MEVDUAT FAİZ ORANLARININ ARİMA YÖNTEMİ İLE TAHMİNİ: 2010-2022 DÖNEMİ TÜRKİYE UYGULAMASI

Yıl 2023, , 363 - 384, 31.05.2023

Cumhur Şahin

https://doi.org/10.30561/sinopusd.1282481

Öz

Finansal verilerin en dikkate değer özelliklerinden biri zamana bağlı biçimde bir dizi teşkil etmeleridir. Bundan ötürü zaman serilerinin unsurları, söz konusu verilerin ifade ettiği ekonomik ve finansal parametreler hakkındaki bilgiyi de kapsamaktadır. Finans çalışmalarında değişkenlere ilişkin öngörü ya da tahmin hayati bir öneme sahiptir. Finansal değişkenlerin doğru, sağlıklı tahmin edilebilmesi, finansal piyasalardaki paydaşların açısından vazgeçilmez bir durumdur. Tahmin yapmada en sık kullanılan yöntemlerden birisi de ARİMA modelidir. Auto Regressive Integrated Moving Average (Otoregresif entegre hareketli ortalama) (ARIMA) modeli, tek değişkenli zaman serisi verilerini, transfer fonksiyonu verilerini ve ayrıca müdahale verilerini eşit şekilde dağıtan verilerde analiz ve tahminler için kullanılmaktadır. ARIMA yöntemi, ilk olarak Box ve Jenkins (1976) tarafından açıklamıştır, bu nedenle ARIMA modelleri genellikle Box-Jenkins modelleri olarak anılmaktadır. Bu çalışmada 2010-2022 yılı arasındaki dönem itibariyle Türkiye’de 1 yıl vadeli TL mevduat faiz oranları ARİMA yöntemi ile tahmin edilmeye çalışılmıştır. Analiz sonuçlarına göre araştırmada kullanılan Box-Jenkins (ARIMA) modelinin geçerli olduğu sonucuna varılmıştır. ARIMA (1,1,1) modelinin hem model uyum düzeyi ve modelin açıklama gücü, hem de tahmin değerleri ile gerçek değerler, modelin tahminde kullanılabilecek en doğru sonuçları veren, sağlam ve güvenilir bir model olduğunu gözlenmiştir.

Anahtar Kelimeler

ARİMA, Tahmin, Mevduat faiz oranı, Türkiye

Forecasting The Deposit Interest Rates with The ARIMA Method: Turkish Application for The Period 2010-2022

Öz

One of the most remarkable characteristics of financial data is that they form a series in a time-dependent manner. For this reason, the elements of the time series also include the information on the economic and financial parameters expressed by the data in question. Forecasting variables has a vital importance in finance studies. Accurate and healthy forecasting of financial variables is an indispensable condition for stakeholders in financial markets. One of the most frequently used methods in making predictions is the ARIMA Method. The Auto Regressive Integrated Moving Average (ARIMA) Method is used for analysis and forecasting on data that evenly distributes univariate time series data, transfer function data, as well as intervention data. An ARIMA Model predicts a value in the response time series as a linear combination of its past values, errors or shocks, as well as the current and past values of other time series. The ARIMA Method was first described by Box and Jenkins (1976). For this reason, ARIMA Models are often referred to as Box-Jenkins Models. In the present study, 1-year TL deposit interest rates for the period between 2010 and 2022 in Turkey were predicted with the ARIMA Method. According to the results of the analysis, it was concluded that the Box-Jenkins (ARIMA) Model used in the study is valid. It was found that the ARIMA (1, 1, 1) Model is a robust and reliable model that yields the most accurate results that can be used in prediction, both the level of model fit and the explanatory power of the model, as well as the forecasting and actual values.

Anahtar Kelimeler

ARIMA, Forecasting, Deposit interest rate, Turkey

Kaynakça

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