Küresel Tedarik Zinciri Şokları ve Ticaretle İlişkili Finansal Piyasa Tepkileri

Year 2025, Volume: 28 Issue: 2, 659 - 671, 30.11.2025

Ayça Pekmez Bahçeci , Mehmet Pekmezci , Burak Büyükoğlu

Abstract

Küresel tedarik ağları, ticaret politikalarındaki değişiklikler, lojistik darboğazlar, pandemiler ve jeopolitik çatışmalar sonucunda krizlere karşı daha savunmasız hale gelmektedir. Bu şoklar lojistik ve üretime olumsuz etkilerinin yanı sıra finansal piyasalardaki dalgalanmayı ciddi oranda artırmaktadır. Bu çalışma, küresel tedarik zinciri şoklarının borsa tepkilerini nasıl etkilediğini, özellikle karmaşık tedarik zinciri ağlarına önemli ölçüde bağımlı olan sektörlere odaklanarak araştırmaktadır. Çalışmanın veri seti 2020-2024 yılları arasındaki Amerikan Borsası hisse senedi getirileri baz alınarak oluşturulmuştur. Bu veri seti ayrıca COVID-19 kilitlenmeleri, yarı iletken kıtlığı, Rusya-Ukrayna savaşı ve Kızıldeniz güvenlik krizi gibi durumlar için olay kuklalarının yanı sıra VIX endeksi, Baltık Kuru Yük Endeksi ve Brent petrolünün fiyatı gibi sürekli göstergeleri de içermektedir. Araştırmada, Makine öğrenmesi modellerinden Karar Ağacı, Rastgele Orman ve XGBoost yöntemleri karşılaştırmalı olarak kullanılmıştır. Elde edilen bulgulara göre; tedarik zinciri şokları, hisse senedi getirilerini önemli ölçüde düşürmekte; petrol fiyatları, ticaret endeksleri ve finansal oynaklık en alakalı itici güçler olmaktadır. Ayrıca, tedarik zinciri kesintilerinin, operasyonel verimsizliklerin ötesine geçerek, ticaret bağlantılı finans piyasalarının dinamikleri üzerinde doğrudan bir etkiye sahip olduğu sonucuna varılmıştır.

Keywords

Küresel Tedarik Zinciri Şokları , Borsa Getirileri , Makine Öğrenmesi , Uluslararası Ticaret

Global Supply Chain Shocks and Trade-Linked Financial Market Responses

Abstract

Global supply networks have become increasingly vulnerable to crises due to shifts in trade policies, logistical bottlenecks, pandemics, and geopolitical conflicts. These shocks not only negatively affect logistics and production but also significantly amplify volatility in financial markets. This study investigates how global supply chain shocks influence stock market responses, with a particular focus on sectors that are heavily reliant on complex supply chain networks. The dataset is constructed based on U.S. stock market returns between 2020 and 2024. It also incorporates event dummies for key disruptions such as COVID-19 lockdowns, the semiconductor shortage, the Russia–Ukraine war, and the Red Sea security crisis, along with continuous indicators including the VIX index, the Baltic Dry Index, and Brent crude oil prices. In the analysis, machine learning models—namely Decision Trees, Random Forest, and XGBoost—are employed and compared. The findings reveal that supply chain shocks significantly reduce stock returns, with oil prices, trade indices, and financial volatility emerging as the most relevant driving factors. Moreover, the results indicate that supply chain disruptions have a direct impact on the dynamics of trade-related financial markets, extending beyond mere operational inefficiencies.

Keywords

Global Supply Chain Shocks , Stock Returns , Machine Learning , International Trade

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