Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Sami Mestiri"'
Autor:
Sami Mestiri
Publikováno v:
Data Science in Finance and Economics, Vol 4, Iss 2, Pp 236-248 (2024)
Credit scoring is a useful tool for assessing the capability of customers repayments. The purpose of this paper is to compare the predictive abilities of six credit scoring models: Linear Discriminant Analysis (LDA), Random Forests (RF), Logistic Reg
Externí odkaz:
https://doaj.org/article/c19f0afba1f94c9385f12a859e60b645
Autor:
Sami Mestiri
Publikováno v:
Journal of Smart Economic Growth, Vol 6, Iss 2, Pp 67-77 (2021)
In this paper we use the Bayesian Structural VAR framework to identify the major shock monetary policy shocks in Tunisia over the 1997-2015 and to provide information concerning the evolution of the economy response to these shocks. Compared with pre
Externí odkaz:
https://doaj.org/article/374197c2c62e44ed8f44a82cd5e55927
Autor:
Sami MESTIRI
Publikováno v:
Academic Finance, Vol 13, Iss 1 (2022)
Objective: The purpose of this paper is to demonstrate the effectiveness of the nonparametric GARCH model for the prediction of future Bitcoin prices. Methodology: The parametric GARCH models to characterize the volatility of Bitcoin returns are w
Externí odkaz:
https://doaj.org/article/a6f388bbc06848f0ad8ff44543b90377
Autor:
Abdeljelil Farhat, Sami Mestiri
Publikováno v:
Revstat Statistical Journal, Vol 10, Iss 2 (2012)
In this paper, we review the score test procedure used for testing polynomial covariate effects in a semi parametric additive mixed model. This test is based on the mixed model representation of the smoothing spline estimator of the nonparametric fun
Externí odkaz:
https://doaj.org/article/68d502c318a748f2a7a1a3054a9073b6
Autor:
Sami Mestiri, Abdeljelil Farhat
Publikováno v:
SSRN Electronic Journal.
The purpose of this paper is to apply count data models to predict the number of times a credit applicant will not pay the amount awarded to repay the credit. Poisson models and negative binomial distribution models, taking into account the observed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e8563e8137a7e93151a296d286126e4e
https://doi.org/10.2139/ssrn.3464812
https://doi.org/10.2139/ssrn.3464812
Autor:
Manel Hamdi, Sami Mestiri
Publikováno v:
Economics Bulletin. 34(1):133-143
The paper uses two approaches, semi-parametric logistic regression model and artificial neural networks, to predict bankruptcy of Tunisian companies. A sample of 528 Tunisian firms for the period (1999-2006), was used to investigate the performance o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______645::c6da618c81cdf4302f70984f2327fbe8
http://www.accessecon.com/Pubs/EB/2014/Volume34/EB-14-V34-I1-P15.pdf
http://www.accessecon.com/Pubs/EB/2014/Volume34/EB-14-V34-I1-P15.pdf
Autor:
Manel Hamdi, Sami Mestiri
Publikováno v:
International Journal of Management Science and Engineering Management. 7:200-204
The aim of this paper is to compare the model of logistic regression versus logistic regression with random effects in order to predict the credit risk of Tunisian banks. To do this, a battery of 26 ratios was calculated from balance sheets and incom
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0a79021093c62926a3117279fd7d4b86
https://doi.org/10.1080/17509653.2012.10671224
https://doi.org/10.1080/17509653.2012.10671224
Autor:
Abdejelil Farhat, Sami Mestiri
Publikováno v:
SSRN Electronic Journal.
The aim of this paper is to compare the forecasting financial distress models named the logistic mixed scoring and the semi parametric logistic scoring. Altman scoring variables are used to predict financial situation of Tunisian firms. First, the mi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad6554f678dc703f33956997c7b5fb57
https://doi.org/10.2139/ssrn.1528450
https://doi.org/10.2139/ssrn.1528450
Autor:
Sami Mestiri, Abdejelil Farhat
Publikováno v:
SSRN Electronic Journal.
The mixed linear models are frequently used in the studies of research in medicine and social science. In this article, we presented the method of robust maximum likelihood for estimating the parameters of these models. Since this method is sensitive
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::013efcd95675e8723a91d4d2177d603c
https://doi.org/10.2139/ssrn.1270529
https://doi.org/10.2139/ssrn.1270529