EMPIRICAL ANALYSIS OF THE VOLATILITY EFFECT OF THE COVID-19 PANDEMIC PROCESS ON NATURAL GAS FUTURE TRANSACTIONS IN TURKEY
Abstract
The aim of this study is to investigate the volatility movements in natural gas returns, which is one of the financial investment instruments in futures markets, before and after the Covid-19 pandemic, using GARCH family models. For this purpose, daily data from 30.08.2017 to 10.03.2020 before the Covid-19 Pandemic, and daily data from 11.03.2020 to 21.09.2021 after the Covid-19 Pandemic were used. The return on natural gas futures before the Covid-19 Pandemic was expressed as RLNPO and the return on natural gas futures after the Covid-19 Pandemic was expressed as RLNPS. For RLNPO, TGARCH was determined as the most suitable volatility model according to Schwarz Information Criteria, and EGARCH was determined as the most suitable volatility model for RLNPS. As a result of these analyzes, it has been seen that natural gas futures returns can be explained by asymmetric volatility models before and after the Covid-19 Pandemic, but there is no leverage effect as a result of asymmetric volatility, and positive shock asymmetries have a greater effect on volatility. The asymmetric effect tends to decrease in the post-Covid-19 Pandemic period.
Keywords
Covid-19 Pandemic , GARCH Family Models , Natural Gas Futures , Volatility
Kaynakça
- Arslan, T., &Şahin, D. (2022). Covid-19’un Gazete Haberlerine Yansıması: Bir Gazete Örneği. Sosyal Araştırmalar ve Yönetim Dergisi, (1), 1-16.
- Bollerslev, T.(1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31(3), 307-327.
- Çetin, A. C. (2020). Koronavirüs (Covid-19) Salgınının Türkiye'de Genel Ekonomik Faaliyetlere ve Hisse Senedi Borsa Endeksine Etkisi. Mehmet Akif Ersoy Üniversitesi Uygulamalı Bilimler Dergisi, 4(2), 341-362.
- Dickey, D. A., & Fuller, W. A. (1981). Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root. Econometrica (49), 1057-1072.
- Dickey, D. A., & Fuller, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series with a Unit Root. Journal of American Statistical Association, 74, 427-431.
- Duran, M. S., & Acar M. (2020). Bir Virüsün Dünyaya Ettikleri: Covid-19 Pandemisinin Makroekonomik Etkileri. International Journal of Social and Economic Sciences, 10(1), 54-67.
- Elçiçek, Y. K., & Kayalıdere, K. (2021). VİOP 30 Vadeli İşlem Sözleşmesi ile Çeşitli Makroekonomik Faktörler Arasındaki İlişkinin İncelenmesi. Muhasebe ve Finansman Dergisi, (89), 203-220.
- Emeç, H., & Özdemir, M. O. (2014). Türkiye’de Döviz Kuru Oynaklığının Otoregresif Koşullu Değişen Varyans Modelleri ile İncelenmesi. Finans Politik ve Ekonomik Yorumlar, (596), 85-99.
- Engle, R. F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom İnflation. Econometrica: Journal of the Econometric Society, 987-1007.
- Eraslan, M., & Koç, S. (2022). Pay Senedi Endeksleri ile Endeks Vadeli İşlemler Arasındaki Volatilite İlişkisi: Türkiye ve Dünya Örnekleri Arasında Karşılaştırmalı Analiz. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, 23(3), 655-671.