ON THE BRINK OF A NEW WORLD ORDER: TURKISH CAPITAL MARKETS FACING ASYMMETRIC SHOCKS OF UNCERTAINTY FACTORS

Öz

The economic and political instabilities have made the impact of uncertainties in capital markets more salient, and affected investors' decisions since the pandemic period. Turkish capital markets have been operating under the pressure of various uncertainties stemming from both domestic and foreign political or economic dynamics as well. Hence, it is quite crucial for policymakers and investors to reveal the effects of increasing uncertainties on the markets during this global transformation process in order to take the right steps in such an environment. In accordance with the aim of this study, the asymmetric effects of 10-year government bond yields, uncertainties in gold (ounce) and Brent crude oil prices besides the geopolitical uncertainty index (GPR), trade policy uncertainty index (TPU) and climate policy uncertainty index (CPU) on selected stock market indices are investigated by the Nonlinear Autoregressive Distributed Lag (NARDL) model for the 2015-2025 period. According to the findings, the selected uncertainty factors have asymmetric effects on stock market indices in different directions and to different magnitude. The findings are expected to provide not only a meaningful contribution to the existing literature but also provide a framework for the position of the Turkish stock markets during the transformation process.

Anahtar Kelimeler

• Global uncertainty factors
• financial markets
• asymmetric shocks
• Borsa Istanbul
• NARDL

Destekleyen Kurum

This is the revised and edited version of the paper presented at the IERFM2025 Conference.

Etik Beyan

This study did not involve research requiring an ethics statement.

Teşekkür

I would like to thank the editors and reviewers in advance for their contributions.

Yeni Bir Dünya Düzeninin Eşiğinde: Belirsizlik Faktörlerinin Asimetrik Şokları Karşısında Türk Sermaye Piyasaları

Öz

Dünyada özellikle pandemi döneminden itibaren yaşanan ekonomik ve politik istikrarsızlıklar sermaye piyasalarında da belirsizliklerin etkisini belirginleştirmekte ve yatırımcıların kararlarını etkilemektedir. Türk sermaye piyasaları ise son yıllarda hem kendi iç dinamikleri hem de yabancı politik veya ekonomik dinamiklerle bağlantılı birçok belirsizlik karşısında faaliyet göstermektedir. Dolayısıyla dünyadaki yeni dönüşüm sürecinde artan belirsizliklerin piyasalar üzerindeki etkilerinin ortaya koyulabilmesi, hem politika yapıcılar hem de yatırımcılar için böyle bir ortamda doğru adımların atılabilmesi açısından oldukça önemlidir. Bu amaç doğrultusunda, 10 yıllık tahvil faiz oranları, ons altın ve brent petrol fiyatlarındaki belirsizliklerin yanı sıra, jeopolitik belirsizlik endeksi (GPR), ticari politika belirsizlik endeksi (TPU) ve iklim politikası belirsizlik endeksi (CPU) verilerinin seçilmiş borsa endeksleri üzerine asimetrik etkileri 2015-2025 dönemi için doğrusal olmayan gecikmesi dağılmış otoregresif (NARDL) model ile incelenmiştir. Bulgulara göre, seçilen belirsizlik unsurlarının borsa endeksleri üzerinde farklı yön ve ölçüde asimetrik etkileri bulunmaktadır. Elde edilen bulguların literatür için anlamlı katkılar sağlamasının yanında, Türkiye borsalarının dönüşüm süreci içerisindeki duruşu açısından da bir çerçeve sunabilmesi beklenmektedir.

Anahtar Kelimeler

• Küresel belirsizlik unsurları
• finansal piyasalar
• asimetrik şoklar
• Borsa İstanbul
• NARDL

Destekleyen Kurum

IERFM2025 Kongresinde sunulan bildirinin gözden geçirilmiş ve düzenlenmiş halidir.

Etik Beyan

Bu çalışmada etik beyan gerektiren bir araştırma yürütülmemiştir.

Teşekkür

Sayın editör ve hakemlere katkıları için şimdiden teşekkür ederim.

Kaynakça

1. Banerjee, A.K., Sensoy, A. and Goodell, J.W. (2024). Volatility connectedness between geopolitical risk and financial markets: Insights from pandemic and military crisis periods, International Review of Economics & Finance, 96(C), 103740.
2. Black, F. (1976). Studies of stock price volatility changes. Proceedings of the 1976 Meetings of the Business and Economic Statistics Section, American Statistical Association, 177-181.
3. Bloom, N. (2009). The impact of uncertainty shocks. Econometrica, 77(3), 623–685.
4. Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity, Journal of Econometrics, 31(3), 307-327.
5. Camgöz, M. (2022). Global belirsizlik faktörlerinin BIST hisse senedi fiyatlarına asimetrik etkilerinin NARDL modeliyle analizi, Maliye ve Finans Yazıları, 36(118), 71-100.
6. Christie, A.A. (1982). The stochastic behavior of common stock variances: Value, leverage, and interest rate effects, Journal of Financial Economics, 10: 407-432.
7. Climate Policy Uncertainty Index, https://www.policyuncertainty.com/climate_uncertainty.html, Accessed: 20.04.2025.
8. Doğru, E. (2024). Belirsizliklerin finansal piyasalara simetrik ve asimetrik etkisi: BIST ulaştırma endeksi üzerine bir araştırma, Journal of Transportation and Logistics, 9(1), 97-111.

9. Duffee, G.R. (1995). Stock returns and volatility: A firm-level analysis, Journal of Financial Economics, 37, 399-420.
10. Erdoğan, L., Ceylan, R., & Abdul-Rahman, M. (2022). The impact of domestic and global risk factors on Turkish stock market: Evidence from the NARDL approach. Emerging Markets Finance and Trade, 58(7), 1961–1974.
11. Historical Geopolitical Risk Index, https://www.matteoiacoviello.com/gpr.htm, Accessed: 20.03.2025.
12. Investing.com, Dünya ve Sektör Endeksleri, https://tr.investing.com/indices/world-indices, Accessed: 20.03.2025.
13. Iqbal, N., Bouri, E., Shahzad, S.J.H. & Alsagr, N. (2024). Asymmetric impacts of Chinese climate policy uncertainty on Chinese asset prices. Energy Economics, 133, 107518.
14. Kapetanios, G., Shin, Y., & Snell, A. (2003). Testing for a unit root in the nonlinear STAR framework. Journal of econometrics, 112(2), 359-379.
15. Li, C., Lin, S., Sun, Y., Afshan, S. And Yaqoob, T. (2022). The asymmetric effect of oil price, news-based uncertainty, and COVID-19 pandemic on equity market, Resources Policy, 77, 102740.
16. Long, S., Pei, H., Tian, H. & Lang, K. (2021). Can both Bitcoin and gold serve as safe-haven assets? — A comparative analysis based on the NARDL model, International Review of Financial Analysis, 78, 101914.
17. Mora, A. & Sethapramote, Y. (2019). Spillover effects of global financial uncertainty and economic policy uncertainty on stock exchange of Thailand. Chiang Mai University Journal of Economics, 23(2), 1-26.
18. Nalban, V. & Smădu, A. (2021). Asymmetric effects of uncertainty shocks: Normal times and financial disruptions are different. Journal of Macroeconomics, 69, 103331.
19. Özbay, D. (2022). COVID-19 pandemi döneminde artan belirsizlik ortamı ve kilit denetim konuları açıklamaları üzerindeki etkisi: BİST 100 şirketleri incelemesi. Muhasebe Enstitüsü Dergisi, 66, 49-63.
20. Özyeşil, M. (2020). Investigation of the relationship between economic and political uncertainty and general economic outlook: An econometric analysis on Athens Stock Exchange. Adam Academy Journal of Social Sciences, 10(1), 73-104.
21. Pei, B. (2022). Does economic policy uncertainty affect the correlation between stock price and rmb exchange rate?: Analysis based on DCC-MGARCH and TVP-SV-VAR models, Journal of Global Economy, Business and Finance (JGEBF), 4(4), 15-20.
22. 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.
23. Phillips, P.C. B and Perron, P. (1988). Testing for a unit root in time series regression, Biometrika, 75(2), 335 346.
24. Punwong, S., Kaewsompong, N. & Tansuchat, R. (2021). Impact of economic policy uncertainty on the stock exchange of Thailand: Evidence from the industry-level stock returns in Thailand. In: Sriboonchitta, S., Kreinovich, V., Yamaka, W. (eds) Behavioral Predictive Modeling in Economics. Studies in Computational Intelligence, vol 897. Springer, Cham, pp.393-406.
25. Said, S.E., & Dickey, D.A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599-607.
26. Saka Ilgın, K., (2024). Analysis of the impact of climate policy and energy uncertainties on the stock exchange: The case of Turkiye and America. PressAcademia Procedia (PAP), 20: 34-40.
27. Schwert, G.W. (1989). Business cycles, financial crises, and stock volatility, NBER Working Paper Series, Working Paper No: 2957.
28. Seçme, Z.O. (2024). Global belirsizlik faktörleri ile BİST sektör endeksleri arasındaki kısa ve uzun dönem ilişkisi, BMIJ, 12(1), 93-115.
29. Shiblu, K.A. & Kayser, M.S. (2023). Ballot boxes and stock market: The influence of parliamentary election uncertainty on Dhaka Stock Exchange (DSE) returns, volatility, and trading volume. Jahangirnagar University Journal of Business Research (JUJBR), 23: 93-110.
30. Shin, Y., Yu, B. and Greenwood-Nimmo, M. (2013). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework, Festschrift in Honor of Peter Schmidt, W.C. Horrace and R.C. Sickles, eds., Forthcoming, http://dx.doi.org/10.2139/ssrn.1807745, Accessed: 22.05.2025.
31. Simran and Sharma, A.K. (2023). Asymmetric impact of economic policy uncertainty on cryptocurrency market: Evidence from NARDL approach. The Journal of Economic Asymmetries, 27: e00298.
32. Sulehri, F.A. & Ali, A. (2020). Impact of political uncertainty on Pakistan Stock Exchange (1990-1999), an event study approach, MPRA Paper, No: 104623, University Library of Munich, Germany.
33. Syed, A., Fatima, K., & Zaheer, M. (2022). The impact of COVID-19 on stock market and exchange rate uncertainty in Pakistan. Business Review, 16(2), 96-108.
34. Veronesi, P. (1999). Stock market overreaction to bad news in good times: A rational expectations equilibrium model. The Review of Financial Studies, 12(5), 975–1007.
35. Wafi, F.M. & Merlinda, S. (2023). An empirical study on effect of macroeconomic and United States economic policy uncertainty on Jakarta Islamic Index movement in the Indonesian Islamic capital market. Al-Amwal: Jurnal Ekonomi dan Perbankan Syariah, 15: 139-158.
36. Zanjani, M.S. & Mehregan, N. (2018). asymmetric effect of exchange rate risk on the stock index of export-oriented industries using the NARDL model, JEMR, 9 (33) :89-116.
37. Zivot, E. & Andrews, W.K. (1992). Further evidence on the great crash, the oil-price shock, and the unit root hypothesis. Journal of Business and Economic Statistics, 10(3), 251-270.