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首页> 外文期刊>Journal of Statistical and Econometric Methods >A Three-Step Nonparametric Estimation of Conditional Value-At-Risk Admitting a Location-Scale Model
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A Three-Step Nonparametric Estimation of Conditional Value-At-Risk Admitting a Location-Scale Model

机译:包含位置尺度模型的条件风险值的三步非参数估计

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摘要

Financial institutions owners and regulators are concerned majorly?about risk analysis, Value-at-Risk (VaR) is one of the most popular?and common measures of risk used in finance, measures the down-side?risk and is determined for a given probability level. In this paper, we?consider the problem of estimating conditional Value-at-Risk via the?nonparametric method and have proposed a three-step nonparametric?estimator for conditional Value-at-Risk. The returns are assumed to?have a location-scale model where the function of the error innovations is?assumed unknown. The asymptotic properties of the proposed estimator?were established, a simulation study was also conducted to confirm the?properties. Application to real data was carried out, TOTAL stocks?quoted on the Nigerian Stock Exchange using daily closing prices for?covering the period between January 02, 2008 to December 29, 2017?trading days was used to illustrate the applicability of the estimator.
机译:金融机构所有者和监管机构主要关注风险分析,风险价值(VaR)是最流行的金融风险度量方法之一,用于衡量下行风险,并针对特定风险确定概率水平。在本文中,我们考虑了通过非参数方法估算条件风险的问题,并提出了一个三步的条件风险估算器。假定收益具有一个位置尺度模型,其中错误创新的功能被假定为未知。建立了拟议估计量的渐近性质,并进行了仿真研究以确认其性质。进行了真实数据的应用,使用每日收盘价(包括2008年1月2日至2017年12月29日之间的交易日)在尼日利亚股票交易所报价的TOTAL股票,以说明该估算器的适用性。

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