## Abstract ValueβatβRisk (VaR) is widely used as a tool for measuring the market risk of asset portfolios. However, alternative VaR implementations are known to yield fairly different VaR forecasts. Hence, every use of VaR requires choosing among alternative forecasting models. This paper undertak
β¦ LIBER β¦
Empirical likelihood-based evaluations of Value at Risk models
β Scribed by ZhengHong Wei; SongQiao Wen; LiXing Zhu
- Book ID
- 107347955
- Publisher
- SP Science China Press
- Year
- 2009
- Tongue
- English
- Weight
- 214 KB
- Volume
- 52
- Category
- Article
- ISSN
- 1674-7283
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
Selection of Value-at-Risk models
β
Mandira Sarma; Susan Thomas; Ajay Shah
π
Article
π
2003
π
John Wiley and Sons
π
English
β 128 KB
A proposal for evaluating value-at-risk
β
Marta Korczak
π
Article
π
2000
π
Springer US
π
English
β 98 KB
An Empirical Investigation of the Assump
β
John C. Butler; James S. Dyer; Jiammin Jia
π
Article
π
2005
π
Springer
π
English
β 466 KB
Empirical likelihood-based inference in
β
He Qixiang; Zheng Ming
π
Article
π
2005
π
SP Editorial Committee of Applied Mathematics - A
π
English
β 372 KB
A Conditional Value-at-Risk Based Inexac
β
L. G. Shao; X. S. Qin; Y. Xu
π
Article
π
2011
π
Springer Netherlands
π
English
β 483 KB
A Study of Value-at-Risk Based on M-Esti
β
Farhat Iqbal; Kanchan Mukherjee
π
Article
π
2011
π
John Wiley and Sons
π
English
β 119 KB
π 2 views
## ABSTRACT In this paper, we investigate the performance of a class of Mβestimators for both symmetric and asymmetric conditional heteroscedastic models in the prediction of valueβatβrisk. The class of estimators includes the least absolute deviation (LAD), Huber's, Cauchy and Bβestimator, as well