Uyarlanabilir Hareketli Ortalama ile Turkiye’nin Makro Gostergelerinden Sinyal Cikarimi

Eren Ocakverdi and Erdal Yilmaz

CBT Research Notes in Economics from Research and Monetary Policy Department, Central Bank of the Republic of Turkey

Abstract: [TR] Ekonomik verilerdeki gecici dalgalanmalar, ekonominin genel yonunu izlemeyi guclestirebilmektedir. Bu notta, soz konusu dalgalanmalari ayiklamak ve ana egilimi belirlemek amaciyla AlbaMA adli uyarlanabilir hareketli ortalama yontemi Turkiye verilerine uygulanmaktadir. Geleneksel hareketli ortalamalar sabit uzunluktaki donemleri esas alirken, AlbaMA hangi gozlemlere ne kadar agirlik verecegini verinin seyrine gore ayarlamaktadir. Yontem, ekonomik buyume, sanayi uretimi, tuketici enflasyonu, perakende ticaret hacmi ve ihtiyac kredisi faiz oranlari icin incelenmektedir. Kullanilan degerlendirme olcutleri altinda, kisa donemli degisimlere daha duyarli parametre tercihleri one cikmaktadir. Enflasyona iliskin grafiksel karsilastirmalar, AlbaMA’nin incelenen bazi donemlerde yon degisimlerini geleneksel hareketli ortalamalara gore daha hizli yansitabildigine isaret etmektedir. Bununla birlikte, yontemin basarisi gostergeler arasinda farklilasmaktadir. Bulgular, AlbaMA’nin politika yapicilar acisindan diger gostergelerle birlikte kullanilabilecek tamamlayici bir izleme araci olabilecegini dusundurmektedir. [EN] Temporary fluctuations in economic data can make it difficult to identify underlying trends. This note applies AlbaMA, an adaptive moving average method, to selected Turkish economic indicators to help separate these fluctuations from the broader direction of economic activity. Conventional moving averages use a fixed window of observations, whereas AlbaMA adjusts the weight assigned to each observation as patterns in the data change. The analysis covers GDP growth, industrial production, consumer price inflation, retail sales volume, and consumer lending rates. Under the evaluation criteria used, parameter calibrations that respond more closely to short-term changes are preferred. Graphical comparisons for inflation suggest that AlbaMA can reflect changes in direction faster than conventional moving averages in some of the periods examined. Its performance nevertheless varies across indicators. The findings suggest that AlbaMA could complement other indicators used by policymakers to monitor economic developments.

Date: 2026
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