguments": {
    "prompt": "Retrieve full historical end-of-day price data for the ^GSPC index from 2025-01-01 to 2025-04-30."
  }
}

3. Expected Output

The agent returns comprehensive daily index data:

Key Statistics:

• Highest single-day volume: 9.49B on 2025-04-09
• Largest daily gain: +9.90% on 2025-04-09
• Largest daily loss: -4.12% on 2025-04-04
• Trading days covered: 79

Data Sources: octagon-stock-data-agent

4. Interpret Results

See references/interpreting-results.md for guidance on:

• Analyzing index price trends
• Calculating period returns
• Understanding volume patterns
• Identifying significant market moves

Example Queries

S&P 500 History:

Retrieve full historical end-of-day price data for the ^GSPC index from 2025-01-01 to 2025-04-30.

NASDAQ Composite:

Get historical data for ^IXIC from 2024-01-01 to 2024-12-31.

Dow Jones:

Show ^DJI historical prices for Q1 2025.

Russell 2000:

Retrieve historical data for ^RUT from 2024-06-01 to 2025-06-01.

Multiple Indices:

Compare ^GSPC and ^IXIC performance from 2025-01-01 to 2025-03-31.

Common Index Symbols

US Major Indices

Sector Indices

Volatility Indices

Understanding Index Data

Price Components

Daily Range Analysis

Return Calculations

Period Returns

Example

From the data:

• Start (Jan 2): 5,868.56
• End (Apr 30): 5,569.07
• Return: (5,569.07 - 5,868.56) / 5,868.56 = -5.10%

Cumulative Returns

Cumulative = (1 + r1) × (1 + r2) × ... × (1 + rn) - 1

Volume Analysis

Volume Patterns

Volume Metrics

Example

From the data:

• Highest volume: 9.49B on 2025-04-09
• This coincided with +9.90% gain (major rally)

Trend Analysis

Trend Identification

Moving Averages

Volatility Analysis

Measuring Volatility

Volatility Context

Example

From the data:

• Largest gain: +9.90%
• Largest loss: -4.12%
• Range: 14.02%
• Interpretation: Period of elevated volatility

Key Market Events

Identifying Significant Days

Event Analysis

Benchmarking Use

Stock vs. Index

Example Use

• Your stock returned +15%
• S&P 500 returned -5.10%
• Alpha: +20.10% outperformance

Common Use Cases

Market Context

What was the overall market doing when my stock fell?

Return Comparison

How did the S&P 500 perform in Q1 2025?

Volatility Assessment

What were the biggest up and down days for the market in 2024?

Trend Analysis

Is the market in an uptrend or downtrend?

Volume Analysis

What were the highest volume days for the S&P 500?

Analysis Tips

1. Use for context: Index performance explains stock moves.
2. Calculate alpha: Your returns vs. market.
3. Watch volume: High volume days are significant.
4. Track extremes: Big up/down days signal sentiment.
5. Compare indices: Different indices, different signals.
6. Consider VIX: Volatility index for fear gauge.

Integration with Other Skills