Empirical evidence shows stock returns are often heavy-tailed rather than
normally distributed. The κ-generalised distribution, originated in the
context of statistical physics by Kaniadakis, is characterised by the
κ-exponential function that is asymptotically exponential for small
values and asymptotically power law for large values. This proves to be a
useful property and makes it a good candidate distribution for many types of
quantities. In this paper we focus on fitting historic daily stock returns for
the FTSE 100 and the top 100 Nasdaq stocks. Using a Monte-Carlo goodness of fit
test there is evidence that the κ-generalised distribution is a good fit
for a significant proportion of the 200 stock returns analysed