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Journals / Akdeniz İİBF Dergisi / 2009 / Cilt: 9 - Sayı: 17

Value at risk analysis with expected shortfall

Beklenen kayıp yöntemi ile riske maruz değer analizi

Türker ADAKALE
Mert URAL
Pages
23–39
Publication Date
2022-10-11
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results show that the estimated VaR and ES for traders having both short and long positions in the Istanbul Stock Exchange is more accurately modeled by a Skewed Student-t APARCH model that by a normal, Student-t or GED distributions.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Empirical studies have shown that a large number of financial asset returns exhibit fat tails and are often characterized by volatility clustering and asymmetry.
📊
Key Findings & Data:This paper provides Value at Risk (VaR) and Expected Shortfall (ES) estimations for daily stock returns in two different periods (normal and crises) with the application of Generalized Asymmetric Power ARCH (APGARCH) model according to different error distribution assumptions.
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Conclusion & Impact:The results show that the estimated VaR and ES for traders having both short and long positions in the Istanbul Stock Exchange is more accurately modeled by a Skewed Student-t APARCH model that by a normal, Student-t or GED distributions.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

Empirical studies have shown that a large number of financial asset returns exhibit fat tails and are often characterized by volatility clustering and asymmetry. This paper provides Value at Risk (VaR) and Expected Shortfall (ES) estimations for daily stock returns in two different periods (normal and crises) with the application of Generalized Asymmetric Power ARCH (APGARCH) model according to different error distribution assumptions. The results show that the estimated VaR and ES for traders having both short and long positions in the Istanbul Stock Exchange is more accurately modeled by a Skewed Student-t APARCH model that by a normal, Student-t or GED distributions.

Özet

Uygulamalı çalışmalar, finansal varlık getirilerinin şişman kuyruklu olduklarını ve büyük bir kısmının volatilite kümelenmesi ve asimetri ile karakterize edildiklerini göstermektedir. Bu çalışmada, iki farklı dönem (normal ve kriz) açısından çeşitli dağılımlara göre Genelleştirilmiş Asimetrik Üslü ARCH (APGARCH) modeli uygulanarak günlük hisse senedi getirileri için Riske Maruz Değer (VaR) ve Beklenen Kayıp (ES) tutarları hesaplanmıştır. İstanbul Menkul Kıymetler Borsası’nda kısa ve uzun pozisyon alan yatırımcılar için VaR ve ES hesaplamalarının normal, Student-t ve GED dağılımlarına kıyasla Skewed (Çarpık) Student-t dağılımlı APGARCH modeli ile daha doğru modellendiği anlaşılmıştır.

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Cite This Article

ADAKALE, T., URAL, M. (2022). Value at risk analysis with expected shortfall. Akdeniz İİBF Dergisi, Cilt: 9 - Sayı: 17, 23–39. https://ajindex.com/articles/433177

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