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  • A Copula Function Approach in Monte Carlo simulation
    The theory of copulas is known to provide a useful tool for modelling dependence in integrated risk management In this paper, we describe how may be used copula methodology for the Monte Carlo Analysis whereas the main emphasis is put on Value-at-Risk as a risk measure In the second part of this paper we show properties more generalised model as measurable space and we show how it is
  • openresearch. lsbu. ac. uk
    This paper investigates the asymmetric conditional dependence between Shanghai and Hong Kong stock index returns, to assess the impact of the recent financial recession on Chinese equity markets using the Copula approach We first propose methods for optimal model selection when constructing the conditional margins The joint conditional distribution is then modeled by the time-varying copula
  • ResearchGate
    Keywords: Banking sector CDS – copulas – financial crises – dependence structure Introduction
  • 關聯結構（copula）在信用風險評量之使用
    在第二節中，我們已強調過利用Copula函數最大的好處是可以將邊際分配及相關性結構分開處理，在市場風險的衡量上，我們可以將視為各種風險因子的報酬率(例如：股價指數、利率或匯率)，此時在配適各風險因子時，並不需要挶限於常態分配的假設條件上，我們可以依實際的市場資料，估計出更
  • www. scienpress. com
    This is the major advantage of using copulas to model and simulate interdependent variables compared to Cholesky decomposition, which is the current standard procedure in Monte Carlo simulations with asset return dependence incorporated A copula method models each variable separately and then measures the relations between variables
  • dauphine. psl. eu
    In this study, we apply five different copulas (Gaussian, Student’s t , Gumbel, Frank, Clayton) to fit joint default distributions These copulas permit to identify main statistical properties of the loan portfolios Gumbel copula is able to capture right tail dependence which is a particularly explored aspect of default dependency





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