Türk Bankalarının Dinamik Performansına Tensör TOPSIS Yaklaşımı: LOPCOW–TOPSIS Odaklı Hibrit Bir Model

Abstract

Bu çalışma, 23 Türk bankasının 2002–2024 dönemindeki dinamik finansal performansını hibrit bir LOPCOW–TOPSIS–Tensör TOPSIS modeliyle değerlendirmektedir. Yöntem; CAMELS uyumlu yedi ana kriter altındaki 46 finansal rasyonun LOPCOW ile ağırlıklandırılması, grup içi TOPSIS ile her banka‑yıl için yedi ana kriter skorunun üretilmesi ve Tensör TOPSIS ile 23 yıllık panelden trend, ortalama ve standart sapma özniteliklerinin çıkarılarak nihai dinamik sıralamanın elde edilmesi olmak üzere üç aşamadan oluşmaktadır. Modelin sağlamlığı Borda sayımı ile test edilmiştir. Bulgular, aktif kalitesi ve bilanço yapısının en belirleyici boyutlar olduğunu, sermaye yeterliliğinin ise en düşük ağırlığa sahip olduğunu göstermiştir. Yabancı sermayeli uzmanlaşmış bankalar (Deutsche Bank, Citibank), ilk iki sırada yer alırken bunları özel (Akbank, QNB) ve kamu bankaları (T.C. Ziraat Bankası) izlemiştir. Kamu bankalarının kriz dönemlerinde performansının iyileşmesi, devlet bankalarının konjonktür karşıtı rolüne ilişkin uluslararası bulgularla örtüşmektedir. Tensör TOPSIS ile Borda sıralamaları arasındaki yüksek Spearman korelasyonu modelin güvenilirliğini teyit etmektedir. Düzenleyici otoriteler, önerilen dinamik çerçeveyi yapısal riskleri izlemek, performans düzeyini ve zamansal istikrarı dikkate alan erken uyarı sistemleri tasarlamak için kullanabilmektedir.

Keywords

• Dinamik Performans Değerlendirmesi
• Bankacılık
• Tensör TOPSIS
• LOPCOW

Tensor TOPSIS Approach to Dynamic Performance of Turkish Banks: A LOPCOW–TOPSIS-Driven Hybrid Model

Abstract

This study evaluates the dynamic financial performance of 23 Turkish banks over the 2002–2024 period using a hybrid LOPCOW–TOPSIS–Tensor TOPSIS model. The methodology comprises three stages: (1) 46 financial ratios under seven CAMELS‑aligned main criteria are objectively weighted using LOPCOW; (2) within‑group TOPSIS generates seven main criterion scores for each bank‑year; (3) Tensor TOPSIS extracts trend, mean, and standard deviation from the 23‑year panel to produce a final dynamic ranking. Robustness is tested via Borda count. Results show that Asset Quality and Balance Sheet Structure are the most differentiating dimensions, while Capital Adequacy has the lowest weight. Foreign‑owned niche banks (Deutsche Bank, Citibank) rank first and second, followed by private (Akbank, QNB) and state‑owned banks (T.C. Ziraat Bank). Public banks improve their relative performance during crisis periods, consistent with international evidence on the counter‑cyclical role of state‑owned banks. The high Spearman correlation between Tensor TOPSIS and Borda rankings confirms model robustness. Regulators can use the proposed dynamic framework to monitor structural risks and design early‑warning systems that capture both performance levels and temporal stability.

Keywords

• Dynamic Performance Evaluation
• Banking
• Tensor TOPSIS
• LOPCOW

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