Title:

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

Group publication title:

Ekonometria = Econometrics

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

Subject and Keywords:

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

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

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