Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Zoulikha Kaid"'
Autor:
Zouaoui Chikr Elmezouar, Fatimah Alshahrani, Ibrahim M. Almanjahie, Salim Bouzebda, Zoulikha Kaid, Ali Laksaci
Publikováno v:
AIMS Mathematics, Vol 9, Iss 3, Pp 5550-5581 (2024)
Analyzing the real impact of spatial dependency in financial time series data is crucial to financial risk management. It has been a challenging issue in the last decade. This is because most financial transactions are performed via the internet and
Externí odkaz:
https://doaj.org/article/ccf30683cd48413ea84ffbb8ea3eb34d
Publikováno v:
Axioms, Vol 13, Iss 10, p 678 (2024)
The main aim of this paper is to consider a new risk metric that permits taking into account the spatial interactions of data. The considered risk metric explores the spatial tail-expectation of the data. Indeed, it is obtained by combining the ideas
Externí odkaz:
https://doaj.org/article/5a77fa31b38249509aaeea667ada586f
Publikováno v:
Entropy, Vol 26, Iss 9, p 798 (2024)
This paper treats the problem of risk management through a new conditional expected shortfall function. The new risk metric is defined by the expectile as the shortfall threshold. A nonparametric estimator based on the Nadaraya–Watson approach is c
Externí odkaz:
https://doaj.org/article/88d40122d5dc46b99c7deffc189a661a
Publikováno v:
Symmetry, Vol 16, Iss 7, p 928 (2024)
This paper deals with the problem of financial risk management using a new expected shortfall regression. The latter is based on the expectile model for financial risk-threshold. Unlike the VaR model, the expectile threshold is constructed by an asym
Externí odkaz:
https://doaj.org/article/1f5c95d08fd54b9ba234b294c82cfa04
Autor:
Zouaoui Chikr Elmezouar, Fatimah Alshahrani, Ibrahim M. Almanjahie, Zoulikha Kaid, Ali Laksaci, Mustapha Rachdi
Publikováno v:
Axioms, Vol 12, Iss 7, p 613 (2023)
Analyzing the co-variability between the Hilbert regressor and the scalar output variable is crucial in functional statistics. In this contribution, the kernel smoothing of the Relative Error Regression (RE-regression) is used to resolve this problem
Externí odkaz:
https://doaj.org/article/77c1aef31f9142e19e7572c7bd333675
Publikováno v:
Mathematics, Vol 10, Iss 23, p 4508 (2022)
In this paper, we study the nonparametric estimation of the expected shortfall regression when the exogenous observation is functional. The constructed estimator is obtained by combining the double kernels estimator of both conditional value at risk
Externí odkaz:
https://doaj.org/article/3ff55c8d84554f6eb6ab1606602ca90a
Autor:
Fatimah Alshahrani, Ibrahim M. Almanjahie, Zouaoui Chikr Elmezouar, Zoulikha Kaid, Ali Laksaci, Mustapha Rachdi
Publikováno v:
Mathematics, Vol 10, Iss 20, p 3919 (2022)
In this article, we study the problem of the recursive estimator of the expectile regression of a scalar variable Y given a random variable X that belongs in functional space. We construct a new estimator and study the asymptotic properties over a ge
Externí odkaz:
https://doaj.org/article/12a97e3de5d0488984c81d1be65438c4
Publikováno v:
PeerJ, Vol 9, p e11719 (2021)
Predicting the yearly curve of the temperature, based on meteorological data, is essential for understanding the impact of climate change on humans and the environment. The standard statistical models based on the big data discretization in the finit
Externí odkaz:
https://doaj.org/article/fa0378064643499aa80120478fdda102
Publikováno v:
Mathematics, Vol 10, Iss 6, p 902 (2022)
In this study, the problem of conditional density estimation of a scalar response variable, given a functional covariable, is considered. A new estimator is proposed by combining the k-nearest neighbors (k-N-N) procedure with the local linear approac
Externí odkaz:
https://doaj.org/article/973cc2e1c5c044808a458e1bb139f25c
Autor:
Rachdi, Zouaoui Chikr Elmezouar, Fatimah Alshahrani, Ibrahim M. Almanjahie, Zoulikha Kaid, Ali Laksaci, Mustapha
Publikováno v:
Axioms; Volume 12; Issue 7; Pages: 613
Analyzing the co-variability between the Hilbert regressor and the scalar output variable is crucial in functional statistics. In this contribution, the kernel smoothing of the Relative Error Regression (RE-regression) is used to resolve this problem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::31ee20eb13a7f21ff756385401423488