Estimation latent factors from high-dimensional financial time series based on unsupervised learning
Unsupervised learning methods have been increasingly used for detecting latent factors in high-dimensional time series, with many applications, especially in financial risk modelling. Most latent factor models assume that the factors are pervasive and affect all of the time series. However, some fac...
| Permalink: | http://skupni.nsk.hr/Record/fer.KOHA-OAI-FER:51930/Similar |
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| Glavni autor: | Begušić, Stjepan (-) |
| Ostali autori: | Kostanjčar, Zvonko (Thesis advisor) |
| Vrsta građe: | Knjiga |
| Jezik: | eng |
| Impresum: |
Zagreb :
S. Begušić; Fakultet elektrotehnike i računarstva,
2020.
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APA stil citiranja
Begušić, S., & Kostanjčar, Z. (2020). Estimation latent factors from high-dimensional financial time series based on unsupervised learning: Estimation latent factors from high-dimensional financial time series based on unsupervised learning : doctoral thesis. Zagreb: S. Begušić; Fakultet elektrotehnike i računarstva.
Chicago stil citiranjaBegušić, Stjepan, and Zvonko Kostanjčar. Estimation latent factors from high-dimensional financial time series based on unsupervised learning: Estimation latent factors from high-dimensional financial time series based on unsupervised learning : doctoral thesis. Zagreb: S. Begušić; Fakultet elektrotehnike i računarstva, 2020.
MLA stil citiranjaBegušić, Stjepan, and Zvonko Kostanjčar. Estimation latent factors from high-dimensional financial time series based on unsupervised learning: Estimation latent factors from high-dimensional financial time series based on unsupervised learning : doctoral thesis. Zagreb: S. Begušić; Fakultet elektrotehnike i računarstva, 2020.