In this study; breaks in stock price volatility are detected with ICSS algorithm which was developed by Inclan and Tiao 1994 After detecting multiple breaks in variance dummy variables are introduced to the variance equation of GARCH 1 1 model to account for the sudden changes in variance We examined daily İMKB U30 return series and found that volatility persistence has considerably dwindled in new GARCH 1 1 model with eight dummy variables Key Words: GARCH Variance Break ICSS Volatility
📌 3 Key Takeaways
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Objective & Hypothesis:In this study; breaks in stock price volatility are detected with ICSS algorithm which was developed by Inclan and Tiao 1994 After detecting multiple breaks in variance dummy variables are introduced to the variance equation of GARCH 1 1 model to account for the sudden changes in variance We examined daily İMKB U30 return series and found that volatility persistence has considerably dwindled in new GARCH 1 1 model with eight dummy variables Key Words: GARCH Variance Break ICSS Volatility
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Key Findings & Data:In this study; breaks in stock price volatility are detected with ICSS algorithm which was developed by Inclan and Tiao 1994 After detecting multiple breaks in variance dummy variables are introduced to the variance equation of GARCH 1 1 model to account for the sudden changes in variance We examined daily İMKB U30 return series and found that volatility persistence has considerably dwindled in new GARCH 1 1 model with eight dummy variables Key Words: GARCH Variance Break ICSS Volatility
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Conclusion & Impact:In this study; breaks in stock price volatility are detected with ICSS algorithm which was developed by Inclan and Tiao 1994 After detecting multiple breaks in variance dummy variables are introduced to the variance equation of GARCH 1 1 model to account for the sudden changes in variance We examined daily İMKB U30 return series and found that volatility persistence has considerably dwindled in new GARCH 1 1 model with eight dummy variables Key Words: GARCH Variance Break ICSS Volatility
In this study; breaks in stock price volatility are detected with ICSS algorithm which was developed by Inclan and Tiao 1994 After detecting multiple breaks in variance dummy variables are introduced to the variance equation of GARCH 1 1 model to account for the sudden changes in variance We examined daily İMKB U30 return series and found that volatility persistence has considerably dwindled in new GARCH 1 1 model with eight dummy variables Key Words: GARCH Variance Break ICSS Volatility
Özet
Bu çalışmada hisse senedi oynaklığındaki kırılmalar Inclan ve Tiao’nun 1994 ICSS Iterative Cumulative Sum of Squares algoritması ile tespit edilmiş bulunan kırılma noktaları kukla değişkenler olarak GARCH modeline eklenmiş ve kırılmaların dikkate alındığı yeni bir GARCH modeli oluşturulmuştur Çalışmada İMKB Ulusal 30 günlük getiri serisi kullanılmış bulunan sekiz kırılma noktası modele dahil edildiğinde oynaklık kalıcılığında önemli bir azalma olmuştur Bu da yatırımcılara riske karşı alacakları tutum konusunda ışık tutacak önemli bir sonuçtur
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