Dergiler / Alphanumeric Journal / 2019 / Cilt: 7 - Sayı: 2

Reducing Variation of Risk Estimation by Using Importance Sampling

Sayfa
173–184
Yayın Tarihi
2019-12-31
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

This study aims to demonstrate the usage of delta normal method, historical simulation method, Monte Carlo simulation, and importance sampling to calculate the value at risk and to show which method is more effective by applying them to the S&P index between 1993 and 2003.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Öz In today's world, risk measurement and risk management are of great importance for various economic reasons.
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Temel Bulgular & Veri:Many methods have been developed for accurate measurement of risk.
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Sonuç & Katkı:This study aims to demonstrate the usage of delta normal method, historical simulation method, Monte Carlo simulation, and importance sampling to calculate the value at risk and to show which method is more effective by applying them to the S&P index between 1993 and 2003.
🔬Tür:Araştırma Makalesi
📍Kapsam:2003 Verileri
⚙️Değişkenler:Anahtar Kelimeler Importance Sampling · Value at Risk · Monte Carlo Simulation

Özet

Öz In today's world, risk measurement and risk management are of great importance for various economic reasons. Especially in the crisis periods, the tail risk becomes very important in risk estimation. Many methods have been developed for accurate measurement of risk. The easiest of these methods is the Value at Risk (VaR) method. However, standard VaR methods are not very effective in tail risks. This study aims to demonstrate the usage of delta normal method, historical simulation method, Monte Carlo simulation, and importance sampling to calculate the value at risk and to show which method is more effective by applying them to the S&P index between 1993 and 2003.

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Bu Makaleye Atıf Yap

ÇOBAN, H., KOCAKOÇ, İ. D., ERKEN, Ş., AKSOY, M. A. (2019). Reducing Variation of Risk Estimation by Using Importance Sampling. Alphanumeric Journal, Cilt: 7 - Sayı: 2, 173–184. https://ajindex.com/articles/63490

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Kaynakça (11)

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