Küresel Belirsizlik Şoklarına ETF Piyasalarının Tepkisi: Yeni Sanayileşen Ülkeler Üzerine Bir Uygulama

Year 2025, Volume: 10 Issue: 2, 377 - 395

Fazlı Irmak

Abstract

Bu çalışmada, yeni sanayileşen ülkelerdeki iShares MSCI ETF fonları ile küresel risk ve belirsizlik göstergeleri olan VIX endeksi, altın (ONS) ve Brent petrol volatilitesi arasındaki kısa ve uzun vadeli ilişkileri incelemektedir. 2012 Şubat-2025 Nisan dönemine ait yeni sanayileşen ülkelere ilişkin aylık veriler kullanılarak Johansen eşbütünleşme testi ve Vektör Hata Düzeltme Modeli (VECM) uygulanmıştır. Ampirik bulgular, uzun dönemde çoğu ülke için ETF ile VIX arasında anlamlı ve negatif yönlü uzun dönemli bir ilişki olduğunu ortaya koymaktadır. Altın volatilitesi bazı ülkelerde pozitif etkiler yaratırken, Brent petrol oynaklığının özellikle enerji ithalatçısı ülkelerde ETF fiyatlarını olumsuz etkilediği tespit edilmiştir. Kısa dönem analizleri Brezilya, Endonezya, Filipinler, Malezya, Tayland ve Türkiye’de ETF fiyatları üzerinde negatif etkileri belirlenmiştir. Buna karşılık VIX endeksi ile altın volatilitesine verilen kısa dönem tepkiler ülke bazında farklılık göstermektedir. Hata düzeltme katsayıları, bazı ülkelerde kısa vadeli sapmaların uzun vadede dengeye geldiğini göstermektedir. Sonuçlar, ETF piyasalarının küresel risk ve belirsizliklere karşı yüksek duyarlılığa sahip olduğunu, ancak bu etkinin ülke ekonomilerinin enerji bağılılığı finansal derinliği gibi ülkeye özgü faktörlere göre değiştiğini ortaya koymaktadır. Bulgular, yatırımcılar ve politika yapıcılar açısından ülkeye özgü risk yönetim stratejilerinin önemini vurgulamaktadır.

Keywords

Borsa Yatırım Fonları (ETF) , Yeni sanayileşen Ülkeler , Küresel Belirsizlik , VECM

Ethical Statement

Bu çalışmada herhangi bir etik kurul onayı gerektiren bir insan veya hayvan deneyi gerçekleştirilmemiştir.

Supporting Institution

Destekleyen kurum bulunmamaktadır

The Response of ETF Markets to Global Uncertainty Shocks: Evidence from Newly Industrialized Countries

Abstract

This study investigates the short- and long-term relationships between iShares MSCI ETF funds in newly industrialized countries and the global risk and uncertainty indicators represented by the VIX index, gold (ONS), and Brent oil volatility. Using monthly data for the period from February 2012 to April 2025, the Johansen cointegration test and the Vector Error Correction Model (VECM) are applied. The empirical findings reveal a significant and negative long-run relationship between ETFs and the VIX index for most countries. While gold volatility generates positive effects in some markets, Brent oil volatility adversely affects ETF prices, particularly in energy-importing economies. The short-run analyses indicate that ETF prices in Brazil, Indonesia, the Philippines, Malaysia, Thailand, and Turkey are negatively influenced by volatility shocks. Conversely, short-run responses to VIX and gold volatility differ across countries. The error-correction coefficients demonstrate that short-term deviations from equilibrium tend to adjust in the long run-in certain markets. Overall, the results suggest that ETF markets in newly industrialized countries are highly sensitive to global risk and uncertainty; however, the magnitude of this sensitivity varies depending on country-specific factors such as energy dependence and financial depth. These findings emphasize the importance of designing country-specific risk management strategies for both investors and policymakers.

Keywords

Exchange Traded Funds (ETFs) , Emerging Markets , Global Uncertainty , VECM

Ethical Statement

This study did not involve any human or animal experiments requiring ethical committee approval.

Supporting Institution

There is no funding or supporting institution for this study.

References

• Akaike, H. (1978). On the Likelihood of a time series model. Journal of the Royal Statistical Society: Series D (The Statistician), 27(3-4), 217-235. https://doi.org/10.2307/2988185
• Ambachtsheer, K. P. (1987). Pension fund asset allocation: In defense of a 60/40 equity/debt asset mix. Financial Analysts Journal, 43(5), 14-24.
• Aypek, N., Cingöz, F., & Deniz, F. (2025). Borsa yatirim fonu endekslerinin kredi temerrüt swap primi değişimlerine tepkileri: Karılgan beşli ülkeler örneği. Üçüncü Sektör Sosyal Ekonomi Dergisi, 60(1), 281-296.
• Başarır, Ç. & Keten, M. (2016). Gelişmekte olan ülkelerin CDS primleri ile hisse senetleri ve döviz kurları arasındaki kointegrasyon ilişkisi. Mehmet Akif Ersoy Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 8(15), 369-380. https://doi.org/10.20875/sb.72076
• Baur, D. G., & Lucey, B. M. (2010). Is Gold a hedge or a safe haven? An analysis of stocks, bonds and gold. Financial Review, 45(2), 217-229. https://doi.org/10.1111/j.1540-6288.2010.00244.x
• Bekmez, S. ve Özpolat, A. (2013). Gelir esnekliğinin ve kentsel dönüşüm uygulamalarinin konut talebine etkisinin VECM yöntemi ile tahmin edilmesi. Akdeniz İİBF Dergisi, 13(27), 99-113.
• Bernanke, B. S. (1986). Alternative explanations of the money-income correlation. Carnegie-Rochester Conference Series on Public Policy, Elsevier, 25(1), 49-99. DOI 10.3386/w1842
• Bernanke, B. S., & Mihov, I. (1998). Measuring monetary policy. The Quarterly Journal of Economics, 113(3), 869-902. https://doi.org/10.1162/003355398555775
• Bhattacharjee, A. & Das, J. (2020). Do Indian stock prices respond to domestic macroeconomic variables. NMIMS Management Review, 38(3), 55-71.
• Bloomberght (2024). Fitch: Türkiye’de islami finans büyüklüğü 100 milyar dolara ulaşabilir, <https://www.bloomberght.com/fitch-turkiyede-islami-finans-buyuklugu-100-milyar-dolara-ulasabilir-2341117>20.08.2024. (Erişim Tarihi: 04.11.2024).
• Booth, D. G., & Fama, E. F. (1992). Diversification returns and asset contributions. Financial Analysts Journal, 48(3), 26-32.
• Borsa İstanbul (BİST) (2024). <https://borsaistanbul.com/tr/endeks/1/3/katilim>, (Erişim Tarihi: 20.11.2024).
• Chan, K. C., Fung, H. G. & Zhang, G. (2009). On the relationship between asian credit default swap and equity markets. Journal of Asia Business Studies, 4(1), 3-12. https://doi.org/10.1108/15587890980000414
• Chan-Lau, J. A. & Kim, Y. S. (2004). Equity prices, credit default swaps, and bond spreads in emerging markets. IMF Working Paper, WP/04/27, International Capital Markets.
• Cifarelli, G., & Paladino, G. (2010). Oil price dynamics and speculation: A multivariate financial approach. Energy Economics, 32(2), 363-372.
• Coronado, M., Corzo, M. T. ve Lazcano, L. (2012). A case for europe: the relationship between sovereign CDS and stock indexes. Frontiers in Finance and Economics, 9(2), 32-63.
• Dewandaru, G., Rizvi, S.A.R., Masih, R., Masih, M. & Alhabshi, S.O. (2014). Stock market co-movements: Islamic versus conventional equity indices with multi-timescales analysis. Economic Systems, 38(4), 553-571. https://doi.org/10.1016/j.ecosys.2014.05.003
• Ehrmann, M., Fratzscher, M., Mehl, A., & Bekaert, G. (2011). Global crises and equity market contagion. Working Paper Series 1381, European Central Bank.
• Elliott, G., Rothenberg, T. J. & Stock, J. H. (1992). Efficient tests for an autoregressive unit root. NBER Technical Working Papers Series, 130, Technical Working Paper, Cambridge, Mass.
• Engle, R. F., & Granger, C. W. (1987). Co-integration and error correction: Representation, Estimation, and testing. Econometrica: journal of the Econometric Society, 251-276. https://doi.org/10.2307/1913236
• Filis, G., Degiannakis, S., & Floros, C. (2011). Dynamic correlation between stock market and oil prices: The case of oil-importing and oil-exporting countries. International Review of Financial Analysis, 20(3), 152-164.
• Gazel, S. (2020). The effect of exchange rate and CDS premium on msci etf investments: A NARDL model for Turkey. International Journal of Eurasia Social Sciences/Uluslararasi Avrasya Sosyal Bilimler Dergisi, 11(40).
• Granger, C. W. (1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica: Journal of the Econometric Society, 424-438. https://doi.org/10.2307/1912791
• Habib, M. & Islam, K. U. (2017). Impact of macroeconomic variables on islamic stock market returns: Evidence from NIFTY 50 shariah index. Journal of Commerce and Accounting Research, 6(1), 37-44.
• Hakim, S. & Rashidian, M. (2002). Risk and return of islamic stock market indexes, In 9th Economic Research Forum Annual Conference in Sharjah, United Arab Emirates.
• Hamilton, J. D. (1994). Time series analysis, Princeton University Press.
• Hammoudeh, S., Mensi, W., Reboredo, J. C. & Nguyen, D. K. (2014). Dynamic dependence of the global islamic equity index with global conventional equity market indices and risk factors. Pacific-Basin Finance Journal, 30, 189-206. https://doi.org/10.1016/j.pacfin.2014.10.001
• Ho, C.S.F., Abd Rahman, N.A., Yusuf, N.H.M. & Zamzamin, Z. (2014), Performance of global islamic versus conventional share indices: International evidence. Pacific-Basin Finance Journal, 28, 110-121. https://doi.org/10.1016/j.pacfin.2013.09.002
• Hood, M., & Malik, F. (2013). Is gold the best hedge and a safe haven under changing stock market volatility?. Review of Financial Economics, 22(2), 47-52.
• Horn, M., & Oehler, A. (2020). Automated portfolio rebalancing: Automatic erosion of investment performance?. Journal of Asset Management, 21, 489-505
• İçellioğlu, C. Ş. (2018). Sermaye piyasalarinda islami endeksler ve geleneksel endeksler arasındaki ilişkiler: Katılım 30 endeksi ve BİST 100 endeksi. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, 19(2), 132-144.
• Jain, A., & Biswal, P. C. (2016). Dynamic linkages among oil price, gold price, exchange rate, and stock market in India. Resources Policy, 49, 179-185.
• Johansen, S. (1988). Statistical Analysis of Cointegration Vectors. Journal of Economic Dynamics and Control, 12(2-3), 231-254. https://doi.org/10.1016/0165-1889(88)90041-3
• Johansen, S. & Juselius, K. (1990). Maximum Likelihood Estimation and Inference on Cointegration—With Appucations to the Demand for Money. Oxford Bulletin of Economics and Statistics, 52(2), doi:169-210. 10.1111/j.1468-0084.1990.mp52002003.x
• Kenourgios, D., Naifar, N., & Dimitriou, D. (2016). Islamic financial markets and global crises: Contagion or decoupling?. Economic Modelling, 57, 36-46. https://doi.org/10.1016/j.econmod.2016.04.014
• Koch, T. W. & Saporoschenko, A. (2001). The effect of market returns, interest rates, and exchange rates on the stock returns of Japanese horizontal keiretsu financial firms. Journal of Multinational Financial Management, 11(2), 165-182. https://doi.org/10.1016/S1042-444X(00)00048-7
• Konak, F. & Türkoğlu, D. (2022). Borsa Istanbul bünyesinde katılım endeksi oluşturulmasının hisse senedi fiyatlari üzerindeki etkisi. USBAD Uluslararası Sosyal Bilimler Akademi Dergisi, 4(10), 813-831. https://doi.org/10.47994/usbad.1140256
• Longstaff, F. A., Pan, J., Pedersen, L. H., & Singleton, K. J. (2011). How sovereign is sovereign credit risk?. American Economic Journal: Macroeconomics, 3(2), 75-103.
• LSEG (London Stock Exchange Group). (2024). <https://www.lseg.com/en/data-analytics/products/eikon-trading-software/islamic-finance>, (Erişim Tarihi: 20.12.2024).
• MacKinnon, J.G., Haug, A.A. & Michelis, L. (1999). Numerical Distribution functions of likelihood ratio tests for cointegration. Journal of Applied Econometrics, 14, 563-577. https://doi.org/10.1002/(SICI)1099-1255(199909/10)14:5<563::AID-JAE530>3.0.CO;2-R
• Maysami, R. C., Lee, C. H. & Hamzah, M. A. (2004). Relationship between macroeconomic variables and stock market indices: Cointegration evidence from stock exchange of Singapore’s All-S sector indices. Jurnal Pengurusan, 24, 47-77.
• Naeem, M. A., Qureshi, F., Arif, M. & Balli, F. (2021). Asymmetric relationship between gold and islamic stocks in bearish, normal and bullish market conditions. Resources Policy, 72, 102067. https://doi.org/10.1016/j.resourpol.2021.102067
• Naifar, N. (2016). Do global risk factors and macroeconomic conditions affect global islamic index dynamics? A quantile regression approach. The Quarterly Review of Economics and Finance, 61, 29-39. https://doi.org/10.1016/j.qref.2015.10.004
• Nath Sahu, T., Bandopadhyay, K. & Mondal, D. (2014). An empirical study on the dynamic relationship between oil prices and Indian stock market. Managerial Finance, 40(2), 200-215. https://doi.org/10.1108/MF-06-2013-0131
• Nishat, M., Shaheen, R. & Hijazi, S. T. (2004). Macroeconomic factors and the Pakistani equity market.  The Pakistan Development Review, 43(4), 619-637.
• Özer, A., Kaya, A. & Özer, N. (2011). Hisse senedi fiyatlari ile makroekonomik değişkenlerin etkileşimi. Dokuz Eylül Üniversitesi İktisadi İdari Bilimler Fakültesi Dergisi, 26(1), 163-182.
• Panda, C. (2008). Do interest rates matter for stock markets?. Economic and Political Weekly, 43(17), 107-115.
• Purbowisanti, R. (2018). The relationship between exchange rates and islamic indices in Indonesia and Malaysia. An-Nisbah: Jurnal Ekonomi Syariah, 4(2), 30-52.
• Rahim, Y.A. & Masih, M. (2015). Is islamic stock index secured against interest rate risk? Evidence from wavelet analysis. MPRA Paper, 65259, Munich, Germany.
• Raza, N., Ali, S., Shahzad, S. J. H., Rehman, M. U. & Salman, A. (2019). Can alternative hedging assets add value to islamic-conventional portfolio mix: Evidence from MGARCH models. Resources Policy, 61, 210-230. https://doi.org/10.1016/j.resourpol.2019.02.013
• Rizvi, S. A. R., Bacha, O. I. ve Mirakhor, A. (2016). Public finance and islamic capital markets: Theory and application, içinde: Iqbal, Z., Sultan, J. ve Asutay, M.Springer (Ed.). Capital Markets: Conventional Versus Islamic (s. 45-63), New York: Palgrave Macmillan.
• Sahu, P. K., Dey, S., Sinha, K., Singh, H. & Narsimaiaha, L. (2019). Cointegration and price discovery mechanism of major spices in India. American Journal of Applied Mathematics and Statistics, 7(1), 18-24. doi:10.12691/ajams-7-1-3
• Sakti, M. R. P. & Harun, M. Y. (2013). Relationship between islamic stock prices and macroeconomic variables: Evidence from Jakarta stock exchange islamic index. Global Review of Islamic Economics and Business, 1(1), 71-84. https://doi.org/10.14421/grieb.2013.011-06
• Sancar, C., Uğur, A. & Akbaş, Y. E. (2017). Hisse senedi fiyat endeksi ile makroekonomik değişkenler arasındaki ilişkinin analizi: Türkiye örneği. International Journal of Social Sciences and Education Research, 3(5), 1774-1786.
• Shahzad, S. J. H., Ferrer, R., Ballester, L. & Umar, Z. (2017). Risk transmission between islamic and conventional stock markets: A return and volatility spillover analysis. International Review of Financial Analysis, 52, 9-26. https://doi.org/10.1016/j.irfa.2017.04.005
• Sims, C. A. (1986). Are Forecasting models usable for policy analysis?, Quarterly Review, 10(Win), 2-16.
• Shiller, R. J. & Beltratti, A. E. (1992). Stock prices and bond yields: Can Their comovements be explained in terms of present value models?. Journal of Monetary Economics, 30(1), 25-46. https://doi.org/10.1016/0304-3932(92)90042-Z
• Syzdykova, A. (2018). Makroekonomik değişkenler ve hisse senedi piyasası ilişkisi: KASE örneği. Çankırı Karatekin Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 8(2), 331-354. https://doi.org/10.18074/ckuiibfd.444811
• Tarı, R. & Yıldırım, D. Ç. (2009). Döviz kuru belirsizliğinin ihracata etkisi: Türkiye için bir uygulama. Yönetim ve Ekonomi Dergisi, 16(2), 95-105.
• Vejzagic, M. & Zarafat, H. (2013). Relationship between macroeconomic variables and stock market index: Cointegration evidence from FTSE bursa Malaysia hijrah shariah index. Asian Journal of Management Sciences & Education, 2(4), 94-108.
• Yalçınkaya, Ö. (2019). Türkiye ekonomisinde dış borçların sürdürülebilirliğinin analizi: Doğrusal ve doğrusal olmayan birim kök testlerinden kanıtlar (1970-2018). Maliye Dergisi, 176, 27-51.
• Yavas, B. F., & Rezayat, F. (2016). Country ETF returns and volatility spillovers in emerging stock markets, Europe and USA. International Journal of Emerging Markets, 11(3), 419-437.