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Covid-19 Döneminde Türkiye’de Finansal Varlıklar Arasındaki Volatilite Yayılımı: TVP-VAR Uygulaması

Year 2023, Volume: 8 Issue: 21, 339 - 357, 30.06.2023
https://doi.org/10.25204/iktisad.1204527

Abstract

Tüm dünyayı etkisi altına alan Covid-19 pandemisi finansal piyasalar da dahil olmak üzere yaşamın her alanını olumsuz etkilemiştir. Bu çalışmanın amacı Covid-19 döneminde Türkiye’de küresel ve yerel finansal varlıklar arasındaki dinamik bağlantılılık ilişkisini araştırmaktır. Dinamik bağlantılılık ilişkisini araştırabilmek için 11.03.2020-01.02.2022 dönemine ait veriler TVP-VAR yöntemi kullanılarak analiz edilmiştir. Analiz sonucunda elde edilen bulgulara göre Bitcoin fiyatı ve ons altın fiyatının volatiliteyi yayan değişkenler olduğu; BIST 100 endeksi, dolar kuru ve WTI ham petrol fiyatının ise volatiliteyi alan değişkenler olduğu belirlenmiştir. Volatiliteyi en çok alan değişken BIST 100 endeksi olurken ikinci sırada dolar kuru üçüncü sırada ise WTI ham petrol fiyatı yer almaktadır. BIST 100 endeksinin ons altın, Bitcoin ve dolar kurunda meydana gelen değişmelerden etkilendiği görülürken, BIST 100 endeksini en fazla etkileyen değişkenin ons altın olduğu belirlenmiştir. Ulaşılan bu sonuçların portföy yöneticileri, riskten korunmak isteyenler, politika yapıcılar, yatırım stratejisi oluşturmak isteyenler açısından faydalı olacağı düşünülmektedir.

References

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Spread of Volatility Among Financial Assets in Türkiye During Covid-19 Period: TVP-VAR Application

Year 2023, Volume: 8 Issue: 21, 339 - 357, 30.06.2023
https://doi.org/10.25204/iktisad.1204527

Abstract

The Covid-19 pandemic, which has affected the whole world, has adversely affected all areas of life, including financial markets. The aim of this study is to investigate the dynamic connectedness between global and local financial assets in Türkiye during the Covid-19 period. Data for the period 11.03.2020-01.02.2022 were analyzed using the TVP-VAR method in order to investigate the dynamic connectivity relationship. According to the findings obtained as a result of the analysis, Bitcoin price and ounce gold price are variables that volatility transmitters; it has been determined that BIST 100 index, dollar rate and WTI crude oil price are volatility receivers. The variable with the highest volatility is the BIST 100 index, while the dollar rate is in the second place and the WTI crude oil price is in the third place. While BIST 100 index is the variable that receives the most this volatility, the dollar rate is in second place and the WTI crude oil price is in third place. While it was observed that the BIST 100 index was affected by the changes in the ounce gold, Bitcoin and dollar rates, it was determined that the variable that most affected the BIST 100 index was ounce gold. It is thought that these results will be beneficial for portfolio managers, hedgers, policymakers, and those who want to create an investment strategy.

References

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  • Andersen, T. G., Bollerslev, P. Christoffersen ve F. X. Diebold. 2006. Volatility forecasting. In Handbook of economic forecasting, ed. G. Elliott, C. Granger, and A. Timmermann, 778–878. Amsterdam: North-Holland.
  • Antonakakis, N., Chatziantoniou, I. ve Gabauer, D. (2020). Refined measures of dynamic connectedness based on time-varying parameter vector autoregressions. Journal of Risk and Financial Management, 13(4), 84. https://doi.org/10.3390/jrfm13040084
  • Antonakakis, N., Cuñado, J., Filis, G., Gabauer, D. ve de Gracia, F. P. (2019a). Oil and asset classes implied volatilities: dynamic connectedness and investment strategies. Available at SSRN 3399996. http://dx.doi.org/10.2139/ssrn.3399996
  • Antonakakis, N., Gabauer, D., ve Gupta, R. (2019b). International monetary policy spillovers: Evidence from a time-varying parameter vector autoregression. International Review of Financial Analysis, 65, 101382. https://doi.org/10.1016/j.irfa.2019.101382
  • Antonakakis, N., Gabauer, D., ve Gupta, R. (2019c). Greek economic policy uncertainty: Does it matter for Europe? Evidence from a dynamic connectedness decomposition approach. Physica A: Statistical Mechanics and Its Applications, 535, 122280. https://doi.org/10.1016/j.physa.2019.122280
  • Avşarlıgil, N. (2020). Covid-19 salgının Bitcoin ve diğer finansal piyasalar ile ilişkisi üzerine bir inceleme. Alanya Akademik Bakış, 4(3), 665-682. https://doi.org/10.29023/alanyaakademik.735214
  • Ayhan, F. ve Abdullazade, M. (2021). Türkiye ekonomisinde Covid-19 salgını sonrasında petrol ve altın fiyatları ile vaka sayılarının döviz kuru üzerindeki etkileri. Yaşar Üniversitesi E-Dergisi, 16(62), 509-523. https://doi.org/10.19168/jyasar.887005
  • Ayrancı, A.E. ve Arı, G. (2021). Covid-19 Pandemisinin BIST sektör endeksleri ile ilişkisi: Bayer-Hanck (2013) eşbütünleşme analizi. İşletme Araştırmaları Dergisi, 13(4), 3770-3785. https://doi.org/10.20491/isarder.2021.1355
  • Bahrini, R. ve Filfilan, A. (2020). Impact of the novel coronavirus on stock market returns: evidence from GCC countries. Quantitative Finance and Economics, 4(4), 640-652. https://doi.org/10.3934/QFE.2020029
  • Baker, S.R., Bloom, N., Davis, S.J., Kost, K., Sammon, M. ve Viratyosin, T. (2020). The unprecedented stock market reaction to COVID-19. The Review of Asset Pricing Studies, 10(4), 742-758. https://doi.org/10.1093/rapstu/raaa008
  • Baruník, J. ve Křehlík, T. (2018). Measuring the frequency dynamics of financial connectedness and systemic risk. Journal of Financial Econometrics, 16(2), 271-296. https://doi.org/10.1093/jjfinec/nby001
  • Bayer, C. ve Hanck, C. (2013). Combining non-cointegration tests. Journal of Time Series Analysis, 34(1): 83-95. https://doi.org/10.1111/j.1467-9892.2012.00814.x
  • Beirne, J., Renzhi, N., Sugandi, E. ve Volz, U. (2020). Financial market and capital flow dynamics during the COVID-19 pandemic. Asian Development Bank Institute Working Paper 1158, 1-36. https://doi.org/10.2139/ssrn.3656848
  • Bouhali, H., Dahbani, A. ve Dinar, B. (2021). COVID-19 impacts on financial markets: takeaways from the third wave. Russian Journal of Economics, 7, 200-212. https://doi.org/10.32609/j.ruje.7.65328
  • Bouri, E., Cepni, O., Gabauer, D. ve Gupta, R. (2021). Return connectedness across asset classes around the COVID-19 outbreak. International Review of Financial Analysis, 73, 101646. https://doi.org/10.1016/j.irfa.2020.101646
  • Büyükakın, F. ve Demir, S. (2022). COVID-19 sürecinin türk finansal sistemine yönelik etkilerinin Toda-Yamamoto yöntemi ile analizi. Aksaray Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 14(4), 387-396. https://doi.org/10.52791/aksarayiibd.1053192
  • Caporale, G. M., Catik, A. N., Helmi, M. H., Akdeniz, C. ve Ilhan, A. (2021). The effects of the Covid-19 pandemic on stock markets, CDS and economic activity: Time-varying evidence from the US and Europe. CESifo Working Paper No. 9316. http://dx.doi.org/10.2139/ssrn.3932024
  • Cogley, T. ve Sargent, T.J. (2005). Drifts and volatilities: Monetary policies and outcomes ın the post WWII US. Review of Economic Dynamics, 8(2), 262-302. https://doi.org/10.1016/j.red.2004.10.009
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There are 65 citations in total.

Details

Primary Language Turkish
Subjects Econometric and Statistical Methods, Finance
Journal Section Research Papers
Authors

Arife Özdemir Höl 0000-0002-9902-9174

Early Pub Date June 24, 2023
Publication Date June 30, 2023
Submission Date November 15, 2022
Published in Issue Year 2023 Volume: 8 Issue: 21

Cite

APA Özdemir Höl, A. (2023). Covid-19 Döneminde Türkiye’de Finansal Varlıklar Arasındaki Volatilite Yayılımı: TVP-VAR Uygulaması. İktisadi İdari Ve Siyasal Araştırmalar Dergisi, 8(21), 339-357. https://doi.org/10.25204/iktisad.1204527
AMA Özdemir Höl A. Covid-19 Döneminde Türkiye’de Finansal Varlıklar Arasındaki Volatilite Yayılımı: TVP-VAR Uygulaması. JEBUPOR. June 2023;8(21):339-357. doi:10.25204/iktisad.1204527
Chicago Özdemir Höl, Arife. “Covid-19 Döneminde Türkiye’de Finansal Varlıklar Arasındaki Volatilite Yayılımı: TVP-VAR Uygulaması”. İktisadi İdari Ve Siyasal Araştırmalar Dergisi 8, no. 21 (June 2023): 339-57. https://doi.org/10.25204/iktisad.1204527.
EndNote Özdemir Höl A (June 1, 2023) Covid-19 Döneminde Türkiye’de Finansal Varlıklar Arasındaki Volatilite Yayılımı: TVP-VAR Uygulaması. İktisadi İdari ve Siyasal Araştırmalar Dergisi 8 21 339–357.
IEEE A. Özdemir Höl, “Covid-19 Döneminde Türkiye’de Finansal Varlıklar Arasındaki Volatilite Yayılımı: TVP-VAR Uygulaması”, JEBUPOR, vol. 8, no. 21, pp. 339–357, 2023, doi: 10.25204/iktisad.1204527.
ISNAD Özdemir Höl, Arife. “Covid-19 Döneminde Türkiye’de Finansal Varlıklar Arasındaki Volatilite Yayılımı: TVP-VAR Uygulaması”. İktisadi İdari ve Siyasal Araştırmalar Dergisi 8/21 (June 2023), 339-357. https://doi.org/10.25204/iktisad.1204527.
JAMA Özdemir Höl A. Covid-19 Döneminde Türkiye’de Finansal Varlıklar Arasındaki Volatilite Yayılımı: TVP-VAR Uygulaması. JEBUPOR. 2023;8:339–357.
MLA Özdemir Höl, Arife. “Covid-19 Döneminde Türkiye’de Finansal Varlıklar Arasındaki Volatilite Yayılımı: TVP-VAR Uygulaması”. İktisadi İdari Ve Siyasal Araştırmalar Dergisi, vol. 8, no. 21, 2023, pp. 339-57, doi:10.25204/iktisad.1204527.
Vancouver Özdemir Höl A. Covid-19 Döneminde Türkiye’de Finansal Varlıklar Arasındaki Volatilite Yayılımı: TVP-VAR Uygulaması. JEBUPOR. 2023;8(21):339-57.