Browsing by Author "Moutari, Natatou Dodo"

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    The ARMA-APARCH-EVT Models Based on HAC in Dependence Modeling and Risk Assessment of a Financial Portfolio
    (European Journal of Pure and Applied Science, 2021-11-10) Moutari, Natatou Dodo; Hassane, Abba Mallam; Diakarya, Barro
    Multivariate modeling of dependence and its impact on risk assessment remains a major concern for financial institutions. Thus, the copula model, in particular Archimedean hierarchical copulas (HAC) appears as a promising alternative, capable to precisely capture the structure of dependence between financial variables. This study aims to widen the sphere of practical applicability of the HAC model combined with the ARMA-APARCH volatility forecast model and the extreme values theory (EVT). A sequential process of modeling of the VaR of a portfolio based on the ARMA-APARCH-EVT-HAC model is discussed. The empirical analysis conducted with data from international stock market indices clearly illustrates the performance and accuracy of modeling based on HACs.
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    Extremal Copulas and Tail Dependence in Modeling Stochastic Financial Risk
    (European Journal of Pure and Applied Science, 2021-08-05) Mallam, Hassane Abba; Moutari, Natatou Dodo; Diakarya, Barro
    These last years the stochastic modeling became essential in financial risk management related to the ownership and valuation of financial products such as assets, options and bonds. This paper presents a contribution to the modeling of stochastic risks in finance by using both extensions of tail dependence coefficients and extremal dependance structures based on copulas. In particular, we show that when the stochastic behavior of a set of risks can be modeled by a multivariate extremal process a corresponding form of the underlying copula describing their dependence is determined. Moreover a new tail dependence measure is proposed and properties of this measure are established.