Advanced search ?

Object

Variability in Times of Disease. Application of ARMA-GARCH in Modelling and Predicting Volatility of S&P500 Index Return Rates in COVID-19
Download

Title: Variability in Times of Disease. Application of ARMA-GARCH in Modelling and Predicting Volatility of S&P500 Index Return Rates in COVID-19

Title in english:

Zmienność w czasach zarazy, czyli o zastosowaniu modeli ARMA-GARCH w modelowaniu i prognozowaniu zmienności stóp zwrotu z indeksu S&P500 w dobie pandemii COVID-19

Creator:

Wiśniewski, Damian

Description:

Econometrics = Ekonometria, 2025, Vol. 29, No. 4, s. 18-32

Abstrakt:

Aim: The article considers the time series case of the closing prices of the S&P500 index over the period from January 2020 to April 2021. The author selected the best ARMA(p,q)-GARCH(1,1) models with different forms of probability density functions. The errors of the forecasts generated both in terms of logarithmic returns and their variability were compared. Methodology: The study followed the Box-Jenkins procedure. Applying the information criterion the study considered the best among these models with normal, skewed Student’s t, generalised error and generalised hyperbolic distribution. Results: The author obtained the following representations: ARMA(2,0)-GARCH(1,1) and ARMA(0,2)-GARCH(1,1), with normal, skewed Student’s t and generalised error distribution. The assessment of forecast accuracy showed that in the case of conditional variance forecasts, the ARMA(2,0)GARCH(1,1) models with a normal distribution and a generalised error distribution were the best. The largest errors of conditional variance forecasts were generated by models with a skewed Student’s t-distribution. Implications and recommendations: It is worth extended the study to models based on the range of fluctuations (such as Range GARCH-RGARCH or Conditional Autoregressive Range Model-CARR). Originality/value: The author considered models with various probability density functions, showing that such diversity was important when looking for the best models in times of high volatility.

Publisher:

Publishing House of Wroclaw University of Economics and Business

Place of publication:

Wroclaw

Date:

2025

Resource Type:

artykuł

Resource Identifier:

doi:10.15611/eada.2025.4.02 ; oai:dbc.wroc.pl:142475

Language:

eng

Relation:

Econometrics = Ekonometria, 2025, Vol. 29, No. 4

Rights:

Pewne prawa zastrzeżone na rzecz Autorów i Wydawcy

Access Rights:

Dla wszystkich zgodnie z licencją

License:

CC BY-SA 4.0

Location:

Uniwersytet Ekonomiczny we Wrocławiu

Group publication title:

Ekonometria = Econometrics

Subject and keywords:

COVID-19 pandemic ARMA-GARCH time series S&P500 index stationarity COVID-19 szereg czasowy stacjonarność

Object collections:

Last modified:

Dec 17, 2025

In our library since:

Dec 17, 2025

Number of object content hits:

2

All available object's versions:

https://dlibra.kdm.wcss.pl/publication/181418

Show description in RDF format:

RDF

Show description in OAI-PMH format:

OAI-PMH

Edition name Date
Variability in Times of Disease. Application of ARMA-GARCH in Modelling and Predicting Volatility of S&P500 Index Return Rates in COVID-19 Dec 17, 2025

Objects Similar

Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu
Własności szeregów czasowych stóp zwrotu z inwestycji w metale nieżelazne

Król, Paulina

2024
artykuł
Debiuty Studenckie
Debiuty Studenckie
Analiza interwencji na przykładzie badania wpływu pandemii COVID-19 na dzietność za pomocą modeli SARIMA

Kozaczewska, Kornelia Stanimir, Agnieszka. Redakcja

2024
rozdział
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu
Model regresji Feldsteina-Horioki – wyniki badań dla Polski

Markowicz, Iwona

2015
artykuł
Konwergencja cykli w Unii Europejskiej a COVID-19

Augustyński, Iwo Pancer-Cybulska, Ewa. Redakcja Baran, Bernardeta. Redakcja Szostak, Ewa. Redakcja

2022
rozdział
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu
Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu
Global value chains (GVCS) in East Asia during the COVID-19 pandemic – the perspective of Japan

Bobowski, Sebastian Drelich-Skulska, Bogusława

2022
artykuł
Financial Sciences. Nauki o Finansach
Financial Sciences. Nauki o Finansach
The impact of the COVID-19 pandemic on the non-bank loan market in Poland

Waliszewski, Krzysztof

2020
artykuł
Financial Sciences. Nauki o Finansach
Financial Sciences. Nauki o Finansach
Analysis of the impact of the crisis caused by Covid-19 in the intercultural environment with reference to economic factors

Kadlec, Željka Žunić, Marija Lovrenović, Marijana

2021
artykuł
Has the COVID-19 Pandemic Changed the Way Travel Agencies Clients’ Make Decisions?

Jaremen, Daria E. Michalska-Dudek, Izabela Pellešová, Pavlina Drelich-Skulska, Bogusława. Redakcja Sobocińska, Magdalena. Redakcja Tomášková, Andrea. Redakcja

2024
rozdział
More
×

Citation

Citation style:

Contact details

Address

Wrocław University of Science and Technology (Coordinator)
Library of Wrocław University of Science and Technology
Wybrzeże Wyspiańskiego 27
50-370 Wrocław, Poland

Phone

(+48) 71-320-38-30
(+48) 71-320-47-50

E-Mail

bc@pwr.edu.pl

Visit us!

https://biblioteka.pwr.edu.pl/

This page uses 'cookies'. More information