Weekly recap of the crypto derivatives markets by BlockScholes.

Key Insights:

The summer volatility lull continues to weigh on derivatives markets as 7-day BTC at-the-money implied volatility trades around its lowest levels since 2023, in line with a drop in realised volatility which is also at its lowest since September 2025.

Despite a number of macro developments over the past week, BTC continues to mostly trade sideways around $60K. President Trump expressed an apparent lack of willingness to extend the June memorandum of understanding signed between the US and Iran which expired Monday, while a softer-than-expected CPI and nonfarm payrolls print helped markets significantly reduce their expectations of a September rate hike. Nonetheless, Monday’s bounce to $64K coincided with a recovery in put-call skew at the front-end – though not enough to turn options markets bullish.

Block Scholes BTC Risk Appetite Index

Block Scholes ETH Risk Appetite Index

1-Month Tenor ATM Implied Volatility

BTC Options

BTC SVI ATM IMPLIED VOLATILITY – 7-day ATM IV fell to 23% last week, its lowest level since September 2023.

ETH Options

ETH SVI ATM IMPLIED VOLATILITY – The summer volatility lull is equally apparent in ETH, where short-dated vol fell towards 30% in mid-August.

BTC and ETH Skew

BTC 25-Delta Risk Reversal – A modest rally in Monday’s trading session back above $64K has coincided with a move higher in short-tenor put-call skew. However, as we’ve seen for most of the year, skew is yet to turn positive meaningfully. Despite the move in skew, sentiment recently has been dragged down by a run of outflows from spot ETFs and nearly two-months of no buying from Strategy, the largest BTC digital asset treasury.

ETH 25-Delta Risk Reversal – ETH put-call skew trades negatively across all tenors, though like BTC, has recovered at the front end. ETH is currently up around 2% on the month.

Market Composite Volatility Surface

BTC SVI – 8:00 UTC Snapshot.

ETH SVI – 8:00 UTC Snapshot.

Cross-Exchange Volatility Smiles

BTC SVI, 30D TENOR – 8:00 UTC Snapshot.

ETH SVI, 30D TENOR – 8:00 UTC Snapshot.

Constant Maturity Volatility Smiles

BTC SVI, 30D TENOR – 8:00 UTC Snapshot.

ETH SVI, 30D TENOR – 8:00 UTC Snapshot.

Data Reference

Block Scholes Risk Appetite (BTC/ETH)

Block Scholes’ Risk Appetite index uses a composite spot index price; POST /api/v1/price/index

1-month ATM implied volatility (BTC/ETH)

At-the-money IV at a constant 1-month tenor; forward- looking vol expectations; POST /api/v1/iv/moneyness

Volatility term structure & SVI ATM IV by tenor (BTC/ETH)

SVI-fitted ATM IV across constant tenors (7d / 14d / 30d / 90d / 180d); POST /api/v1/modelparams

25-delta risk reversal / skew (BTC/ETH)

Spread between 25Δ call and 25Δ put IV; a measure of upside vs downside option demand; POST /api/v1/iv/risk-reversal

Market composite volatility surface (BTC/ETH)

BlockScholes composite SVI surface across forward moneyness and tenor, aggregating market-wide options pricing into one clean fitted surface; POST /api/v1/iv/moneyness + POST /api/v1/modelparams

Cross-exchange volatility smiles (BTC/ETH)

Venue-level (Deribit, Bybit) and composite smiles at a fixed tenor, for comparing exchange pricing against the market composite; POST /api/v1/iv/moneyness

Constant-maturity volatility smiles (BTC/ETH)

Like-for-like smile at a fixed tenor across strikes, showing how the smile shifted between dates; POST /api/v1/iv/strike

Disclaimer

This article reflects the personal views of its author, not Deribit or its affiliates. Deribit has neither reviewed nor endorsed its content.

Deribit does not offer investment advice or endorsements. The information herein is informational and shouldn’t be seen as financial advice. Always do your own research and consult professionals before investing.

Financial investments carry risks, including capital loss. Neither Deribit nor the article’s author assumes liability for decisions based on this content.

AUTHOR(S)

Block Scholes

Trading with a competitive edge. Providing robust quantitative modelling and pricing engines across crypto derivatives and risk metrics.

THANKS TO

Andrew Melville and Thahbib Rahman, Block Scholes

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