SavedAdd your journal

Journals / Uluslararası Ekonomi İşletme ve Politika Dergisi / 2026 / Cilt: 10 Sayı: 2

Financial Contagion in Crisis Periods: The Tourism Sector’s Vulnerability in Turkish Capital Markets

Kriz Dönemlerinde Finansal Bulaşıcılık: Türk Sermaye Piyasalarında Turizm Sektörünün Kırılganlığı

Yalçın Yalman(SİVAS CUMHURİYET ÜNİVERSİTESİ)0000-0002-4340-7068
Tuba Sarikaya Kara(SİVAS CUMHURİYET ÜNİVERSİTESİ, CUMHURİYET SOSYAL BİLİMLER MESLEK YÜKSEKOKULU)0000-0003-1853-2198
Bahri Fatih Tekin(SİVAS CUMHURİYET ÜNİVERSİTESİ, CUMHURİYET SOSYAL BİLİMLER MESLEK YÜKSEKOKULU)0000-0002-0541-4371
Pages
744–769
Publication Date
2026-10-01
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Dynamic results show that major shocks-such as the 2016 coup attempt, the 2018 currency crisis, the 2020 pandemic, and the 2023 earthquakes-push the Total Connectedness Index (TCI) to levels around or above 80%.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study analyzes the return connectedness among 7 Borsa İstanbul sector indices (tourism, services, trade, transportation, financials, technology, and sustainability) using the Quantile VAR (QVAR) model over the period from November 6, 2014, to February 4, 2025.
📊
Key Findings & Data:The static analyses conducted with daily data reveal that total connectedness rises to 82.71%–82.50% under extreme market conditions (lower and upper quantiles), representing a substantial increase compared to the 68.32% observed under normal conditions.
💡
Conclusion & Impact:Dynamic results show that major shocks-such as the 2016 coup attempt, the 2018 currency crisis, the 2020 pandemic, and the 2023 earthquakes-push the Total Connectedness Index (TCI) to levels around or above 80%.
🔬Design:Modeling & Simulation
📍Scope:2014 Verileri
⚙️Variables:BİST Turizm Endeksi · Finansal Bulaşıcılık · Kantil VAR (QVAR)

Abstract

This study analyzes the return connectedness among 7 Borsa İstanbul sector indices (tourism, services, trade, transportation, financials, technology, and sustainability) using the Quantile VAR (QVAR) model over the period from November 6, 2014, to February 4, 2025. The static analyses conducted with daily data reveal that total connectedness rises to 82.71%–82.50% under extreme market conditions (lower and upper quantiles), representing a substantial increase compared to the 68.32% observed under normal conditions. Dynamic results show that major shocks-such as the 2016 coup attempt, the 2018 currency crisis, the 2020 pandemic, and the 2023 earthquakes-push the Total Connectedness Index (TCI) to levels around or above 80%. The Tourism index (XTRZM) consistently acts as a net shock receiver across all regimes, whereas the Sustainability index (XUSRD) remains a net shock transmitter. The Services index (XUHIZ) functions as a net transmitter in normal and bearish markets, while the Financials index (XUMAL) plays this role in bullish markets. Dynamic analyses at different quantile levels further indicate that total connectedness is 20–30% higher in extreme quantiles than at the median and that the net directional roles of sectors can reverse depending on the quantile. The study demonstrates that, in the Turkish market, risks spilling over to the tourism sector are primarily fed by the services and sustainability sectors across different quantile regimes, thereby revealing the critical role of domestic shocks in inter-sectoral risk transmission.

Özet

Bu çalışma, Borsa İstanbul’un 7 sektör endeksi (turizm, hizmetler, ticaret, ulaştırma, mali, teknoloji, sürdürülebilirlik) arasındaki getiri bağlantılılığını Kantil VAR (QVAR) modeli ile 06/11/2014-04/02/2025 tarihleri arasında analiz etmektedir. Günlük verilerle yürütülen statik analizler, olağandışı piyasa koşullarında (düşen/yükselen kantiller) toplam bağlantılılığın %82.71–%82.50 seviyesine yükseldiğini, normal koşullardaki %68.32’ye kıyasla belirgin artış gösterdiğini ortaya koymaktadır. Dinamik bulgular, 2016 darbe girişimi, 2018 kur krizi, 2020 pandemisi, 2023 depremleri gibi şokların TCI’yi %80’lere taşıdığını ortaya koymaktadır. Turizm endeksi (XTRZM) tüm rejimlerde net şok alıcısı, sürdürülebilirlik endeksi (XUSRD) ise net yayıcı konumundadır. Hizmetler (XUHIZ) normal ve düşen piyasalarda, mali (XUMAL) yükselen piyasalarda net şok yayıcısıdır. Farklı kantil düzeylerinde dinamik analiz, uç kantillerde bağlantılılığın medyana göre %20–30 daha yüksek olduğunu ve net rollerin kantil bazında tersine dönebildiğini göstermektedir. Çalışma, Türkiye piyasasında turizm sektörüne yayılan risklerin hizmet ve sürdürülebilirlik sektörlerinden beslendiğini farklı kantil düzeylerinde ortaya koyarak, yerel şokların sektörler arası risk aktarımındaki rolünü ortaya çıkarmaktadır.

🔖

Cite This Article

Yalman, Y., Kara, T. S., Tekin, B. F. (2026). Financial Contagion in Crisis Periods: The Tourism Sector’s Vulnerability in Turkish Capital Markets. Uluslararası Ekonomi İşletme ve Politika Dergisi, Cilt: 10 Sayı: 2, 744–769. https://doi.org/10.29216/ueip.1886921

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (54)

  1. Aharon, D. Y., Demir, E., & Ersan, O. (2024). Where do tourism tokens travel to and from?. Current Issues in Tourism, 27(16), 2561–2583. https://doi.org/10.1080/13683500.2023.2237169
  2. Alola, U. V., Cop, S., & Alola, A. A. (2019). The spillover effects of tourism receipts, political risk, real exchange rate, and trade indicators in Turkey. International Journal of Tourism Research, 21(6), 813–823. https://doi.org/10.1002/jtr.2307
  3. Ando, T., Greenwood-Nimmo, M., & Shin, Y. (2018, April 18). Quantile connectedness: Modelling tail behaviour in the topology of financial networks. SSRN. https://dx.doi.org/10.2139/ssrn.3164772
  4. Anscombe, F.J., Glynn, W.J., 1983. Distribution of the kurtosis statistic B2 for normalsamples. Biometrika 70 (1), 227–234.
  5. 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), 1–23. https://doi.org/10.3390/jrfm13040084
  6. Baker, S. R., Bloom, N., Davis, S. J., Kost, K., Sammon, M., & 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
  7. Baruník, J., & 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
  8. Bezirgan, E. (2024). BIST turizm endeksi ve BIST ulaştırma endeksi arasındaki nedensellik ilişkisi: VAR model–Toda Yamamoto yaklaşımı. İşletme Araştırmaları Dergisi, 17(1), 45–55. https://doi.org/10.20491/isarder.2025.1957
  9. 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, s. 1-14.
  10. Chatziantoniou, I., Gabauer, D., & Stenfors, A. (2021). Interest rate swaps and the transmission mechanism of monetary policy: A quantile connectedness approach. Economics Letters, 204, 109891.
  11. D’Agostino, R.B., 1970. Transformation to normality of the null distribution of g1.Biometrika 679–681.
  12. Demirel, S. (2024). İsrail–Hamas savaşının Orta Doğu borsalarına etkisinin olay çalışması metodolojisi ile incelenmesi. Business & Management Studies: An International Journal (BMİJ), 12(1), 116–131. https://doi.org/10.15295/bmij.v12i1.2350
  13. Demirkale, Ö., & Can, E. N. (2021). Makroekonomik değişkenlerin BIST turizm endeksi üzerindeki etkisinin incelenmesi. Sakarya Üniversitesi İşletme Enstitüsü Dergisi, 3(1), 175–180. https://doi.org/10.47542/sauied.906256
  14. Dickey, D. A., & Fuller, W. A. (1981). Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica, 49, 1057–1072.
  15. Diebold, F. X., & Yilmaz, K. (2009). Measuring financial asset return and volatility spillovers, with application to global equity markets. The Economic Journal, 119(534), s. 158-171.
  16. Diebold, F. X., & Yilmaz, K. (2012). Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of forecasting, 28(1), s. 57-66.
  17. 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. https://doi.org/10.1016/j.ijforecast.2011.02.006
  18. Diebold, F. X., & Yilmaz, K. (2014). On the network topology of variance decompositions: Measuring the connectedness of financial firms. Journal of Econometrics, 182(1), s. 119-134.
  19. Dündar, T., & Beyzatlar, M. A. (2021). Hava taşımacılığı ve kentleşme: Türkiye ve Avrupa’nın en kalabalık dört ülkesindeki bağlantılılık bulguları. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 23(Özel Sayı), 231–248. https://doi.org/10.16953/deusosbil.1055653
  20. Dwumfour, R. A., Pan, L., & Nsafoah, D. (2025). Dynamic spillovers and portfolio optimization in tourism, fintech, and cryptocurrency (MPRA Paper No. 124157). Munich Personal RePEc Archive. https://mpra.ub.uni-muenchen.de/124157/
  21. Ekinci, R., & Gençyürek, A. G. (2021). Dynamic connectedness between sector indices: Evidence from Borsa Istanbul. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 16(2), 512–534. https://doi.org/10.17153/oguiibf.879784
  22. El Rifai, O., Ozatac, N., & Taspinar, N. (2023). Volatility spillovers among major tourism stock indices during COVID-19 pandemic. Current Issues in Tourism, 26(13), 2075–2082. https://doi.org/10.1080/13683500.2022.2153015
  23. Elliott, G., Rothenberg, T.J., Stock, J.H., 1996. Efficient tests for an autoregressive unit root. Econometrica 64 (4), 813–836.
  24. Eyüboğlu, S., & Eyüboğlu, K. (2018). Hizmet güven endeksi ile hizmet sektörü alt endeksleri arasındaki ilişkinin test edilmesi. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 20(2), 271–282.
  25. Fisher, T.J., Gallagher, C.M., 2012. New weighted Portmanteau statistics for time series goodness of fit testing. J. Am. Stat. Assoc., 107 (498), 777–787.
  26. 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. Gabauer, D., 2022. Package ‘ConnectednessApproach’. R Package Version 1.0
  27. Gemici, E. (2020). Gelişmekte olan piyasalarda finansal bağlantılılık. OPUS International Journal of Society Researches, 16(30), 3134–3160. https://doi.org/10.26466/opus.778653
  28. Gökmen, O., & Çömlekçi, İ. (2018). Turizm endeksleri arasındaki eşbütünleşme ilişkisi. Seyahat ve Otel İşletmeciliği Dergisi, 15(2), 273–286. https://doi.org/10.24010/soid.453157
  29. Hacıevliyagil, N., & Gümüş, A. (2020). COVID-19 salgın hastalığının borsaya etkisi: Turizm ve ulaştırma endeksleri üzerine bir uygulama. Akademik Yaklaşımlar Dergisi, 11(1), 76–97.
  30. Hadi, D. M., Naeem, M. A., & Karim, S. (2022). Impact of COVID-19 on the connectedness across global hospitality stocks. International Journal of Hospitality Management, 104, 103243. https://doi.org/10.1016/j.ijhm.2022.103243
  31. Hu, Y., Lang, C., Corbet, S., & Wang, J. (2024). The impact of COVID-19 on the volatility connectedness of the Chinese tourism sector. Research in International Business and Finance, 68, 102192. https://doi.org/10.1016/j.ribaf.2023.102192
  32. Jarque, C.M., Bera, A.K., 1980. Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Econom. Lett. 6 (3), 255–259.
  33. Koop, G., Pesaran, H. M., & Potter, S. M. (1996). Impulse response analysis in nonlinear multivariate models. Journal of econometrics, 74(1), s. 119-147.
  34. Kumar, D. (2023). Nexus between travel & leisure stocks and uncertainties: An extreme risk spillover analysis. American Business Review, 26(1), 245–268. https://doi.org/10.37625/abr.26.1.245-268
  35. Kutlu, M., & Karakaya, A. (2019). Borsa Istanbul tourism index volatility: Markov regime switching ARCH model. Yaşar Üniversitesi E-Dergisi, 14, 18–24.
  36. Mitra, S. K., Chattopadhyay, M., & Jana, R. K. (2019). Spillover analysis of tourist movements within Europe. Annals of Tourism Research, 79, 102754. https://doi.org/10.1016/j.annals.2019.102754
  37. Naeem, M. A., Arfaoui, N., Karim, S., & Lim, W. M. (2024). Tourism market in turbulent times: Evidence of asymmetric connectedness. Current Issues in Tourism, 27(23), 4104–4133. https://doi.org/10.1080/13683500.2023.2274904
  38. Nahiduzzaman, M., Shabbir, R., Kuri, B. C., Dhar, B. K., & Roy, A. (2025). Financial volatility spillovers and risk dynamics in global tourism: Evidence from equity and bond markets. Thunderbird International Business Review, 1–70. https://doi.org/10.1002/tie.70031
  39. Nazlıoğlu, E. H. (2022). Turizm endeksleri ve döviz kuru ilişkisi: Türkiye için ampirik analiz. In N. Biray (Ed.), Uluslararası Türk Dünyası Turizm, Ekonomi ve Kültürel Miras Sempozyumu: Bildiri Kitabı (ss: 200–211). Pamukkale Üniversitesi Yayınları. https://gcris.pau.edu.tr/entities/publication/1e7ff595-51c2-4c8f-8a01-5e7251b7f0fb
  40. Pesaran, H. H., & Shin, Y. (1998). Generalized impulse response analysis in linear multivariate models. Economics letters, 58(1), 17-29.
  41. Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75, 335–346.
  42. Shahzad, S. J. H., Bouri, E., & Ferrer, R. (2023). Default risk transmission in the travel and leisure industry. International Journal of Hospitality Management, 113, 103525. https://doi.org/10.1016/j.ijhm.2023.103525
  43. Şahin, E., Konak, F., & Karaca, S. S. (2017). Türkiye ve Rusya arasındaki “uçak krizi”nin Borsa İstanbul gıda, içecek ve turizm endeksleri üzerine etkisi. Business and Economics Research Journal, 8(3), 473–485. https://doi.org/10.20409/berj.2017.61
  44. Tayar, T., Gümüştekin, E., Dayan, K., & Mandi, E. (2020). COVID-19 krizinin Türkiye’deki sektörler üzerindeki etkileri: Borsa İstanbul sektör endeksleri araştırması. Yüzüncü Yıl Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (Salgın Hastalıklar Özel Sayısı), 293–320.
  45. Uçar, İ. H., & Alsu, E. (2025). The impact of COVID-19 pandemic on the tourism and transportation sectors: Evidence from Borsa Istanbul. Ekonomi Maliye İşletme Dergisi, 8(1), 91–111. https://doi.org/10.46737/emid.1560605
  46. Vurur, N. S., & Özdemir, L. (2023). Küresel ve Türkiye jeopolitik risklerin BIST turizm endeksine etkisinin karşılaştırılması. Uluslararası İktisadi ve İdari İncelemeler Dergisi (C-iasoS 2022 Özel Sayısı), 163–174. https://doi.org/10.18092/ulikidince.1224580
  47. Yamak, N., Kolcu, F., & Köyel, F. (2018). Asymmetric relationship between exchange rate volatility and stock market index volatility. Balkan Journal of Social Sciences, 7(14), 171–187.
  48. Yaman, S., & Korkmaz, T. (2020). Döviz kurları ile BİST turizm endeksi getirileri arasındaki volatilite yayılım etkisinin belirlenmesi. Business and Economics Research Journal, 11(3), 681–702. https://doi.org/10.20409/berj.2020.277
  49. Yıldırım, S., Ögel, S., & Alhajrabee, O. (2020). Makroekonomik değişkenlerin BİST turizm endeks getirileri üzerindeki etkilerinin incelenmesi. Sakarya Üniversitesi İktisat Dergisi, 9(2), 103–121.
  50. Yousaf, I., Abrar, A., & Goodell, J. W. (2023). Connectedness between travel & tourism tokens, tourism equity, and other assets. Finance Research Letters, 53, 103595. https://doi.org/10.1016/j.frl.2022.103595
  51. Yousaf, I., Zeitun, R., Ali, S., & Palma, A. (2024). Impact of tokenization on financial investments: Exploring connectedness through the case of transport and travel/tourism sectors. Finance Research Letters, 62, 105221. https://doi.org/10.1016/j.frl.2024.105221
  52. Zeng, H., Abedin, M. Z., Ahmed, A. D., & Huang, Q. (2025). Extreme risk connection among the European tourism, energy and carbon emission markets. Research in International Business and Finance, 74, 102693. https://doi.org/10.1016/j.ribaf.2024.102693
  53. Zhang, D., Hu, M., & Ji, Q. (2020a). Financial markets under the global pandemic of COVID-19. Finance Research Letters, 36, 101528. https://doi.org/10.1016/j.frl.2020.101528
  54. Zhang, W., Zhuang, X., Wang, J., & Lu, Y. (2020b). Connectedness and systemic risk spillovers analysis of Chinese sectors based on tail risk network. The North American Journal of Economics and Finance, 54, 101248. https://doi.org/10.1016/j.najef.2020.101248