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What Are the Key Limitations of the Original Black-Scholes Model in a Volatile Market like Crypto?

The original Black-Scholes model has several key limitations that are exacerbated in the volatile crypto market. It assumes volatility is constant, asset prices follow a log-normal distribution, and trading is continuous, none of which perfectly hold true for crypto.

Crypto markets exhibit high, non-constant volatility, price jumps, and "fat tails" (more extreme price movements than log-normal predicts). These violations mean the model can systematically misprice options, particularly those far out-of-the-money, leading to the "volatility smile" phenomenon.

What Are the Main Limitations of the Original Black-Scholes Model in the Crypto Context?
How Do ‘Fat Tails’ in Asset Price Distributions Affect Option Pricing?
What Are the Main Limitations of the ‘Black-Scholes’ Model for Pricing Crypto Options?
How Does the ‘Black-Scholes’ Model Adapt to the Unique Characteristics of Crypto Options?