Garman-Klass Volatility Calculator

Garman-Klass Volatility Calculator MCP Connector for Claude

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Calculate efficient Garman-Klass volatility using OHLC data.

3 tools Official Updated Oct 1, 2026 Official Vinkius Partner

This MCP server provides high-efficiency volatility estimation for quantitative finance. By utilizing the calculate_gk_volatility tool, agents can compute the Garman-Klass metric using Open, High, Low, and Close (OHLC) price arrays. This method is significantly more efficient than Parkinson volatility as it incorporates intraday price direction. Users can also use compare_volatility_methods to evaluate the efficiency of Garman-Klass against Parkinson and Close-to-Close benchmarks, or get_volatility_percentile to determine if current market turbulence is an outlier relative to historical distributions.

volatilityohlcquantitative-financegarman-klassrisk-management

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

calculate_gk_volatility

Computes the primary Garman-Klass volatility metric for a given set of price data

compare_volatility_methods

Provides a comparative analysis of different volatility estimators

get_volatility_percentile

Determines the relative extremity of the current Garman-Klass volatility

See how to talk to your AI agent using Garman-Klass Volatility Calculator.

Calculate the Garman-Klass volatility for these prices: Open [100, 102], High [105, 106], Low [98, 101], Close [103, 104].

The calculated Garman-Klass volatility is 0.0452.

Compare the volatility methods for the following data: Open [10, 11], High [12, 13], Low [9, 10], Close [11, 12].

The results are: Garman-Klass: 0.085, Parkinson: 0.072, Close-to-Close: 0.065.

Is a volatility of 0.25 extreme if the historical volatilities were [0.1, 0.15, 0.12, 0.18, 0.2]?

Yes, the volatility is in the 100th percentile and is considered extreme.

Garman-Klass is more efficient because it uses all four OHLC prices, whereas Parkinson only uses the High and Low prices.

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