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Multivariate asset‐pricing model based on subordinated stable processes
Author(s) -
Panov Vladimir,
Samarin Evgenii
Publication year - 2019
Publication title -
applied stochastic models in business and industry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.413
H-Index - 40
eISSN - 1526-4025
pISSN - 1524-1904
DOI - 10.1002/asmb.2446
Subject(s) - subordination (linguistics) , econometrics , multivariate statistics , context (archaeology) , geometric brownian motion , capital asset pricing model , stock (firearms) , stochastic process , asset (computer security) , economics , brownian motion , mathematical economics , mathematics , computer science , statistics , diffusion process , economy , mechanical engineering , paleontology , philosophy , linguistics , computer security , engineering , biology , service (business)
In this paper, we consider a multidimensional time‐changed stochastic process in the context of asset‐pricing modeling. The proposed model is constructed from stable processes, and its construction is based on two popular concepts: multivariate subordination and Lévy copulas. From a theoretical point of view, our main result is Theorem 1, which yields a simulation method from the considered class of processes. Our empirical study shows that the model represents the correlation between asset returns quite well. Moreover, we provide some evidence that this model is more appropriate for describing stock prices than classical time‐changed Brownian motion, at least if the cumulative amount of transactions is used for a stochastic time change.