stock-historical-index

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Retrieve full historical end-of-day price data for market indices using Octagon MCP. Use when analyzing index performance over time, tracking market trends, calculating returns, and understanding market context for individual stock analysis.

2installs

Sourceoctagonai/skills

Added on2026-05-10

NPX Install

npx skill4agent add octagonai/skills stock-historical-index

SKILL.md Content

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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:

json

{
  "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:

Date	Open	High	Low	Close	Volume	Change	Change %	VWAP
2025-04-30	5,499.44	5,581.84	5,433.24	5,569.07	5.45B	+69.63	+1.27%	5,520.90
2025-04-29	5,508.87	5,571.95	5,505.70	5,560.82	4.75B	+51.95	+0.94%	5,536.84
...	...	...	...	...	...	...	...	...

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

Symbol	Index	Description
^GSPC	S&P 500	500 large-cap US stocks
^DJI	Dow Jones	30 blue-chip stocks
^IXIC	NASDAQ Composite	All NASDAQ stocks
^NDX	NASDAQ 100	100 largest NASDAQ
^RUT	Russell 2000	2000 small-cap stocks

Sector Indices

Symbol	Index	Description
^XLK	Technology	Tech sector
^XLF	Financials	Financial sector
^XLV	Healthcare	Healthcare sector
^XLE	Energy	Energy sector
^XLI	Industrials	Industrial sector

Volatility Indices

Symbol	Index	Description
^VIX	VIX	Market volatility
^VXN	VXN	NASDAQ volatility

Understanding Index Data

Price Components

Field	Description
Open	First trade price of day
High	Highest price of day
Low	Lowest price of day
Close	Last trade price of day
Volume	Total shares traded
Change	Point change from prior close
Change %	Percentage change
VWAP	Volume-weighted average price

Daily Range Analysis

Metric	Calculation
Daily Range	High - Low
Range %	(High - Low) / Open
Position in Range	(Close - Low) / (High - Low)

Return Calculations

Period Returns

Period	Formula
Daily	(Close - Prior Close) / Prior Close
Weekly	(Friday Close - Monday Open) / Monday Open
Monthly	(Month End - Month Start) / Month Start
YTD	(Current - Year Start) / Year Start

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

Pattern	Interpretation
High volume + up	Strong buying
High volume + down	Strong selling
Low volume + up	Weak rally
Low volume + down	Lack of sellers

Volume Metrics

Metric	Purpose
Average daily volume	Baseline
Volume spike	Unusual activity
Volume trend	Participation changes

Example

From the data:

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

Trend Analysis

Trend Identification

Pattern	Characteristics
Uptrend	Higher highs, higher lows
Downtrend	Lower highs, lower lows
Consolidation	Range-bound
Reversal	Trend change

Moving Averages

MA	Use
50-day	Short-term trend
200-day	Long-term trend
Golden Cross	50 > 200 (bullish)
Death Cross	50 < 200 (bearish)

Volatility Analysis

Measuring Volatility

Metric	Calculation
Daily Range %	(High - Low) / Close
Daily Change	Absolute daily change
Std Deviation	Dispersion of returns

Volatility Context

Daily Change %	Market Condition
<0.5%	Low volatility
0.5-1%	Normal
1-2%	Elevated
>2%	High volatility
>4%	Extreme

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

Criteria	Threshold
Big up day	>2% gain
Big down day	>2% loss
Volume spike	>2x average
Range expansion	>2x normal range

Event Analysis

From Data	Event
+9.90% on Apr 9	Major rally
-4.12% on Apr 4	Significant selloff
9.49B volume	Highest participation

Benchmarking Use

Stock vs. Index

Comparison	Formula
Alpha	Stock Return - Index Return
Beta	Stock Vol / Index Vol × Correlation
Relative Strength	Stock / 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

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

Integration with Other Skills

Skill	Combined Use
stock-performance	Stock vs. index comparison
sector-performance-snapshot	Sector vs. index
stock-quote	Current vs. historical
historical-market-cap	Market cap vs. index

stock-historical-index

NPX Install

Tags

SKILL.md Content

Stock Historical Index

Prerequisites

Workflow

1. Identify Parameters

2. Execute Query via Octagon MCP

3. Expected Output

4. Interpret Results

Example Queries

Common Index Symbols

US Major Indices

Sector Indices

Volatility Indices

Understanding Index Data

Price Components

Daily Range Analysis

Return Calculations

Period Returns

Example

Cumulative Returns

Volume Analysis

Volume Patterns

Volume Metrics

Example

Trend Analysis

Trend Identification

Moving Averages

Volatility Analysis

Measuring Volatility

Volatility Context

Example

Key Market Events

Identifying Significant Days

Event Analysis

Benchmarking Use

Stock vs. Index

Example Use

Common Use Cases

Market Context

Return Comparison

Volatility Assessment

Trend Analysis

Volume Analysis

Analysis Tips

Integration with Other Skills