Reducing Variation of Risk Estimation by Using Importance Sampling

Hatem Çoban, İpek Deveci Kocakoç, Şemsettin Erken and Mehmet Akif Aksoy

Alphanumeric Journal, 2019, vol. 7, issue 2, 173-184

Abstract: 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.

Keywords: Delta Normal Method; Importance Sampling; Monte Carlo Simulation; Tail Risk; Value at Risk (search for similar items in EconPapers)
JEL-codes: G32 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.alphanumericjournal.com/media/Issue/vo ... tance-sa_z9RFQne.pdf (application/pdf)
https://alphanumericjournal.com/article/reducing-v ... importance-sampling/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:anm:alpnmr:v:7:y:2019:i:2:p:173-184

DOI: 10.17093/alphanumeric.605584

Access Statistics for this article

More articles in Alphanumeric Journal from Bahadir Fatih Yildirim
Bibliographic data for series maintained by Bahadir Fatih Yildirim ().