How Does the “Cost of Carry” Affect the Theoretical Price of a Futures Contract?
The cost of carry is the net cost of holding the underlying asset until the futures expiration date. It includes financing costs (interest paid) and storage costs (e.g. insurance, secure custody), minus any income generated (e.g. dividends, staking rewards).
The theoretical futures price equals the spot price plus the cost of carry. A positive cost of carry leads to contango, where the futures price is higher than the spot price.
Glossar
Positive Cost of Carry
Favorable Carry Environment ⎊ A market condition where the cost associated with holding a leveraged position is negative, meaning the trader receives a net payment for maintaining the position over time, often seen when funding rates are strongly negative.
Theoretical Futures Price
Valuation ⎊ A theoretical futures price in cryptocurrency derivatives represents an estimated equilibrium price derived from cost of carry models, incorporating factors like spot price, time to expiration, risk-free interest rates, and storage costs ⎊ though storage is often negligible for digital assets.
Theoretical Price
Pricing ⎊ Theoretical Price is the calculated fair market value of a derivative instrument, such as a futures contract or an option, derived from a no-arbitrage principle using a foundational financial model.
Bitcoin Futures
Settlement ⎊ These standardized, exchange-traded contracts obligate the holder to buy or sell a specific quantity of Bitcoin at a future date for a predetermined price, forming a critical component of regulated crypto derivatives markets.
Financing Costs
Assessment ⎊ The cost associated with maintaining leveraged or collateralized positions over time, encompassing interest paid on borrowed capital, funding rates for perpetual swaps, and opportunity costs of locked collateral.
Interest Rate Environment
Calibration ⎊ The interest rate environment, within cryptocurrency derivatives, functions as a critical calibration parameter for pricing models, notably those employing stochastic volatility frameworks like Heston.