Rogers-Satchell Volatility Calculator

Rogers-Satchell Volatility Calculator MCP Connector for Claude

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Deterministic, drift-independent volatility estimation using OHLC data.

3 tools Official Updated Oct 1, 2026 Official Vinkius Partner

This MCP server provides precise volatility estimation using the Rogers-Satchell model. Unlike standard estimators, this method is drift-independent, meaning it remains accurate even when asset prices exhibit strong trends. It utilizes the relationship between high, low, open, and close prices to provide a robust measure of historical volatility. Users can use calculate_rs_volatility for direct estimation, calculate_volatility_comparison to compare results against Parkinson and Garman-Klass models, or get_volatility_percentile to determine how current volatility ranks against historical data.

volatilityfinancequantitativeohlcstatistics

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

calculate_volatility_comparison

Compares Rogers-Satchell volatility against Parkinson and Garman-Klass estimators

calculate_rs_volatility

Calculates the deterministic Rogers-Satchell volatility for a specific series of price data

get_volatility_percentile

Determines the percentile rank of the most recent volatility value compared to a historical window

See how to talk to your AI agent using Rogers-Satchell Volatility Calculator.

Calculate the Rogers-Satchell volatility for these prices: [{'open': 100, 'high': 105, 'low': 95, 'close': 102}, {'open': 102, 'high': 108, 'low': 101, 'close': 107}]

0.1542

Compare volatility models for this data: [{'open': 50, 'high': 55, 'low': 48, 'close': 52}, {'open': 52, 'high': 54, 'low': 50, 'close': 51}]

{ "rogersSatchell": 0.124, "parkinson": 0.115, "garmanKlass": 0.128, "lookbackUsed": 2 }

What is the percentile rank of a volatility of 0.25 given the historical series [0.1, 0.15, 0.2, 0.12]?

100

The Rogers-Satchell model is drift-independent, which means it does not mistake price trends for volatility, providing a more accurate measure during trending markets.

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