Mixed-Stable Models: An Application to High-Frequency Financial Data.
Entropy (Basel)
; 23(6)2021 Jun 11.
Article
en En
| MEDLINE
| ID: mdl-34208204
ABSTRACT
The paper extends the study of applying the mixed-stable models to the analysis of large sets of high-frequency financial data. The empirical data under review are the German DAX stock index yearly log-returns series. Mixed-stable models for 29 DAX companies are constructed employing efficient parallel algorithms for the processing of long-term data series. The adequacy of the modeling is verified with the empirical characteristic function goodness-of-fit test. We propose the smart-Δ method for the calculation of the α-stable probability density function. We study the impact of the accuracy of the computation of the probability density function and the accuracy of ML-optimization on the results of the modeling and processing time. The obtained mixed-stable parameter estimates can be used for the construction of the optimal asset portfolio.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Tipo de estudio:
Health_economic_evaluation
/
Prognostic_studies
Idioma:
En
Revista:
Entropy (Basel)
Año:
2021
Tipo del documento:
Article
País de afiliación:
Lituania