Student't mixture models for stock indices. A comparative study

Autor: Massing, Till, Ramos, Arturo
Rok vydání: 2023
Předmět:
Zdroj: Physica A: Statistical Mechanics and its Applications, 580, 126143 (2021)
Druh dokumentu: Working Paper
DOI: 10.1016/j.physa.2021.126143
Popis: We perform a comparative study for multiple equity indices of different countries using different models to determine the best fit using the Kolmogorov-Smirnov statistic, the Anderson-Darling statistic, the Akaike information criterion and the Bayesian information criteria as goodness-of-fit measures. We fit models both to daily and to hourly log-returns. The main result is the excellent performance of a mixture of three Student's $t$ distributions with the numbers of degrees of freedom fixed a priori (3St). In addition, we find that the different components of the 3St mixture with small/moderate/high degree of freedom parameter describe the extreme/moderate/small log-returns of the studied equity indices.
Databáze: arXiv