Findings Of Asymetric Volatility During The Covid-19 Pandemic: A Review Of BIST Sector Indices

Year 2022, Volume: 6 Issue: 2, 2217 - 2233, 31.05.2022

Berkan Ataş Osman Emre Arlı

https://doi.org/10.29023/alanyaakademik.1025865

Cited By: 2

Abstract

Asymmetric volatility can be defined as negative fluctuations having a higher effect on the variance than positive fluctuations. Although this phenomenon is a structural feature of financial series, it is thought to strengthen even more during crisis periods. In this study, the presence of asymmetric volatility was tested as a result of the effect of the global crisis caused by the pandemic, which started to be seen in the Far East countries at the beginning of 2020 and then spread rapidly all over the world. The asymmetric volatility effect of the crisis on BIST primary sector indices has been examined. GJR-GARCH (1,1) statistical model is applied. Based on findings, although asymmetric volatility is a characteristic feature of BIST sector indices for both the pre-pandemic and pandemic periods, all sectors gave more significant results in the pandemic period. In addition, it is observed that the asymmetry coefficient is higher in all pandemic periods.

Keywords

Asymmetric Volatility, Covid-19, GJR-GARCH

Covid-19 Pandemisi Döneminde Asimetrik Volatilite Bulguları: BIST Sektör Endekslerinde Bir İnceleme

Abstract

Asimetrik volatilite negatif dalgalanmaların varyans üzerinde pozitif dalgalanmalara göre daha yüksek etki yaratması olarak tanımlanabilir. Bu olgu finansal serilerin yapısal bir özelliği olmakla birlikte kriz dönemlerinde daha da derinleştiği düşünülmektedir. Bu çalışmada 2020 başlarında uzak doğu ülkelerinde görülmeye başlayan daha sonra hızla tüm dünyaya yayılan pandemi kaynaklı küresel krizin etkisi sonucu asimetrik volatilite varlığı test edilmiştir. Pandemi kaynaklı krizin BIST birincil sektör endeksleri üzerinde yarattığı asimetrik volatilite etkisi incelenmiştir. Çalışmada GJR-GARCH (1,1) istatistiksel modeli kullanılmıştır. Bulunan sonuçlara göre asimetrik volatilite hem pandemi öncesi hem de pandemi dönemi için BIST sektör endekslerinin karakteristik bir özelliği olmakla birlikte bütün alt sektörler kriz sonrası dönemde daha anlamlı derecede sonuçlar vermiştir. Ayrıca asimetri katsayısının kriz sonrası dönemlerin tamamında daha yüksek olduğu görülmüştür.

Keywords

Asimetrik Volatilite, Covid-19, GJR-GARCH

References

• ABOURA, S., & CHEVALLIER, J. (2013). “Leverage vs. Feedback: Which Effect Drives the Oil Market?”, Finance Research Letters, 10(3), 131-141.
• BARNDORFF-NIELSEN, O. E., KINNEBROCK, S., & SHEPHARD, N. (2008). “Measuring Ddownside Risk-Realised Semivariance”, Creates Research Paper, (2008-42).
• BAUR, D. G. (2012). “Asymmetric Volatility in the Gold Market”, The Journal of Alternative Investments, 14(4), 26-38.
• BAUR, D. G., & DIMPFL, T. (2018). “Asymmetric Volatility in Cryptocurrencies”, Economics Letters, 173, 148-151.
• BOLLERSLEV, T. (1986): “Generalized Autoregressive Conditional Heteroskedasticity”, Journal of Econometrics, 31, 307-327
• BROOKS, C. (2008). Introductory econometrics for finance (2nd ed.). Cambridge University Press.
• CAMPBELL, J. Y., & HENTSCHEL, L. (1992). “No News is Good News: An Asymmetric Model of Changing Volatility in Stock Returns”, Journal of financial Economics, 31(3), 281-318.
• CAO, C. Q., & TSAY, R. S. (1992). “Nonlinear Time‐Series Analysis of Stock Volatilities”, Journal of Applied Econometrics, 7(S1), S165-S185.
• CHEN, R., BAO, W., & JIN, C. (2021). “Investor Sentiment and Predictability for Volatility on Energy Futures Markets: Evidence from China”, International Review of Economics & Finance, 75, 112-129.
• CHIARELLA, C., KANG, B., NIKITOPOULOS, C. S., & TÔ, T. D. (2016). “The Return–Volatility Relation in Commodity Futures Markets”, Journal of Futures Markets, 36(2), 127-152.
• CHRISTENSEN, B. J., NIELSEN, M. Ø., & ZHU, J. (2015). “The İmpact of Financial Crises On The Risk–Return Tradeoff and The Leverage Effect”, Economic Modelling, 49, 407-418.
• CHRISTIE, A. A. (1982). “The Stochastic Behavior of Common Stock Variances: Value, Leverage and Interest Rate Effects”, Journal of financial Economics, 10(4), 407-432.
• COX, J. C., & ROSS, S. A. (1976). “The Valuation of Options for Alternative Stochastic Processes”, Journal of Financial Economics, 3(1-2), 145-166.
• DENNIS, P., MAYHEW, S., & STIVERS, C. (2006). “Stock Returns, Implied Volatility Innovations, and The Asymmetric Volatility Phenomenon”, Journal of Financial and Quantitative Analysis, 381-406.
• ENGLE, R. F. (1982). “Autoregressive Conditional Heteroscedasticity with Estimates of Variance of United Kingdom Inflation”, Econometrica. 50 (4): 987–1008. doi:10.2307/1912773
• GLOSTEN, L., JAGANNATHAN, R., RUNKLE, D., (1993). “Relationship Between the Expected Value and the Volatility of the Nominal Excess Return on Stocks”, J. Finance 48, 1779–1801.
• GOUDARZI, H., & RAMANARAYANAN, C. S. (2011). “Modeling Asymmetric Volatility in the Indian Stock Market”, International Journal of Business and Management, 6(3), 221.
• HASSAN, S. A. (2011). “Modeling Asymmetric Volatility in Oil Prices”, Journal of Applied Business Research (JABR), 27(3), 71-78.
• HORPESTAD, J. B., LYÓCSA, Š., MOLNÁR, P., & OLSEN, T. B. (2019). “Asymmetric Volatility in Equity Markets Around the World”, The North American Journal of Economics and Finance, 48, 540-554.
• KARMAKAR, M. (2007). “Asymmetric Volatility and Risk-Return Relationship in the Indian Stock Market”, South Asia Economic Journal, 8(1), 99-116.
• KOUTMOS, G., & BOOTH, G. G. (1995). “Asymmetric Volatility Transmission in International Stock Markets”, Journal of international Money and Finance, 14(6), 747-762.
• LOW, C. (2004). “The Fear and Exuberance From Implied Volatility Of S&P 100 Index Options”, The Journal of Business, 77(3), 527-546.
• LUO, J., & WANG, S. (2019). “The Asymmetric High-Frequency Volatility Transmission Across International Stock Markets”, Finance Research Letters, 31, 104-109.
• MAITRA, D., GUHATHAKURTA, K., & KANG, S. H. (2021). “The Good, The Bad and the Ugly Relation Between Oil and Commodities: An Analysis Of Asymmetric Volatility Connectedness and Portfolio Implications”, Energy Economics, 94, 105061.
• PAGAN, A. R., & SCHWERT, G. W. (1990). “Alternative Models For Conditional Stock Volatility”, Journal of Econometrics, 45(1-2), 267-290.
• SCHWERT, G. W. (1990). “Stock Volatility and the Crash of’87”, The Review of Financial Studies, 3(1), 77-102.
• TODOROVA, N. (2017). “The Asymmetric Volatility in the Gold Market Revisited”, Economics Letters, 150, 138-141.
• WANG, J., & YANG, M. (2009). “Asymmetric Volatility in the Foreign Exchange Markets”, Journal of International Financial Markets, Institutions and Money, 19(4), 597-615.
• WU, G. (2001). “The Determinants of Asymmetric Volatility”, The Review of Financial Studies, 14(3), 837-859.
• XIANG, J., & ZHU, X. (2014). “Intraday Asymmetric Liquidity and Asymmetric Volatility in FTSE-100 Futures Market”, Journal of Empirical Finance, 25, 134-148.