Naslov
Estimating the Number of Latent Factors in High-Dimensional Financial Time Series

Autori
Keranović, Vanessa ; Begušić, Stjepan ; Kostanjčar, Zvonko

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), ostalo

Izvornik
2020 International Conference on Software, Telecommunications and Computer Networks (SoftCOM) / - : Institute of Electrical and Electronics Engineers (IEEE), 2020

ISBN
978-953-290-099-6

Skup
International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2020)

Mjesto i datum
Hvar, Hrvatska, 17.09.2020. - 19.09.2020

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
latent factor models ; high-dimensionality ; heavy tails

Sažetak
Various methods for modelling financial risk rely on factor models which assume that a smaller number of latent factors are responsible for a significant portion of the observed price dynamics. A critical step for accurate estimation of these factors is obtaining the true number of factors, which is additionally problematic in high- dimensional settings and in presence of heavy tailed data - both of which are common circumstances in financial time series. In this paper we propose a method for estimating the number of latent factors that tackles these issues. To find the number of factors, the method relies on properties of optimal portfolios estimated from the covariance matrices, given by the estimated factor structures. We also introduce a simulation environment for evaluating the selection of the number of factors on high-dimensional data with heavy tailed distributions, and test the performance of the proposed method against some well known estimators such as the Marčenko-Pastur law and parallel analysis. The results suggest that our method works very well and delivers more accurate and remarkably stable results.

Izvorni jezik
Engleski

Znanstvena područja
Brodogradnja

POVEZANOST RADA