MCP For Claude Marketplace
Parkinson Volatility Calculator

Parkinson Volatility Calculator MCP Connector for Claude

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Calculate precise Parkinson volatility using high-low price ranges.

3 tools Official Updated Oct 1, 2026 Official Vinkius Partner
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This MCP server provides a deterministic engine for calculating Parkinson volatility. By utilizing the high-low price range instead of just closing prices, it captures intraday price movement more effectively. Use calculate_parkinson_volatility for direct calculations, get_volatility_context to compare Parkinson volatility against close-to-close moves and percentile ranks, or compare_volatilities to evaluate the ratio of intraday to end-of-day volatility across multiple timeframes.

volatilityparkinsonfinancequantitativetrading

3 tools expose this connector's capabilities to your AI agent.

compare_volatilities

Answers how the current intraday volatility (Parkinson) compares to the end-of-day volatility (Close-to-Close) over multiple timeframes

calculate_parkinson_volatility

Calculates the annualized Parkinson volatility for a specific set of price data

get_volatility_context

Provides a comparative view of Parkinson volatility against standard close-to-close volatility and its percentile rank

See how to talk to your AI agent using Parkinson Volatility Calculator.

Calculate the Parkinson volatility for these high prices [105, 106, 104] and low prices [100, 101, 99] with a lookback of 3 and annualization of 252.

The annualized Parkinson volatility for the provided data is 0.245.

Compare the intraday and end-of-day volatility for these prices.

The Parkinson volatility is 0.15 and the close-to-close volatility is 0.12, resulting in a ratio of 1.25, indicating significant intraday movement.

What is the volatility percentile rank for the current market conditions?

The current Parkinson volatility is at the 85th percentile relative to its historical distribution.

Parkinson volatility is a measure of historical volatility that uses the high and low prices of an asset within a period, providing a more efficient estimate than standard close-to-close volatility.

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