Object

Title: Inverted gamma vs. log-normal innovations in MSFSBEKK models in the forecasting of selected Polish exchange rates

Title in english:

Odwrócone gamma a logarytmiczno-normalne innowacje w modelach MSF-SBEKK w prognozowaniu wybranych polskich kursów walutowych

Creator:

Pajor, Anna

Description:

Śląski Przegląd Statystyczny = Silesian Statistical Review, 2020, Nr 18 (24), s. 197-218

Abstrakt:

The aim of the paper is to compare the forecasting potentials of two classes of Multiplicative Stochastic Factor – scalar BEKK (MSF-SBEKK) models which differ in the type of latent process. In the first class, the innovations of a first order autoregressive structure for the natural logarithm of latent variables are log-normal, whereas in the second class the innovations are inverted gamma distributed. The comparison of the models’ forecasting abilities by means of the predictive Bayes factor as well as the log predictive score and energy score were performed based on the Polish exchange rates. The author considered one- to ten-step-ahead predictions during the period beginning from 3 September 2019 and ending on 2 September 2020, which covers the time of the crisis caused by COVID-19. The author concluded that for most of the forecast horizons, the considered log-normal innovations outperformed the inverted gamma ones

Publisher:

Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu

Place of publication:

Wrocław

Date:

2020

Resource Type:

artykuł

Resource Identifier:

doi:10.15611/sps.2020.18.11 ; oai:dbc.wroc.pl:109569

Language:

eng

Relation:

Śląski Przegląd Statystyczny = Silesian Statistical Review

Access Rights:

Dla wszystkich zgodnie z licencją

License:

CC BY-SA 4.0

Location:

Uniwersytet Ekonomiczny we Wrocławiu

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