Spotting Option Mispricing with Moneyness Surfaces

Moneyness surfaces map an option's implied volatility relative to the underlying asset price. By focusing on how far in or out of the money an option is, traders can gain a clear view of how implied volatility (IV) shifts across different strike distances. This approach helps identify potential pricing inefficiencies between in-the-money (ITM) and out-of-the-money (OTM) contracts. If certain options display abnormal IV relative to similar moneyness levels, it might signal a mispricing that can be exploited.

Below, we'll explain how two Amberdata endpoints can help achieve these insights. The Moneyness Surfaces Floating endpoint captures the volatility smile of actual listed expirations, while the Moneyness Surfaces Constant endpoint shows IV for standardized tenors, such as 30 days or 90 days to expiration. Each endpoint highlights option pricing dynamics that might otherwise remain hidden. When used together, they paint a detailed picture of volatility conditions.

By comparing implied volatilities at different moneyness levels, traders can pinpoint potential pricing anomalies that signal opportunities or risks.

Analyzing Moneyness Surfaces with the Floating Endpoint

Moneyness Surfaces Floating presents implied volatility as a function of how far in or out of the money each option is, aligned with its actual listed expiration. This data is typically delivered in a structured form, listing moneyness levels and corresponding IV values for every relevant contract date. By calibrating to the forward price, the surface normalizes differences between spot and futures pricing, making comparisons across strikes more consistent.

Traders can use this dataset to observe how IV changes for ITM vs OTM options across multiple expiries. For example, if deep OTM puts carry much higher implied volatility than similarly distant OTM calls, it might indicate a stronger demand for downside protection. When these relative levels deviate from historical norms, traders can identify mispricings. Perhaps an OTM call is trading at an unusually low IV despite upcoming events that could spark a price rally. By referencing historical values, users can track whether an option's implied volatility at a specific moneyness is too high or too low compared to past behavior.

The floating endpoint is updated for BTC and ETH on Derbit in real time and hourly intervals. Because it is tied to actual expiration dates, users can directly compare the smiles of near-term vs long-term options without interpolation. If a certain strike for the next monthly expiry displays an unexpected IV spike, it might signal local order flow imbalances. In the absence of a valid rationale for that spike, this could be a tradeable anomaly.

Leveraging the Constant Moneyness Surface Endpoint

Unlike the floating endpoint, which uses actual expirations, the Moneyness Surfaces Constant endpoint fixes time to maturity at specific intervals. For instance, a user might examine 7-day,

30-day, and 90-day implied volatility curves, each tied to a constant horizon. This approach involves interpolating or extrapolating from existing contract data to produce a consistent set of moneyness buckets at each standard tenor.

By analyzing constant surfaces, traders can compare short-term vs medium-term IV on an equal footing. If the 30-day curve shows a significantly higher implied volatility at 5 percent OTM than the 7-day curve, it might suggest that the market expects bigger moves over the next month rather than in the immediate week. Contrasts like this can highlight term structure anomalies and pinpoint specific moneyness levels that may be under or overpriced. For example, if the 7-day OTM calls are relatively cheap while the 30-day calls are more expensive, there might be a potential calendar spread strategy.

Historical analysis is also easier with constant maturities. If you always look at the 30-day surface, you can assess how IV at a 10 percent OTM strike has evolved and identify trends. If today's value is far below its historical average, that option may be undervalued. Traders can also track whether the overall skew is flattening or steepening over time. The data is updated hourly and in real time, covering assets like BTC and ETH on Dexibit

Using These Endpoints to Identify Pricing Discrepancies

Combining data from both endpoints helps traders uncover opportunities more thoroughly. The floating endpoint displays actual listed expiries, letting you spot if any particular contract displays an odd implied volatility at a certain strike. The constant endpoint smooths out the timeline by applying fixed maturities, so you can detect broader shifts in term structure without worrying about expiring contracts.

One approach is to cross-check anomalies. If the floating surface shows a surprisingly low IV for a certain OTM call in next month's expiry, you can see if that discrepancy also appears in the constant 30-day curve. If both reveal an unexpectedly weak implied volatility, there is evidence that the option is genuinely underpriced. On the other hand, if the floating data shows a spike | specific to one contract date, it might be a localized phenomenon.

Another strategy is to examine whether short-term surfaces reflect an upcoming event risk that medium-term surfaces do not. If the 7-day IV is extremely high while the 30-day IV is relatively low, it might mean the market only anticipates near-term volatility (further indicating a shift in sentiment). Selling or buying these mismatched implied vols, depending on one's outlook, can be profitable. By feeding these endpoints into automated tools, users can set alerts for when certain strikes or maturities deviate too far from historic norms.

How to Use This

Moneyness surfaces are a powerful lens for uncovering option pricing inefficiencies. The Floating endpoint ties implied volatility to actual listed expiries, revealing granular details about each contract's IV behavior. The Constant endpoint uses standardized maturities, ensuring consistent comparisons across time. Used together, these tools help traders see whether implied volatilities at specific moneyness levels are rational or out of line with expectations.

Spotting an unusual skew in the floating data might prompt further checks in the constant curves to confirm whether the anomaly is broad-based or limited to one expiry. A clear mismatch can indicate an exploitable trade, while a widespread shift in implied volatility suggests a broader market re-pricing. Either way, understanding how ITM and OTM options are valued relative to each other provides an edge. Amberdata's comprehensive data, available in real time and historically, lets users integrate these insights into risk models and automated alerts.

Traders seeking deeper knowledge can integrate Amberdata's real-time data feeds with custom analytics. Refer to the Amberdata API documentation for further details.

By combining historical data, one can run backtests to measure how well certain implied volatility divergences predict future price swings. In volatile markets, short-term dislocations in OTM option pricing often emerge. Analyzing these dislocations through floating and constant endpoints clarifies whether they reflect genuine market shifts or transient liquidity-driven quirks. This holistic view can guide decisions on whether to build directional spreads, delta-hedged option strategies or maintain simpler positions.

Ultimately, well-informed traders gain a key edge by incorporating robust implied volatility analysis (e.g., looking at implied volatility surfaces) into their approach, minimizing the guesswork that can otherwise plague complex options markets. This data-driven approach also bolsters overall risk management and fosters more robust trading strategies.