Fourier Serileri ile Modifiye Edilmiş Modelleri Kullanarak Borsa İstanbul (BİST) Üzerine Bir Uygulama

Cebeli İnan; Erkan Oktay

EN TR

An Application on Borsa Istanbul (BIST) Using Models Modified with Fourier Series

Abstract

Predicting the future accurately is of vital importance in all disciplines, as well as in the field of social sciences. Especially today, due to the development of technology and the presence of package programs that can process huge data, it is a very important development for all fields, including econometrics, that we can reach more accurate estimates. As a result, it is a situation that is directly related to the decrease in the error rates of the forecasts and more accurate planning for the future. In this study, time series analyzes were made over the proportional changes of the closing values of the Borsa Istanbul (BIST30) index, that is, the monthly average closing values, and 24-month forecasts were calculated. For this purpose, in order to increase the accuracy of the prediction results of the classical ARIMA models and the models based on the Box-Cox transform, new prediction results were obtained with the models modified with the Fourier series. Mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE) and mean absolute percent error (MAPE) performance criteria were used to evaluate the success of the established models. It was concluded that the model with the lowest value for MSE, RMSE, MAE and MAPE performance criteria was more successful than the other models. As a result, more successful results were obtained with more accurate estimation results, that is, with lower error rates.

Keywords

Fourier Serileri ile Modifiye Edilmiş Modelleri Kullanarak Borsa İstanbul (BİST) Üzerine Bir Uygulama

Öz

Bütün disiplinlerde geleceği doğru tahmin etme hayati öneme sahip olduğu gibi sosyal bilimler alanında da bu çok önemli bir durumdur. Özellikle günümüzde teknolojinin gelişmesi ve devasal verileri işleyebilecek paket programların olmasından ötürü daha doğru tahminlere ulaşabilmemiz ekonometri alanı dahil tüm alanlar için çok önemli bir gelişmedir. Sonuç olarak yapılan tahminlerin hata oranlarının azalması ve geleceğe dair daha doğru planlamaların yapılması ile direkt ilişkili bir durumdur. Bu çalışmada, Borsa İstanbul (BİST30) endeksi kapanış değerlerinin oransal değişimlerine yani, aylık ortalama kapanış değerleri üzerinden zaman serisi analizleri yapılmış ve 24 aylık öngörüler hesaplanmıştır. Bu amaçla klasik ARIMA modelleri ve Box-Cox dönüşümü temeline dayanan modellerin tahmin sonuçlarının doğruluklarını arttırmak için Fourier serileri ile modifiye edilmiş modeller ile yeni tahmin sonuçları elde edilmiştir. Kurulan modellerin başarısını değerlendirmek için ortalama kare hata (MSE), kök ortalama kare hata (RMSE), ortalama mutlak hata (MAE) ve ortalama mutlak yüzde hata (MAPE) performans ölçütleri kullanılmıştır. MSE, RMSE, MAE ve MAPE performans ölçütleri için en düşük değeri veren model diğer modellere göre daha başarılı olduğu sonucuna varılmıştır. Netice olarak yeni tahmin sonuçlarının daha doğru yani daha düşük hata oranları ile daha başarılı sonuçlar elde edilmiştir.

Anahtar Kelimeler

Kaynakça

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Ayrıntılar

Birincil Dil

Türkçe

Konular

Ekonomi

Bölüm

Araştırma Makalesi

Yazarlar

Cebeli İnan ^*
0000-0002-7924-9911
Türkiye

Erkan Oktay
0000-0002-1739-3184
Türkiye

Yayımlanma Tarihi

11 Ocak 2023

Gönderilme Tarihi

16 Ağustos 2022

Kabul Tarihi

6 Eylül 2022

Yayımlandığı Sayı

Yıl 2022 Cilt: 5 Sayı: 2

IZ

https://izlik.org/JA63JK57BA

Kaynak Göster

RIS / Bibtex

APA

İnan, C., & Oktay, E. (2023). Fourier Serileri ile Modifiye Edilmiş Modelleri Kullanarak Borsa İstanbul (BİST) Üzerine Bir Uygulama. Turkish Research Journal of Academic Social Science, 5(2), 81-91. https://izlik.org/JA63JK57BA