Which probability distribution describes many phenomena such as returns on equity or assets?

The normal distribution is a fundamental probability distribution that is widely used in statistics, particularly for representing real-valued random variables whose distributions are not known. It is characterized by its symmetrical shape, where the mean, median, and mode of the distribution all coincide at the center.

Many phenomena, including financial returns such as returns on equity or assets, tend to cluster around a central mean, with occurrences of extreme values less frequent. This aligns well with the properties of the normal distribution. For instance, as it relates to finance, the normal distribution is often applied in the context of portfolio theory and asset pricing, making it a significant model for understanding and predicting potential returns.

This distribution captures the concept that while most returns will be close to the average, there are also instances of both high positive and high negative returns, albeit with decreasing probabilities as one moves further away from the mean. As a result, when assessing the risk and volatility associated with investments, the normal distribution effectively represents the variation in returns, thus making it pertinent for modeling financial risks.

In contrast, while other distributions like lognormal, triangular, and BetaPERT also have their uses in specific contexts within finance and statistics, they do not universally describe the kinds of phenomena mentioned as effectively as the normal