摘要翻译:
我们收集了关于二元正态分布的众所周知的和不太为人所知的事实,并将它们翻译成copula语言。此外,我们还证明了二元正规copula的一个非常普遍的公式,计算了Gini的gamma,并给出了对角上的改进的界和近似。
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英文标题:
《The Bivariate Normal Copula》
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作者:
Christian Meyer
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最新提交年份:
2009
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分类信息:
一级分类:Mathematics 数学
二级分类:Probability 概率
分类描述:Theory and applications of probability and stochastic processes: e.g. central limit theorems, large deviations, stochastic differential equations, models from statistical mechanics, queuing theory
概率论与随机过程的理论与应用:例如中心极限定理,大偏差,随机微分方程,统计力学模型,排队论
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一级分类:Quantitative Finance 数量金融学
二级分类:Computational Finance 计算金融学
分类描述:Computational methods, including Monte Carlo, PDE, lattice and other numerical methods with applications to financial modeling
计算方法,包括蒙特卡罗,偏微分方程,格子和其他数值方法,并应用于金融建模
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英文摘要:
We collect well known and less known facts about the bivariate normal distribution and translate them into copula language. In addition, we prove a very general formula for the bivariate normal copula, we compute Gini's gamma, and we provide improved bounds and approximations on the diagonal.
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PDF链接:
https://arxiv.org/pdf/0912.2816


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