High-Frequency Volatility Signature

Volatility Across Timeframes — Signal clarity, scaling laws, and intraday dynamics.

Understand How Volatility Scales with Time

Explore how realized volatility evolves across time intervals—from 1-minute to yearly. Signature plots highlight whether markets exhibit mean-reversion, randomness, or trend persistence.

Separate Market Noise from True Price Movement

Use the two-component model to estimate signal-to-noise ratios at intraday frequencies. Identify which timeframes reflect real information—and which are dominated by microstructure distortion.

Volatility Patterns Throughout the Day

View average volatility profiles by time-of-day and weekday. Detect recurring spikes and calm periods to improve execution timing, position sizing, and risk allocation.

Key Features

Volatility Signature Plot: Visualize how volatility scales across 1-minute to 1-year intervals.
Two-Component Noise Model: Decompose intraday variance into true price movement vs. microstructure noise.
Signal-to-Noise Ratio Chart: Quantify the reliability of high-frequency signals by interval.
Intraday Volatility Patterns: Track U-shape volatility trends using rolling windows across the trading day.
Realized vs. Implied Volatility: Compare actual volatility with VIX to evaluate market sentiment and risk premiums.
Weekday Volatility Analysis: Analyze how volatility varies by day to optimize timing and execution.

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