Gaussian Model Limitations

The Gaussian model, or normal distribution, assumes that most data points cluster around the mean with rare, predictable outliers. Its primary limitation in finance is the inability to account for the non-linear, chaotic nature of market dynamics during crises.

In the crypto domain, where markets operate 24/7 and are subject to rapid liquidity shifts, the Gaussian assumption frequently leads to underpriced risk. It fails to capture the interconnectedness of protocols, where one failure can trigger a systemic contagion.

Consequently, models like Black-Scholes often require significant adjustments or alternative frameworks, such as jump-diffusion models, to remain useful. Relying solely on Gaussian math can create a false sense of security for derivative traders.