Borsa İstanbul Fiyatlarının Arima Modeli İle Tahmin Edilmesi

Açık ekonomilerdeki kritik konumu ve son derece yüksek oynaklığı nedeniyle borsa fiyat endeksi, piyasa araştırmalarının popüler bir konusu olmuştur. Modern finans piyasalarında, tüccarlar ve uygulayıcılar borsa fiyat endeksini tahmin etmekte zorlanıyorlar. Bu soruna çözüm getirmek için araştırmacılar tarafından bazı yöntemler araştırılmış ve uygun yöntemler bulunmuştur. Aylık borsa fiyat endeksini analiz etmek ve tahmin etmek için çeşitli istatistiksel ve ekonometrik modeller yaygın olarak kullanılmaktadır. Bu nedenle, bu çalışma, 2009-M01 ile 2021-M03 arasındaki dönem için İstanbul'da aylık borsa fiyat endeksini tahmin etmek için otoregresif entegre hareketli ortalamalar (ARIMA) uygulamasını araştırmayı amaçlamaktadır. Araştırma, diğer tüm geçici modellerle karşılaştırıldığında, ARIMA (3,1,5) modelinin borsa fiyat endeksini tahmin etmek için en uygun model olduğunu göstermiştir. Tahmin, geliştirilen ARIMA (3,1,5) modeli kullanılarak yapılmıştır ve sonuçlar, tahmin edilen değerlerin gerçek değerlere çok benzer olduğunu ve tahmin hatalarını azalttığını göstermiştir. Genel olarak İstanbul'da borsa fiyat endeksi; tahmin edilen dönemde aşağı yönlü bir eğilim göstermiştir. Çalışmanın sonuçları borsada çalışan araştırmacı ve uygulayıcılara örnek teşkil edebileceği gibi borsada ekonomik karar birimlerine ve yatırımcılara yol gösterici olabilir.

Anahtar Kelimeler:

ARIMA, tahminleme, borsa fiyat endeksi, zaman serisi, Türkiye

Stock Market Price Forecasting Using the Arima Model: an Application to Istanbul, Turkiye

Because of its critical position in open economies and its extremely high volatility, the stock market price index has been a popular subject of market research. In modern financial markets, traders and practitioners have had trouble predicting the stock market price index. In order to solve this problem, some methods have been researched by researchers and suitable methods have been found. To analyze and forecast monthly stock market price index, a variety of statistical and econometric models are extensively used. Thus, this study aims to investigate the application of autoregressive integrated moving averages (ARIMA) for forecasting monthly stock market price index in Istanbul for the period from 2009- M01 to 2021-M03. As compared to all other tentative models, the research showed that the ARIMA (3,1,5) model is the best fit model for predicting the stock market price index. Forecasting is conducted by using the developed model ARIMA (3,1,5) and the results indicated that the forecasted values are very similar to the actual ones, reducing forecast errors. In general, the stock market price index in Istanbul; showed a downwards trend over the forecasted period. The results of the study can set an example for researchers and practitioners working in the stock market and can be a guide for economic decision units and investors in the stock market.

Keywords:

ARIMA, forecasting, stock market price index, time series, Turkiye,

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