Portföy Analizinde Beklenen Getiri Sorunu: Markov Getiriler ve Basit Getirilerin Karşılaştırılması

Ortalama varyans modeline göre optimal portföyler oluşturulurken yatırım araçlarının geçmiş değerlerinden yararlanarak hesaplanan birinci moment (getiri) ve ikinci moment (varyans) değerleri kullanılmaktadır. Amaç, belli bir getiri değerine bağlı olarak minimum riskli portföyler oluşturmak veya belli bir risk değerine bağlı olarak maksimum getiri elde etmektir. Fakat kullanılan risk ve beklenen getiri ölçütüne göre portföydeki hisse senetleri çeşitliliği ve hisse senedi ağırlıkları farklılık göstermektedir. Dolayısıyla doğru risk ve getiri ölçüsü kullanmak daha etkin portföyler oluşturmak için önemlidir. Bu çalışmada literatürde yaygın olarak kullanılan klasik getiri ölçüsü (geçmiş getirilerin beklenen değeri “Basit getiri”) ile Markov zincirleri modellerinden elde edilen getiriler karşılaştırılmış ve bu getirilerin portföy oluşturma üzerindeki etkileri incelenmiştir. Markov getirili modellerin basit getirili modellerden daha etkin portföyler oluşturduğu sonucuna ulaşılmıştır.

Anahtar Kelimeler:

Markov Zincirleri modelleri, Ortalama varyans modeli, Hisse senedi getirileri, BIST30

Expected Returns Issue in Portfolio Analysis: A Comparison of Markov Chains’ Returns and Simple Returns

In mean-variance model, the first moment (mean) and the second moment (variance) of variables are used in the phase of portfolio selection. The aim is to select portfolio that has minimum variance depending on given expected return or to select portfolio that has maximum return depending on given risk. But, according to measurement of expected returns and variance used in portfolio, the weights of stocks and the performance of portfolio would differ from one measurement to another. So, using the correct measurement of expected return and variance is crucial for construction of efficient portfolios. In this article, the expected returns obtained from Markov chain models are compared with expected returns obtained from historical data, and the effects of these returns are investigated on portfolio selection. As a result, portfolio with expected returns of Markov chain model construct more efficient portfolios.

Keywords:

Markov chain models, mean-variancde model, retuns of stock, XU030,

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