Normal Return Model

The Normal Return Model is a quantitative framework used in finance to estimate the expected performance of an asset based on the assumption that its returns follow a normal distribution, often represented by a bell curve. In the context of derivatives and options trading, it serves as a baseline for measuring abnormal returns, which are the deviations from what would be expected under normal market conditions.

By using statistical parameters like mean and standard deviation, traders can assess whether price movements are driven by systematic market factors or idiosyncratic events. This model is foundational for event studies, where analysts evaluate the impact of specific corporate actions or protocol upgrades on asset prices.

It assumes that market participants act rationally and that information is incorporated efficiently into prices. However, in cryptocurrency markets, returns often exhibit fat tails or skewness, meaning the normal distribution may underestimate the probability of extreme events.

Consequently, advanced practitioners often adjust these models to account for volatility clustering and non-normal distribution characteristics. It provides the necessary structure to isolate alpha from beta in complex trading strategies.