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Definition

Moneyness Surfaces provide a structured view of implied volatility relative to an option’s moneyness, rather than its absolute strike price. This approach normalizes volatility analysis, making it easier to compare different expirations and market conditions. Amberdata offers two types of moneyness surface endpoints:
  • Constant Moneyness Surface: Displays implied volatility across fixed moneyness levels for constant days-to-expiration horizons, allowing for consistent historical analysis.
  • Floating Moneyness Surface: Displays implied volatility across fixed moneyness levels for active expirations.
These surfaces help traders and analysts better understand volatility skews, risk exposure, and market dynamics in a standardized format.

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Details

Moneyness measures the relative position of an option’s strike price compared to its underlying asset price. Here, lognormal moneyness is computed using the corresponding futures price and a reference point, providing a consistent framework across expirations. The dataset uses SVI calibration to ensure smooth and arbitrage-free volatility surfaces, which can be applied to risk modeling, option pricing, and quantitative research.

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API Endpoints

/Moneyness Surfaces Floating /Moneyness Surfaces Constant

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Availability

ExchangeStart Date (YYYY-MM-DD)Granularity
Deribit (BTC, ETH)2019-04-01Hourly

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Frequently Asked Questions

How is lognormal moneyness calculated in this dataset?
  • Lognormal moneyness is determined using the natural logarithm of the moneyness price divided by the futures price at a given reference point. This standardization helps normalize volatility structures across different expirations and market conditions.
Why is this dataset only available for BTC and ETH on Deribit?
  • Currently, Deribit is the primary exchange offering deep liquidity and a robust options market for BTC and ETH. The SVI calibration process relies on high-quality data, which is best suited to markets with significant trading activity and available derivatives.