A normal or Gaussian distribution is a probability distribution with a bell shape.
If we take data such as prices, or asset returns, plot them on a graph and connect them with a line, the shape of the line would represent the data’s distribution. If this graph looks like the one below, where all values are plotted symmetrically, with most of the results revolving around the mean, it is said to be a normal distribution.
The highest point in the curve (the top of the bell) depicts the most probable outcome (the mean). The other possible outcomes are evenly distributed around the mean.
Normal distribution is often found in stock market analysis because it is assumed in conventional investment theory that returns follow a normal distribution. Normal distributions tend to bear certain similarities; thus, if particular data are normally distributed, they are likely to follow particular probabilistic patterns in the future.