CDS Primleri ile Petrol Arasındaki Bağlantılılık ve Portföy Stratejileri: Asimetrik TVP-VAR Yaklaşımdan Kanıtlar

Year 2025, Volume: 39 Issue: 2, 231 - 253, 15.04.2025

Bahri Fatih Tekin , Zekai Şenol

https://doi.org/10.16951/trendbusecon.1576540

Abstract

Bu çalışmada petrol ihraç eden altı ülke CDS primleriyle ham petrol getirileri arasındaki bağlantılılık, portföy stratejileri ve riskten korunma (hedge) açısından çeşitli analizler yapılmıştır. Çalışmada 16 Şubat 2011 ile 23 Şubat 2022 dönemine ait günlük fiyat verileri kullanılmıştır. Çalışmada asimetrik TVP-VAR (Time-Varying Parameter Vector Autoregression) analizi, hedge ve çoklu portföy strateji yöntemleri uygulanmıştır. Çalışmada petrol ihraç eden ülke CDS primleri için ham petrolün net şok alıcısı olduğu, CDS primlerinin ham petrol volatilitesinin belirleyicisi olduğu, CDS primleri ile ham petrol arasındaki bağlantılıklarda asimetrik etkinin olduğu görülmüştür. CDS primleriyle ham petrolün içinde bulunduğu farklı portföy stratejilerinde ham petrol oranının %19-34 aralığında olduğu, bu bakımdan CDS portföylerinde ham petrolün önemli derecede yer aldığı belirlenmiştir. CDS primleriyle ham petrol arasındaki hedge katsayısının negatif olduğu yani CDS primleriyle ham petrol arasında doğal hedge imkanı olduğu, CDS primlerinin düşük maliyetle ham petrol ile hedge edilebileceği anlaşılmıştır. Ortaya çıkan sonuçlar ekonomi yönetimleri, risk yöneticileri, yatırımcılar ve portföy yöneticileri açısından önem taşımaktadır.

Keywords

CDS, Petrol, Volatilite, Bağlantılılık, Portföy Stratejileri, Asimetrik TVP-VAR

Connectedness and Portfolio Strategies Between CDS Premiums and Oil: Evidence from Asymmetric TVP-VAR Approach

Abstract

In addition to investigating the connectedness between the CDS premiums of six oil-exporting countries and crude oil returns, analyzes various portfolio strategies and hedging strategies. Daily price data for the period between February 16, 2011 and February 23, 2022 are used in the study. Asymmetric TVP-VAR (Time-Varying Parameter Vector Autoregression) analysis, hedging and multiple portfolio strategy methods were applied in the study. The study reveals that crude oil is a net shock receiver for oil-exporting country CDS premiums, CDS premiums are a determinant of crude oil volatility, and there is an asymmetric effect in the linkages between CDS premiums and crude oil. According to different portfolio strategies where CDS premiums and crude oil included, the crude oil ratio is in the range of 19-34%, indicating that crude oil has a significant role in the CDS portfolios. The hedge coefficients between CDS premiums and crude oil are negative, meaning that there is a natural hedge between CDS premiums and crude oil, and that CDS premiums can be hedged with crude oil at low cost. The results are important for economic administrations, risk managers, investors and portfolio managers.

Keywords

CDS, Oil, Volatility, Connectedness, Portfolio Strategies, Asymmetric TVP-VAR

References

• Abdullah, M., Chowdhury, M. A., & Sulong, Z. (2023). Asymmetric efficiency and connectedness among green stocks, halal tourism stocks, cryptocurrencies, and commodities: Portfolio hedging implications. Resources Policy, 81. [CrossRef]
• Adekoya, O. B., Akinseye, A. B., Antonakakis, N., Chatziantoniou, I., Gabauer, D., & Oliyide, J. (2022). Crude oil and Islamic sectoral stocks: Asymmetric TVP-VAR connectedness and investment strategies. Resources Policy, 78, 102877. [CrossRef]
• Aldasoro, I., & Ehlers, T. (2018, June). The credit default swap market: what a difference a decade makes. BIS Quarterly Review. [CrossRef]
• Amar, A. B., Goutte, S., & Isleimeyyeh, M. (2022). Asymmetric cyclical connectedness on the commodity markets: Further insights from bull and bear markets. The Quarterly Review of Economics and Finance, 85, 386-400. [CrossRef]
• Antonakakis, N., Chatziantoniou, I., & Gabauer, D. (2020). Refined measures of dynamic connectedness based on time-varying parameter vector autoregressions. Journal of Risk and Financial Management, 13(4), 84. [CrossRef]
• Antonakakis, N., Cunado, J., Filis, G., Gabuer, D., & de Gracia, F. (2020). Oil and asset classes implied volatilities: Investment strategies and hedging effectiveness. Energy Economics, 91, 104762. [CrossRef]
• Baffes, J., Kose, M., Ohnsorge, F., & Stocker, M. (2015, April). The great plunge in oil prices: causes, consequences, and policy responses. (1504). [CrossRef]
• Bajaj, V., Kumar, P., & Singh, V. K. (2023). Systemwide directional connectedness from crude oil to sovereign credit risk. Journal of Commodity Markets, 30. [CrossRef]
• Balcilar, M., Hammoudeh, S., & Toparli, E. A. (2018). On the risk spillover across the oil market, stock market, and the oil related CDS sectors: A volatility impulse response approach. Energy Economics, 74, 813-827. [CrossRef]
• BIS. (2023, Haziran 14). BIS. Haziran 14, 2023 tarihinde BIS: https://stats.bis.org/statx/srs/table/d5.2 adresinden alındı
• Blanco, R., Brennan, S., & Marsh, I. W. (2005, October). An empirical analysis of the dynamic relation between investment-grade bonds and credit default swaps. The Journal of Finance, 60(5), 2255-2281. [CrossRef]
• Bouri, E., Jalkh, N., & Roubaud, D. (2019). Commodity volatility shocks and BRIC sovereign risk: A GARCH-quantile approach. Resources Policy, 61, 385-392. [CrossRef]
• Bouri, E., Kachacha, I., & Roubaud, D. (2020). Oil market conditions and sovereign risk in MENA oil exporters and importers. Energy Policy, 137. [CrossRef]
• Broadstock, D. C., Chatziantoniou, I., & Gabauer, D. (2022). Minimum connectedness portfolios and the market for green bonds: Advocating socially responsible investment (SRI) activity. Applications in Energy Finance: The Energy Sector, Economic Activity, Financial Markets and the Environment, 217-253. [CrossRef]
• Cao, C., Yu, F., & Zhong, Z. (2010). The information content of option-implied volatility for credit default swap valuation. Journal of Financial Markets, 13(3), 321-343. [CrossRef]
• Chatziantoniou, I., & Gabauer, D. (2021). EMU risk-synchronisation and financial fragility through the prism of dynamic connectedness. The Quarterly Review of Economics and Finance, 79, 1-14. [CrossRef]
• Chen, Y., Msofe, Z. A., & Wang, C. (2024). Asymmetric dynamic spillover and time-frequency connectedness in the oil-stock nexus under COVID-19 shock: Evidence from African oil importers and exporters. Resources Policy, 90, 104849. [CrossRef]
• Christoffersen, P., Errunza, V., Jacobs, K., & Jin, X. (2014). Correlation dynamics and international diversification benefits. International Journal of Forecasting, 30(3), 807-824. [CrossRef]
• Chuffart, T., & Hooper, E. (2019). An investigation of oil prices impact on sovereign credit default swaps in Russia and Venezuela. Energy Economics, 80, 904-916. [CrossRef]
• Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 28(1), 57-66. [CrossRef]
• Diebold, F. X., & Yilmaz, K. (2014). On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of Econometrics, 182(1), 119-134. [CrossRef]
• Ederington, L. H. (1979). Ederington, L. H. (1979). The hedging performance of the new futures markets. The Journal of Finance, 34(1), 157-170. [CrossRef]
• Elliott, G., Rothenberg, T. J., & Stock, J. H. (1996). Efficient Tests For An Autoregressive Unit Root. Econometrica, 64(4), 813-836. [CrossRef]
• Ericsson, J., Jacobs, K., & Oviedo, R. (2009). The determinants of credit default swap premia. Journal of Financial and Quantitative Analysis, 44(1), 109-132. [CrossRef]
• Fabozzi, F. J., Cheng, X., & Chen, R. R. (2007). Exploring the components of credit risk in credit default swaps. Finance Research Letters, 4(1), 10-18. [CrossRef]
• Fonseca, J., Ignatieva, K., & Ziveyi, J. (2016). Explaining credit default swap spreads by means of realized jumps and volatilities in the energy market. Energy Economics, 56, 215-228. [CrossRef]
• Fontana, A., & Scheicher, M. (2016). An analysis of euro area sovereign CDS and their relation with government bonds. Journal of Banking & Finance, 62, 126-140. [CrossRef]
• Gabauer, D. (2021). Dynamic measures of asymmetric&pairwise connectedness within an optimal currency area: Evidence from the ERM I system. Journal of Multinational Financial Management, 60(100680). [CrossRef]
• Gök, R., Bouri, E., & Gemici, E. (2023). Volatility spillovers between sovereign CDS and futures markets in various volatility states: Evidence from an emerging economy around the pandemic. Research in International Business and Finance, 66. [CrossRef]
• Gürsoy, S., & Kılıç, E. (2021). Küresel Ekonomik Politik Belirsizliğin Türkiye CDS Primi ve BİST Bankacılık Endeksi Üzerindeki Volatilite Etkileşimi: DCC-GARCH Modeli Uygulaması. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 35(4), 1323-1334. [CrossRef]
• Hammoudeh, S., Liu, T., Chang, C.-L., & McAleer, M. (2013). Risk spillovers in oil-related CDS, stock and credit markets. Energy Economics, 36, 526-535. [CrossRef]
• Houweling, P., & Vorst, T. (2005). Pricing default swaps: Empirical evidence. Journal of international money and finance, 24(8), 1200-1225. [CrossRef]
• Hull, J., Predescu, M., & White, A. (2004, August 4). The relationship between credit default swap spreads, bond yields, and credit rating announcements. Journal of Banking & Finance, 28, 2789-2811. [CrossRef]
• Jarque, C. M., & Bera, A. K. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics Letters, 6(3), 255-259. [CrossRef]
• Koop, G., Pesaran, M., & Potter, S. (1996). Impulse response analysis in nonlinear multivariate models. Journal of Econometrics, 74(1), 119-147. [CrossRef]
• Lee, C.-C., Lee, C.-C., & Ning, S.-L. (2017). Dynamic relationship of oil price shocks and country risks. Energy Economics, 66, 571-581. [CrossRef]
• Lee, W. S., & Lee, H. S. (2024). Asymmetric Volatility Connectedness Among G7 Stock Markets. Economic Computation & Economic Cybernetics Studies & Research, 58(1).
• Maillard, S., Roncalli, T., & Teïletche, J. (2010). The properties of equally weighted risk contribution portfolios. Journal of Portfolio Management, 36(4).
• Markowitz, H. (1959). Portfolio selection: Efficient diversification of investments.
• Mensi, W., Al Rababa'a, A. R., Vo, X. V., & Kang, S. H. (2021). Asymmetric spillover and network connectedness between crude oil, gold, and Chinese sector stock markets. Energy Economics, 98. [CrossRef]
• Mensi, W., Shafiullah, M., Vo, X. V., & Kang, S. H. (2022). Asymmetric spillovers and connectedness between crude oil and currency markets using high-frequency data. Resources Policy, 77. [CrossRef]
• Mensi, W., Yousaf, I., Vo, X. V., & Kang, S. H. (2022). Asymmetric spillover and network connectedness between gold, BRENT oil and EU subsector markets. ournal of International Financial Markets, Institutions and Money, 76. [CrossRef]
• Naifar, N., Shahzad, S., & Hammoudeh, S. (2020). Dynamic nonlinear impacts of oil price returns and financial uncertainties on credit risks of oil-exporting countries. Energy Economics, 88. [CrossRef]
• Pavlova, I., Boyrie, M. E., & Parhizgari, A. M. (2018). A dynamic spillover analysis of crude oil effects on the sovereign credit risk of exporting countries. The Quarterly Review of Economics and Finance, 68, 10-22. [CrossRef]
• Pesaran, H. H., & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics Letters, 58(1), 17-29. [CrossRef]
• Shahzad, S. J., Bouri, E., Raza, N., & Roubaud, D. (2019). Asymmetric impacts of disaggregated oil price shocks on uncertainties and invesor sentiment. Review of Quantitative Finance and Accounting, 52, 901-921. [CrossRef]
• Sharpe, W. F. (1966). Mutual fund performance. The Journal of Business, 39(1), 119-138. [CrossRef]
• Stulz, R. M. (2010). Credit default swaps and the credit crisis. Journal of Economic Perspectives, 24(1), 73-92. [CrossRef]
• Tekin, B. (2024). Do economic uncertainty and politicalTekin, Bilgehan. "Do economic uncertainty and political risk steer CDS dynamics? An analysis of the Türkiye CDS. International Journal of Islamic and Middle Eastern Finance and Management. [CrossRef]
• Wang, J., Sun, X., & Li, J. (2020). How do sovereign credit default swap spreads behave under extreme oil price movements? Evidence from G7 and BRICS countries. Finance Research Letters, 34. [CrossRef]
• Yin, L., & Zhou, Y. (2016). What drives long-term oil market volatility? Fundamentals versus speculation. Economics, 10(1). [CrossRef]
• Zhang, W., Zhang, G., & Helwege, J. (2022). Cross country linkages and transmission of sovereign risk: Evidence from China's credit default swaps. Journal of Financial Stability, 58. [CrossRef]