Portföy Yönetiminde Bayesci Yaklaşımlar: BIST30 Endeksi Üzerine Bir Uygulama

Öz p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 12.0px 'Minion Pro'; min-height: 14.0px} p.p2 {margin: 0.0px 0.0px 0.0px 0.0px; text-align: justify; line-height: 10.1px; font: 10.0px 'Minion Pro'; color: #2d2829} span.s1 {font: 12.0px 'Minion Pro'; color: #000000} Markowitz’in ortalama varyans portföyü matematiğin, finansal uygulamalarda kullanılmasına öncülük etmesi açısından bir dönüm noktası olmuştur. Aynı zamanda model, hesap kolaylığı sebebiyle 1-dönemlik portföy kararlarının hızlı alınması açısından da önemlidir. Fakat zaman içinde yapılan çalışmalar, ortalama-varyans portföyünün performansının parametre, tahmin hataları sebebi ile oldukça düşük olduğunu göstermiştir. Bu sebeple literatürde bu sorunun önüne geçebilmek amacıyla birçok yeni teori ve yöntem/ yaklaşım geliştirilmiştir. Bayesci portföy metodu bunlardan bir tanesidir. Bu çalışma, ortalama-varyans modeli üzerine kurulan üç bayesci yaklaşımı: Jorion (1985,1986), Kan ve Zhou (2007), Tu ve Zhou (2011), Markowitz’in ortalama-varyans modeli ile karşılaştırmayı amaçlamaktadır. Ayrıca bir baz model olarak, eşit-ağırlıklı portföy yöntemi de diğer yöntemlerle karşılaştırılmıştır. Bu amaç doğrultusunda, BİST30 endeksinde işlem gören 30 hisse senedine ait 2010-2017 yılları arasındaki günlük getiri serileri kullanılmış ve gerçek getirilerden simülasyon yardımıyla oluşturulan farklı büyüklükteki portföylerin performansları karşılaştırılmaya çalışılmıştır. Genel olarak değerlendirildiğinde, en iyi performans gösteren portföyün Kan ve Zhou’nun önerdiği Bayesci portföy olduğu sonucuna varılmıştır. 

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