HETEROSKEDASTİK VERİLERDE BİLİNMEYEN DEĞİŞİM NOKTALARININ TESPİT EDİLMESİ

Year 2023, Volume: 24 Issue: 2, 81 - 98, 31.12.2023

Sıdıka Başçı , Asad Ul Islam Khan

https://doi.org/10.24889/ifede.1300907

Abstract

Bilinmeyen değişim noktalarında yapısal değişimi tespit etmek için birkaç test vardır. Andrews Sup F testi (1993) en güçlüsüdür, ancak eş varyans varsayımını gerektirir. Ahmed ve ark. (2017), bu varsayımı gevşeten ve hem regresyon hem de varyans katsayılarındaki değişiklikleri aynı anda test eden Sup MZ testini tanıttı. Bu çalışmada, bilinmeyen değişim noktalarındaki yapısal değişiklikleri tespit etmek için Sup MZ testini kullanan bir model güncelleme prosedürü öneriyoruz. Bu prosedürü, İstanbul Menkul Kıymetler Borsası hisse senedi endeksinin (BIST 100) 21 yıllık (2003-2023) haftalık getirilerini modellemek için uyguluyoruz. Modelimiz, bilinmeyen zamanlarda ortalama veya varyans seviyesinde ara sıra sıçramalar ile basit bir ortalama artı gürültüden oluşur. Amaç, bu sıçramaları tespit etmek ve modeli buna göre güncellemektir. Ayrıca, prosedürümüzdeki tahminleri kullanan ve bunu al ve tut stratejisiyle karşılaştıran bir ticaret kuralı öneriyoruz.

Keywords

yapısal değişim, bilinmeyen değişim noktaları, Sup MZ testi, İstanbul borsası, tahmin

DETECTING UNKNOWN CHANGE POINTS FOR HETEROSKEDASTIC DATA

Abstract

There are several tests to detect structural change at unknown change points. The Andrews Sup F test (1993) is the most powerful, but it requires the assumption of homoskedasticity. Ahmed et al. (2017) introduced the Sup MZ test, which relaxes this assumption and tests for changes in both the coefficients of regression and variance simultaneously. In this study, we propose a model update procedure that uses the Sup MZ test to detect structural changes at unknown change points. We apply this procedure to model the weekly returns of the Istanbul Stock Exchange's common stock index (BIST 100) for a 21-year period (2003-2023). Our model consists simply a mean plus noise, with occasional jumps in the level of mean or variance at unknown times. The goal is to detect these jumps and update the model accordingly. We also suggest a trading rule that uses the forecasts from our procedure and compare it to the buy-and-hold strategy.

Keywords

structual change, unknwn change points, Sup MZ test, Istanbul stock exchange, forecast

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