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What Are the Main Limitations of the ‘Black-Scholes’ Model for Pricing Crypto Options?

The Black-Scholes model assumes constant volatility, continuous trading, and a normal distribution of asset returns, which are not true for volatile, 24/7 crypto markets. Crypto returns exhibit 'fat tails' (more extreme events) and 'jump risk.' The model also cannot easily account for the 'volatility skew' seen in crypto options, leading to mispricing, especially for out-of-the-money options.

What Is a “Black-Scholes” Model and Is It Applicable to Valuing Altcoin Derivatives during a Flight to Quality?
What Are the Limitations of Using the Black-Scholes Model to Find Implied Volatility?
How Does a Large, Sudden Price Jump (Jump Risk) Affect a Gamma-Neutral Portfolio?
How Does the Assumption of a Lognormal Distribution of Stock Prices Affect the Model’s Accuracy?