The $κ$-generalised Distribution for Stock Returns

Fuente: arXiv
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Main Author: Forbes, Samuel
Format: Preprint
Published: 2024
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author Forbes, Samuel
author_facet Forbes, Samuel
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2405_09929
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle The $κ$-generalised Distribution for Stock Returns
Forbes, Samuel
Statistical Finance
Applications
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.
title The $κ$-generalised Distribution for Stock Returns
topic Statistical Finance
Applications
url https://arxiv.org/abs/2405.09929