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Study on the Moment and Quantile Functions of Conditional Model of Bivariate Markov Time Series of Order 1

机译:一匹伐地序命令1的矩定量函数研究

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Both of temporal dependence and contemporaneous dependence are primary dependence relationship of time series vector. In economic and financial applications, one is often interested in estimating or forecasting certain characteristics of a time series given known conditions. Considering both classes of dependence and constructing conditional dependence model of bivariate Markov time series of order 1. Based on this conditional model, the moment and quantile functions of bivariate vector and univariate series are studied and a simulating way for the q th conditional quantile of bivariate vector is proposed. They are useful of measure of portfolio risk in the risk management.
机译:时间依赖性和同期依赖性是时间序列向量的主要依赖关系。在经济和财务应用中,人们往往有兴趣估计或预测定期序列的某些特征。考虑到一类依赖性和构建双马尔可夫时间序列的条件依赖模型。基于该条件模型,研究了一体化矢量和单变量系列的瞬间和量子函数,并为一体化的Q Th有条件定量的模拟方式矢量提出。它们有助于衡量风险管理中的投资组合风险。

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