The Impact of U.S.-China Tensions on Borsa Istanbul Stock Market: Evidence from ARDL Approach

Yıl 2025, Cilt: 9 Sayı: 2, 783 - 804, 20.06.2025

Onur Şeyranlıoğlu

https://doi.org/10.30586/pek.1589295

Öz

The aim of this study is to examine the impact of United States (U.S.)-China trade war tensions on the Borsa Istanbul (BIST) stock market. The study covers the period between January 2017 and February 2024. The reason for choosing this period is the escalation of U.S.-China trade tensions after Donald Trump took office as the 45th U.S. President in January 2017. In the research model, the BIST-100 Return Index is used as the dependent variable; the U.S.-China Tension Index developed by Roger et al. (2024) to represent the tensions arising from the U.S.-China trade war and the terms of trade, interest rate, inflation and exchange rate are considered as independent variables. The stationarity properties of the variables are analysed with Augmented Dickey and Fuller (ADF), Kwiatkowski et al. (KPSS, 1992), Christopoulos and León-Ledesma (2010) Fourier ADF and Becker et al. (2006) Fourier KPSS tests. Long and short-run relationships are analysed with the Autoregressive Distributed Lag (ARDL) bounds test approach. The results of the study show that increases in the U.S.-China Tension Index have a negative impact on the BIST-100 Return Index in both the long and short run. This finding reveals that Borsa Istanbul is sensitive to global geopolitical risks stemming from the U.S.-China trade war. The results point to the significant effects of global geopolitical risks on capital markets and emphasise that this is an important strategic factor that should be considered especially in terms of portfolio management and global risk management.

Anahtar Kelimeler

U.S.-China Tension Index , Borsa Istanbul , ARDL Bounds Approach

ABD-Çin Geriliminin Borsa İstanbul Hisse Senedi Piyasasına Etkisi: ARDL Yaklaşımından Kanıtlar

Öz

Bu araştırmanın amacı, Amerika Birleşik Devletleri (ABD)-Çin ticaret savaşı kaynaklı gerilimlerin Borsa İstanbul (BİST) hisse senedi piyasası üzerindeki etkisini incelemektir. Araştırma, Ocak 2017 ile Şubat 2024 dönemini kapsamaktadır. Bu dönemin seçilme nedeni, Donald Trump’ın Ocak 2017’de 45. ABD Başkanı olarak göreve başlamasıyla birlikte ABD-Çin ticari gerilimlerinin tırmanışa geçmesidir. Araştırma modelinde, BİST-100 Getiri Endeksi bağımlı değişken olarak kullanılmış; ABD-Çin ticaret savaşı kaynaklı gerilimleri temsilen, Roger vd. (2024) tarafından geliştirilen ABD-Çin Gerilim Endeksi ile dış ticaret haddi, faiz oranı, enflasyon ve döviz kuru bağımsız değişkenler olarak değerlendirilmiştir. Değişkenlerin durağanlık özellikleri, Augmented Dickey ve Fuller (ADF), Kwiatkowski vd. (KPSS, 1992), Christopoulos ve León-Ledesma (2010) Fourier ADF ve Becker vd. (2006) Fourier KPSS testleriyle analiz edilmiştir. Uzun ve kısa vadeli ilişkiler, Otoregresif Dağıtılmış Gecikmeli Sınır Testi (ARDL) yaklaşımıyla analiz edilmiştir. Araştırma sonuçları, ABD-Çin Gerilim Endeksi’ndeki artışların hem uzun hem de kısa dönemde BİST-100 Getiri Endeksi’ni olumsuz etkilediğini göstermiştir. Bu bulgu, Borsa İstanbul’un ABD-Çin ticaret savaşı kaynaklı küresel jeopolitik risklere duyarlı olduğunu ortaya koymaktadır. Sonuçlar, küresel jeopolitik risklerin sermaye piyasaları üzerindeki belirgin etkilerine işaret etmekte; bu durumun, özellikle portföy yönetimi ve küresel risk yönetimi açısından dikkate alınması gereken önemli bir stratejik faktör olduğunu vurgulamaktadır.

Anahtar Kelimeler

ABD-Çin Gerilim Endeksi , Borsa İstanbul , ARDL Sınır Yaklaşımı

Kaynakça

• Abiad, A.; Baris, K.; Bernabe, J. A.; Bertulfo, D. J.; Romance, S. C.; Feliciano, P. N.; Mariasingham, M. J.; Blackman, V. M. (2018). The impact of trade conflict on developing Asia. ADB Economics Working Paper Series, (No.556).
• Amiti, M.; Redding, S.; Weinstein, D. (2019). The impact of the 2018 trade war on U.S. prices and welfare. CEPR Discussion Paper, (No. 13564).
• Becker, R.; Enders, W.; Hurn, S. (2004). A general test for time dependence in parameters. Journal of Applied Econometrics, 19(7), 899-906.
• Becker, R.; Enders, W.; Lee, J. (2006). A stationarity test in the presence of an unknown number of smooth breaks. Journal of Time Series Analysis, 27(3), 381-409.
• Blanchard, E. J.; Santos‐Paulino, A. U.; Trentini, C.; Milet, E. (2021). Implications of rising trade tensions for FDI projects. Transnational Corporations Journal, 28(2), 161-183.
• Burggraf, T.; Fendel, R.; Huynh, T. L. D. (2020). Political news and stock prices: evidence from Trump’s trade war. Applied Economics Letters, 27(18), 1485-1488.
• Cai, Y.; Chang, H. W.; Chang, T. (2023). Evaluating time-varying Granger causality between US-China political relation changes and China stock market. Finance Research Letters, 55(A), 103918.
• Cai, Y.; Mignon, V.; Saadaoui, J. (2022). Not all political relation shocks are alike: Assessing the impacts of US–China tensions on the oil market. Energy Economics, 114, 106199.
• Capie, D.; Hamilton-Hart, N.; Young, J. (2020). The economics-security nexus in the US-China trade conflict decoupling dilemmas. Policy Quarterly, 16(4), 27-35.
• Carlomagno, G.; Albagli, E. (2022). Trade wars and asset prices. Journal of International Money and Finance, 124(C), 102631.
• Central Bank of the Republic of Türkiye’s Data Delivery System. (2024). All series, Access Date: 15.10.2024, Access address: https://evds2.tcmb.gov.tr
• Charbonneau, K. B. (2019). The impact of a trade war: Assessment of the current tariffs and alternative scenarios. Bank of Canada Staff Analytical Note, (No.20).
• Chen, Y.; Fang, J.; Liu, D. (2023). The effects of Trump’s trade war on US financial markets. Journal of International Money and Finance, 134, 102842.
• Chen, Y.; Pantelous, A. A. (2022). The US-China trade conflict impacts on the Chinese and US stock markets: A network-based approach. Finance Research Letters, 46(B), 102486.
• Chengying, H.; Rui, C.; Ying, L. (2022). US-China trade war and China’s stock market: An event-driven analysis. Economic research-Ekonomska istraživanja, 35(1), 3277-3290.
• Christopoulos, D. K.; León-Ledesma, M. A. (2010). Smooth breaks and non-linear mean reversion: Post-Bretton Woods real exchange rates. Journal of International Money and Finance, 29(6), 1076-1093.
• Danso, S. (2020). Political economy and regional policy: The impact of US-China trade tension on the global economic growth. Budapest International Research and Critics Institute Journal, 3(3), 2224-2232.
• De Nicola, F.; Kessler, M.; Nguyen, H. (2020). The financial costs of the United States-China trade tensions: Evidence from East Asian stock markets. Review of World Economics, 156, 803-833.
• Dickey, D. A.; Fuller, W. A. (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association, 74(366), 427-431.
• Dickey, D. A.; Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49(4), 1057-1072.
• Egger, P. H.; Zhu, J. (2020). The US-Chinese trade war: An event study of stock-market responses. Economic Policy, 35(103), 519-559.
• Enders, W. (2014). Applied econometric time series, 4th Edition; John Wiley: New York.
• Evans, O. (2019). The effects of US-China trade war and Trumponomics. Forum Scientiae Oeconomia, 7(1), 47-55.
• Ferrari Minesso, M.; Kurcz, F.; Pagliari, M. S. (2022). Do words hurt more than actions? The impact of trade tensions on financial markets. Journal of Applied Econometrics, 37(6), 1138-1159.
• Flynn, R.; Glennon, B.; Murciano-Goroff, R.; Xiao, J. (2024). Building a wall around science: The effect of US-China tensions on international scientific research. National Bureau of Economic Research, (No. 32622).
• Gunnella, V.; Quaglietti, L. (2019). The economic implications of rising protectionism: A Euro area and global perspective. ECB Economic Bulletin, Issue 3/2019.
• Hamilton, J. D. (1994). Time series analysis. Princeton University Press: Princeton.
• He, F.; Lucey, B.; Wang, Z. (2021). Trade policy uncertainty and its impact on the stock market-evidence from China-US trade conflict. Finance Research Letters, 40, 101753.
• Hepsağ, A. (2022). Ekonometrik zaman serileri analizlerinde güncel yöntemler. Der Yayınları: İstanbul.
• https://www.policyuncertainty.com/US_China_Tension.html, Access Date: 15.10.2024.
• Huang, Y. (2019). US-China economic tensions: Origins and global implications. China International Strategy Review, 1(1), 127-138.
• Huang, Y.; Lin, C.; Liu, S.; Tang, H. (2023). Trade networks and firm value: Evidence from the US-China trade war. Journal of International Economics, 145, 103811.
• Huynh, T. L. D.; Burggraf, T. (2020). If worst comes to worst: Co-movement of global stock markets in the US-China trade war. Economics and Business Letters, 9(1), 21-30.
• Ing, L. Y.; Vadila, Y. (2019). US–China trade tensions on Indonesia's trade and investment. Asian Economic Papers, 18(3), 95-112.
• Jiming, H.; Posen, A. S. (2019). Economic truths towards resolving China-US trade conflict. Peterson Institute for International Economics (PIIE) Briefings, (No.19-1)
• Jung, Y. S.; Park, Y. (2024). Winners and losers in US-China trade disputes: A dynamic compositional analysis of foreign direct investment. Social Science Quarterly, 105(4), 980-995.
• Kwiatkowski, D.; Phillips, P. C.; Schmidt, P.; Shin, Y. (1992). Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root? Journal of Econometrics, 54(1-3), 159-178.
• Lemmer, W. (2019). SA feeling the impact of US-China trade war. Farmer’s Weekly, 2019(19032), 25-25.
• Lin, J. Y. (2020). China’s economic outlook against the backdrop of the COVID-19 pandemic and US-China tensions. Journal of Chinese Economic and Business Studies, 18(4), 327-331.
• Mohsin, Z.; Munshi, U.; Iftikhar, M.; Yousaf, M. N. (2024). The new cold war: US-China tensions and the reshaping of the global order. Shnakhat, 3(3), 154-163.
• Moosa, N.; Ramiah, V.; Pham, H.; Watson, A. (2020). The origin of the US-China trade war. Applied Economics, 52(35), 3842-3857.
• Narayan, P. K. (2005). The saving and investment nexus for China: Evidence from cointegration tests. Applied Economics, 37(17), 1979-1990.
• Narayan, P.; Smyth, R. (2005). Trade liberalization and economic growth in Fiji. An empirical assessment using the ARDL approach. Journal of the Asia Pacific Economy, 10(1), 96-115.
• Özçelik, O. (2022). Ekonomi ve dış ticaret politikalarındaki belirsizliğinin ABD-Çin dış ticaret dengesine etkileri: Fourier ADF ve genişletilmiş ARDL ile bir analiz. Fiscaoeconomia, 6(3), 1071- 1102.
• Ozdagli, A. K.; Wang, J. (2022). Uncertainty, shock prices and debt structure: Evidence from the US-China trade war. FRB of Dallas Working Paper Series, (No. 2212).
• Öztürk, S.; Altınöz, B. (2019). The effect of US-China trade wars on Shanghai Stock Exchange Composite Index. Afyon Kocatepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 21(1), 59-69.
• Perron, P. (1989). The great crash, the oil price shock, and the unit root hypothesis. Econometrica, 57(6), 1361-1401.
• Pesaran, M. H.; Shin, Y. (1995). An autoregressive distributed lag modelling approach to cointegration analysis. Cambridge Working Papers in Economics, (No.9514).
• Pesaran, M. H.; Shin, Y.; Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326.
• Rogers, J. H.; Sun, B.; Sun, T. (2024). U.S.-China tension. Available at SSRN: https://ssrn.com/abstract=4815838 or http://dx.doi.org/10.2139/ssrn.4815838.
• Sabala, E.; Devadoss, S. (2019). Impacts of Chinese Tariff on World Soybean Markets. Journal of Agriculture and Resource Economics, 44(2), 291-310.
• Setiawan, B. (2020). Does US-China trade war matter on ASEAN stock market: Event-study approach. Sriwijaya International Journal of Dynamic Economics and Business, 4(3), 161-174.
• Steinbock, D. (2018). US-China trade war and its global impacts. China Quarterly of International Strategic Studies, 4(4), 515-542.
• Sun, H. (2019). US-China tech war: Impacts and prospects. China Quarterly of International Strategic Studies, 5(2), 197-212.
• Tokatlı, S. G. (2023). Tukidides tuzağı çerçevesinde ABD-Çin rekabetinin analizi: Teorik bir değerlendirme. Akademik Hassasiyetler, 10(21), 459-481.
• Turkish Statistical Institute. (2024). Foreign trade statistics, Access date: 15.10.2024, Access address: https://data.tuik.gov.tr/Kategori/GetKategori?p=dis-ticaret-104&dil=1
• Wang, X.; Wang, X.; Zhong, Z.; Yao, J. (2021). The impact of US-China trade war on Chinese firms: Evidence from stock market reactions. Applied Economics Letters, 28(7), 579-583.
• Wang, Z.; Tang, L.; Cao, C.; Zhou, Z. (2023). The impact of US-China tensions on people mobility. China Review, 23(4), 159-195.
• Yean, T. S.; Yi, A. K. J.; Ann, T. B. (2019). US-China trade war: Potential trade and investment spill-over into Malaysia. Iseas Yusof Ishak Institute Economics Working Paper, (No.2019-03).
• Yefremov, D. (2018). China in the trade war against the US: Tactical capabilities and prospects. Chinese Studies, 2, 133-141.
• Zeng, K.; Wells, R.; Gu, J.; Wilkins, A. (2022). Bilateral tensions, the trade war, and US-China trade relations. Business and Politics, 24(4), 399-429.
• Zhang, J.; Liu, H. (2024). Analysis of co-movement in Asia-Pacific stock markets against the background of the US-China trade war. Economic Issues, 29(1), 35-69.