Information Flows Among Stocks in Borsa Istanbul: A Transfer Entropy-Based Network Analysis

Abstract

Bu çalışmanın amacı, BİST 100 endeksi bileşenleri arasındaki bilgi akışının yönünü ve büyüklüğünü efektif transfer entropisi (ETE) yöntemiyle incelemektir. Çalışmanın kapsamını 2 Ocak 2020 – 3 Temmuz 2025 döneminde endekste yer alan ve veri bütünlüğü sağlayan 65 hissenin günlük getirileri oluşturmaktadır. Öncelikle veri setindeki her hisse çifti için ETE değerleri hesaplanmış ve asimetrik bir bilgi ağı oluşturulmuştur. Analizlerde yalnızca pozitif ETE değerine sahip ve Markov blok bootstrap testine göre istatistiksel olarak anlamlı bulunan bağlantılar dikkate alınmıştır. Bu filtrelenmiş ağ üzerinden her hisse için ortalama bilgi girişi, bilgi çıkışı ve net bilgi akışı göstergeleri hesaplanmış, ardından hisse senetleri net bilgi kaynağı, net bilgi alıcısı ve görece dengeli bileşenler olarak sınıflandırılmıştır. Mikro düzeyde elde edilen ETE değerleri, Kamuyu Aydınlatma Platformu sektör sınıflamasına göre gruplanarak sektörler arası bilgi transferi matrisi oluşturulmuş ve sektörlerin toplam bilgi alışveriş hacimleri ile net bilgi akışları değerlendirilmiştir. Son olarak hisse ve sektör düzeyinde yönlü maksimum kapsayan ağaçlar elde edilerek bilgi ağının omurga yapısı görselleştirilmiş, mali kuruluşlar sektörünün merkezî konumu ve diğer sektörlere doğru kademeli bilgi yayılımı üzerinden piyasa içi olası yayılma ve bulaşma kanalları tartışılmıştır.

Keywords

• Bilgi Akışı
• Efektif Transfer Entropisi
• Yönlü Ağ Analizi
• BİST 100

Borsa İstanbul’da Hisse Senetleri Arasında Bilgi Akışı: Transfer Entropisi Temelli Ağ Analizi

Abstract

This study aims to examine the strength and direction of information flows among BIST 100 index stocks by employing the effective transfer entropy (ETE) method. The sample consists of daily returns of 65 stocks with continuous data from 2 January 2020 to 3 July 2025. First, ETE values are computed for each stock pair, and an asymmetric information network is constructed. The analyses are based only on positive ETE values that are statistically significant according to the Markov block bootstrap test. Using this filtered network, average information inflow, information outflow, and net information flow indicators are calculated for each stock, and stocks are classified as net information sources, net information receivers, or relatively balanced components. Stock-level ETE measures are then aggregated according to the Public Disclosure Platform (KAP) sector classification to obtain a sector-to-sector information transfer matrix. Finally, directed maximum spanning trees are derived at both the stock and sector levels to visualize the backbone structure of the information network. The findings reveal the central role of the Financial Institutions sector and indicate gradual information diffusion towards other sectors as potential intra-market spillover and contagion channels.

Keywords

• Information Flow
• Effective Transfer Entropy
• Directed Network Analysis
• BIST 100

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