Autopsy
发表于 2025-3-21 18:01:27
书目名称Mathematical and Statistical Methods for Actuarial Sciences and Finance影响因子(影响力)<br> http://impactfactor.cn/2024/if/?ISSN=BK0626718<br><br> <br><br>书目名称Mathematical and Statistical Methods for Actuarial Sciences and Finance影响因子(影响力)学科排名<br> http://impactfactor.cn/2024/ifr/?ISSN=BK0626718<br><br> <br><br>书目名称Mathematical and Statistical Methods for Actuarial Sciences and Finance网络公开度<br> http://impactfactor.cn/2024/at/?ISSN=BK0626718<br><br> <br><br>书目名称Mathematical and Statistical Methods for Actuarial Sciences and Finance网络公开度学科排名<br> http://impactfactor.cn/2024/atr/?ISSN=BK0626718<br><br> <br><br>书目名称Mathematical and Statistical Methods for Actuarial Sciences and Finance被引频次<br> http://impactfactor.cn/2024/tc/?ISSN=BK0626718<br><br> <br><br>书目名称Mathematical and Statistical Methods for Actuarial Sciences and Finance被引频次学科排名<br> http://impactfactor.cn/2024/tcr/?ISSN=BK0626718<br><br> <br><br>书目名称Mathematical and Statistical Methods for Actuarial Sciences and Finance年度引用<br> http://impactfactor.cn/2024/ii/?ISSN=BK0626718<br><br> <br><br>书目名称Mathematical and Statistical Methods for Actuarial Sciences and Finance年度引用学科排名<br> http://impactfactor.cn/2024/iir/?ISSN=BK0626718<br><br> <br><br>书目名称Mathematical and Statistical Methods for Actuarial Sciences and Finance读者反馈<br> http://impactfactor.cn/2024/5y/?ISSN=BK0626718<br><br> <br><br>书目名称Mathematical and Statistical Methods for Actuarial Sciences and Finance读者反馈学科排名<br> http://impactfactor.cn/2024/5yr/?ISSN=BK0626718<br><br> <br><br>
heart-murmur
发表于 2025-3-22 00:07:07
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迅速成长
发表于 2025-3-22 02:04:46
An Empirical Investigation of Heavy Tails in Emerging Markets and Robust Estimation of the Pareto Ttional Threshold Accepting-VaR based algorithm (TAVaR) for optimally estimating the Pareto tail index. A Monte Carlo bias estimation analysis is also carried out by comparing our proposed methodology with the Hill estimator and a variant of it.
Antimicrobial
发表于 2025-3-22 06:53:55
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旁观者
发表于 2025-3-22 11:01:23
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珍奇
发表于 2025-3-22 14:52:42
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观点
发表于 2025-3-22 17:48:54
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Mangle
发表于 2025-3-23 01:08:37
,Conditional Quantile Estimation for Linear ARCH Models with MIDAS Components,MIDAS (Q–ARCH–MIDAS), allows to benefit from the information coming from variables observed at different frequencies with respect to that of the variable of interest. Moreover, the QR context brings additional advantages, such as the robustness to the presence of outliers and the lack of distributional assumptions.
训诫
发表于 2025-3-23 04:10:32
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lymphoma
发表于 2025-3-23 08:17:14
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