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brussels, morocco
It's currently 1:26 AM here
Joined August 17, 2014
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Younès M.
@Statitical
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brussels, morocco
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Statistical Analysis
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Education
Doctorate in statistics
(2 years)
Engineer of statistics
(3 years)
Publications
Mixed Distributions for Loss Severity Modeling with zeros in the Operational Risk losses
international Journal of applied mathematics and statistics
Many events have contributed to the recognition of operational risk as a major problem by banks and their regulators. Basel Committee on Banking Supervision (BCBS) adopted two innovative features in its accord of 2004. First, it recognized operational risk as a distinct risk beside credit and market risks. Second, the methodologies proposed to calculate capital charges for the three types of risk become more risk-sensitive. Indeed, the advanced measurement approach aims to permit to banks to take into accou
A mean-reverting model of the short-term interbank interest rate in the Moroccan interbank money market
Journal of Finance and Investment Analysis
Modeling short-run interest rate is of primary importance for all participants in financial markets. In this paper, we attempt to model short-run interbank interest rate by the well known Ornstein-Uhlenbeck model called also the mean-reverting model. The results show that the speed of reversion is high and that the mean-reverting level is below the key rate and that the estimated volatility of the interbank daily interest rate r, when this variable is assumed to be governed by an OU model, is below the hist
Zero-modified discrete distributions for Operational Risk modelling
Journal of Risk Finance
In this article, we aim to introduce the zero-modified distributions in the calculation of operational Value-at-Risk. This kind of distributions is preffered when excess of zeroes is observed. In operational risk, this phenomenon may be due to the scarcity of data, the existence of extreme values and/or the threshold from wich banks start to collect losses. In this article, we focus on the analysis of Damage to physical Assets. The results show that basic Poisson distribution underestimates the dispersion,
Poisson regression and Zero-inflated Poisson regression: Application to private insurance
European Actuarial Journal
Modeling event counts is important in many fields. For this purpose, the Poisson regression model is often used. However, this model assumes the equidispersion of the data. Unfortunately, this assumption is often violated in the observed data. The source of overdispersion depends on many situations. When the source of overdispersion is the excess of zeroes, the Zero-inflated Poisson regression model fits better counts data. In this paper, we first review the theoretical framework of Poisson regression and Z
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