VOLATİLİTENİN MODELLENMESİ VE ANFIS MODEL İLE BIST100 GETİRİ TAHMİNİ

Hisse senedi piyasası volatilitesi finans literatüründe önemli bir konu olarak ele alınmakta ve herhangi bir menkul kıymetin fiyatında meydana gelen ani değişkenlik olarak tanımlanmaktadır. Volatilite, ortaya çıkabilecek olası değişkenlikler doğrultusunda finansal piyasalarda yatırımcıların karar alma süreçlerini etkileyen belirsizliği de temsil etmektedir. Birçok ülkede, özellikle gelişmekte olan finansal piyasalarda gerek yatırımcılar gerekse politika yapıcılar artan risk ve belirsizlik problemleri ile sıkça karşılaşmaktadır. Buna bağlı olarak volatilitenin dikkate alınması özellikle yatırımcıların uzun dönemli yatırım kararlarında finansal varlıkların getirilerini tahmin edebilmeleri için oldukça önemlidir. Herhangi bir finansal varlığa ait getirinin değişkenliğini ifade eden volatilite, finansal varlıkların getirilerini tahmin etmede de çok önemli bir yere sahiptir. Bu çalışmada Borsa İstanbul100 (BIST100) endeksi kullanılarak Türkiye hisse senedi piyasası volatilitesi ve hisse senedi piyasa endeksinin asimetrik etki gösterip göstermediği GARCH-EGARCH modelleri kullanılarak araştırılmıştır. BIST100 endeksinin barındırdığı belirsizlik ve kaotik (düzensiz) davranışları geleneksel yöntemlerle tahmin etmek bir başka ifade ile riski yönetmek oldukça güç olmaktadır. Bu sebeple, çalışmada hisse senedi getirisinin tahmin edilmesi için belirsizliği modellemede yaygın olarak kullanılan bulanık mantık ve sinir ağı hibrit modeli uygulanmıştır. Çalışmada kullanılan veri seti 2009-2017 dönemine ilişkin günlük hisse senedi kapanış fiyatlarını kapsamaktadır. Yapılan kapsamlı literatür araştırması sonucu volatilitenin tahmini ve devamında bulanık mantık temelli yaklaşımların kullanıldığı bir çalışmaya rastlanmamıştır. Bu sebeple çalışmanın özgün bir değere sahip olduğu düşünülmektedir.

Anahtar Kelimeler:

Volatilite, GARCH, ANFIS

MODELLING VOLATILITY AND FORECASTING BIST100 RETURN BY USING ANFIS

Stock market volatility is considered as an important issue in financial literature and is defined as sudden instability that occurs in the price of any security. Volatility also represents the uncertainty that affects investors' decision-making processes in financial markets in the face of possible variations. In many countries, especially in emerging financial markets, both investors and policy makers are often confronted with increasing risk and uncertainty problems. Accordingly, considering volatility is crucial for investors to predict the return of financial assets, especially in long-term investment decisions. Volatility, which expresses the variability of any financial asset, has a very important place in the estimation of the return. In this study, the volatility of the Turkish stock market was estimated through the GARCH models using the Stock Exchange Istanbul100 (BIST100) index. Whether the stock market index has an asymmetric effect is investigated using the EGARCH model. It is very difficult to predict the uncertainty and chaotic behavior of the BIST100 index by traditional methods. For this reason, the fuzzy logic and neural network hybrid model, which is widely used in the model of uncertainty, has been applied to estimate the stock return in the study. The dataset used in the study includes daily stock closing prices for the period 2009-2017. As a result of the extensive literature survey, no studies have been found on the use of fuzzy logic based approaches in estimating and continuing volatility. For this reason, it is thought that working has an original value.

Keywords:

Volatility, GARCH, ANFIS,

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