Çok Değişkenli Uyarlanabilir Regresyon Uzanımları (MARS) Modeli Kullanılarak Türkiye’de Borsa Fiyatının Makroekonomik Değişkenler İle Tahmin Edilmesi

Öz

Bu çalışma, Türkiye’de Ocak 2010'dan Aralık 2019'a kadar geçen sürede Çok Değişkenli Uyarlanabilir Regresyon Spline (MARS) Modelini kullanarak, Borsa İstanbul kapanış fiyatının (BIST 100) makroekonomik belirleyicilerini tahmin etmeyi amaçlamaktadır. Bu çalışmada,. MARS modelini kullanarak hisse senedi fiyatını tahmin etmek için 10 makroekonomik değişken kullanılmıştır. Sonuçlarımız enflasyon oranı, altın fiyatları, sanayi üretim endeksi, para arzı, döviz kuru, kredi hacmi ve iç borç stoku gibi değişkenlerin BIST 100 kapanış fiyatının tahmini için önemli olduğunu göstermektedir.

Anahtar Kelimeler

• Çok Değişkenli Uyarlanabilir Regresyon Uzanımları (MARS) Modeli
• BIST 100
• Makroekonomik Değişkenler

Forecasting Turkish Stock Market Price With Macroeconomic Variables From The Multivariate Adaptive Regression Splines (Mars) Model

Öz

This empirical investigation aims at forecasting the macroeconomic determinants of Istanbul Stock Price (XU 100) in Turkey by using the Multivariate Adaptive Regression Splines (MARS) Model over the period spanning from the January 2010 to December 2019. In this study, we used 10 macroeconomic variables for forecasting stock price using the MARS model. Our results indicate that variables such as inflation rate, gold prices, industrial production index, money supply, exchange rate, credit volume, and internal debt stock were found to be important for forecasting XU100 price.

Anahtar Kelimeler

• Multivariate Adaptive Regression Splines (MARS) Model
• XU 100
• Macroeconomic Variables

Kaynakça

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