Returns, especially of stock indices, have been extensively studied. In the past, it was assumed that the returns are normally distributed. However, it is now clear that the returns distribution has fat tails (fatter than normal distributions). More information is available at https://en.wikipedia.org/wiki/Fat-tailed_distribution (retrieved October 2015). It is easy enough to check whether data fits the normal distribution. All we need is the mean and standard deviation of the sample.
There are a number of topics that we will explore in this recipe:
The skewness and kurtosis of stock returns are interesting to study. Skewness is especially important in the context of stock option models. Analysts usually limit themselves to the mean and standard deviation, which are assumed to correspond to reward and risk, respectively.
If we are interested in the existence of a trend, then we should take a look at an autocorrelation plot. This is a plot of autocorrelation—that...