Comparison of evolutionary techniques for Value-at-Risk calculation
Yükleniyor...
Dosyalar
Tarih
2007
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer-Verlag Berlin
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The Value-at-Risk (VaR) approach has been used for measuring and controlling the market risks in financial institutions. Studies show that the t-distribution is more suited to representing the financial asset returns in VaR calculations than the commonly used normal distribution. The frequency of extremely positive or extremely negative financial asset returns is higher than that is suggested by normal distribution. Such a leptokurtic distribution can better be approximated by a t-distribution. The aim of this study is to asses the performance of a real coded Genetic Algorithm (CA) with Evolutionary Strategies (ES) approach for Maximum Likelihood (ML) parameter estimation. Using Monte Carlo (MC) simulations, we compare the test results of VaR simulations using the t-distribution, whose optimal parameters are generated by the Evolutionary Algorithms (EAs), to that of the normal distribution. It turns out that the VaR figures calculated with the assumption of normal distribution significantly understate the VaR figures computed from the actual historical distribution at high confidence levels. On the other hand, for the same confidence levels, the VaR figures calculated with the assumption of t-distribution are very close to the results found using the actual historical distribution. Finally, in order to speed up the MC simulation technique, which is not commonly preferred in financial applications due to its time consuming algorithm, we implement a parallel version of it.
Açıklama
Anahtar Kelimeler
Banks, Evolutionary algorithm, Evolutionary algorithms, Evolutionary strategies, Finance, Financial crisis, Genetic algorithm, Liquidity, Marketing, Maximum likelihood, Maximum likelihood estimation, Monte Carlo simulation, Parameter estimation, Risk analysis, T-distribution, Value-at-risk
Kaynak
Applications Of Evolutionary Computing, Proceedings
WoS Q Değeri
Q4
Scopus Q Değeri
Q3
Cilt
4448
Sayı
Künye
Uludağ, G., Uyar, A. S., Şenel, K. & Dağ, H. (2007). Comparison of evolutionary techniques for value-at-risk calculation. Paper presented at the Applications Of Evolutionary Computing, Proceedings, 4448, 218-227.
