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Development of a random-forest-copula-factorial analysis(RFCFA)method for predicting propagation between meteorological and hydrological drought

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National Science Open 2024年第1期3卷 6-27页

作者： Hao Wang Yongping Li Guohe Huang Quan Zhang Yuan Ma Yangfeng Li State Key Joint Laboratory of Environmental Simulation and Pollution Control School of EnvironmentBeijing Normal UniversityBeijing 100875China Institute for Energy Environment and Sustainable CommunitiesUniversity of ReginaRegina Sask S4S 0A2Canada

In the context of global climate warming,the propagation of meteorological drought(MD)may aggravate the devastating impact of hydrological drought(HD)on water security and sustainable development.There are challenges in accurately predicting the propagation of drought and effectively quantifying the effects of uncertainty,especially in data-deficient regions.In this study,a novel method called RFCFA is developed through integrating random forest(RF),copula,and factorial analysis(FA)into a general framework as well as applied to the Aral Sea Basin(a typical arid and data-scarce basin in Central Asia)under considering the impact of climate change.Several findings can be summarized:(1)the projected future drought propagation probability of ASB is 39.2%,which is about 8%higher than historical level;(2)drought propagation is mainly affected by mean climate condition,catchment characteristics(i.e.,elevation,LUCC,and slope),and human activities(i.e.,irrigation and reservoir operation);(3)the lower propagation probability in spring is expected under SSP1-2.6 due to increased snow meltwater,and the drought propagation probability in autumn is the highest(reaching 45.4%)under the influence of reservoir operation;(4)the combined effects of meteorological conditions and agricultural irrigation can lead to a higher probability of future propagation in the upper river basin in summer.Findings are valuable for predicting drought propagation risk,revealing main factors and inherent uncertainties,as well as providing support for drought management and disaster prevention.

关键词： rought propagation random forest copula factorial analysis climate change Aral Sea Basin

Joint Probability Analysis and Prediction of Sea Ice Conditions in Liaodong Bay

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Journal of Ocean University of China 2024年第1期23卷 57-68页

作者： LIAO Zhenkun DONG Sheng TAO Shanshan HUA Yunfei JIA Ning College of Engineering Ocean University of ChinaQingdao 266100China Shuifa Planning and Design Co. Ltd.Jinan 250100China National Hazards Mitigation Service Beijing 100194China

Sea ice conditions in Liaodong Bay of China are often described by sea ice grades,which classify annual sea ice conditions based on the annual maximum sea ice thickness(AM-SIT)and annual maximum floating ice extent(AM-FIE).The joint probability distribution of AM-SIT and AM-FIE was established on the basis of their data pairs from 1949/1950 to 2019/2020 in Liaodong Bay.The joint intensity index of the sea ice condition in the current year is calculated,and the joint classification criteria of the sea ice grades in past years are established on the basis of the joint intensity index series.A comparison of the joint criteria with the 1973 and 2022 criteria revealed that the joint criteria of the sea ice grade match well,and the joint intensity index can be used to quantify the sea ice condition over the years.A time series analysis of the sea ice grades and the joint intensity index sequences based on the joint criteria are then performed.Results show a decreasing trend of the sea ice condition from 1949/1950 to 2019/2020,a mutation in 1990/1991,and a period of approximately 91 years of the sea ice condition.In addition,the Gray-Markov model(GMM)is applied to predict the joint sea ice grade and the joint intensity index of the sea ice condition series in future years,and the error between the results and the actual sea ice condition in 2020/2021 is small.

关键词： sea ice grade ice thickness floating ice extent Liaodong Bay copula

A copula-based approximation to Markov chains

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Science China Mathematics 2022年第3期65卷 623-654页

作者： Zhengyong Zhou Jiehua Xie Jingping Yang Department of Financial Mathematics Peking UniversityBeijing 100871China School of Statistics Jiangxi University of Finance and EconomicsNanchang 330013China Key Laboratory of Mathematical Economics and Quantitative Finance Ministry of EducationBeijing 100871China

The Markov chain is well studied and widely applied in many areas.For some Markov chains,it is infeasible to obtain the explicit expressions of their corresponding finite-dimensional distributions and sometimes it is time-consuming for computation.In this paper,we propose an approximation method for Markov chains by applying the copula theory.For this purpose,we first discuss the checkerboard copula-based Markov chain,which is the Markov chain generated by the family of checkerboard copulas.This Markov chain has some appealing properties,such as self-similarity in copulas and having explicit forms of finite-dimensional distributions.Then we prove that each Markov chain can be approximated by a sequence of checkerboard copula-based Markov chains,and the error bounds of the approximate distributions are provided.Employing the checkerboard copula-based approximation method,we propose a sufficient condition for the geometric β-mixing of copula-based Markov chains.This condition allows copulas of Markov chains to be asymmetric.Finally,by applying the approximation method,analytical recurrence formulas are also derived for computing approximate distributions of both the first passage time and the occupation time of a Markov chain,and numerical results are listed to show the approximation errors.

关键词： Markov chain copula checkerboard copula-based Markov chain ■-convergence β-mixing property

On a Compound Poisson Risk Model Perturbed by Brownian Motion with Variable Premium and Tail Dependence between Claims Amounts and Inter-Claim Time

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Open Journal of Statistics 2024年第1期14卷 1-37页

作者： Delwendé Abdoul-Kabir Kafando Kiswendsida Mahamoudou Ouedraogo Pierre Clovis Nitiema Department of Mathematics University Joseph Ki-Zerbo Ouagadougou Burkina Faso Department of Mathematics University Ouaga 3s Ouagadougou Burkina Faso Department of Mathematics University Thomas-Sankara Ouagadougou Burkina Faso

This paper considers the compound Poisson risk model perturbed by Brownian motion with variable premium and dependence between claims amounts and inter-claim times via Spearman copula. It is assumed that the insurance company’s portfolio is governed by two classes of policyholders. On the one hand, the first class where the amount of claims is high, and on the other hand, the second class where the amount of claims is low, this difference in claim amounts has significant implications for the insurance company’s pricing and risk management strategies. When policyholders are in the first class, they pay an insurance premium of a constant amount c1 and when they are in the second class, the premium paid is a constant amount c2 such that c1 > c2. The nature of claims (low or high) is measured via random thresholds . The study in this work will focus on the determination of the integro-differential equations satisfied by Gerber-Shiu functions and their Laplace transforms in the risk model perturbed by Brownian motion with variable premium and dependence between claims amounts and inter-claim times via Spearman copula. .

关键词： Gerber-Shiu Function copula Integro-Differential Equation Laplace Trans-form Brownian Motion

金融时变高阶矩建模及其风险测度研究:基于收益率分解的方法

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数理统计与管理 2024年第1期43卷 177-190页

作者：柯睿郝斌谭常春合肥工业大学经济学院安徽合肥230009

本文基于收益率分解方法,将收益率表示成符号部分和绝对值部分的乘积形式,通过对符号部分、绝对值部分以及这两部分间的相关性分别进行时变性设定,构建了动态收益率分解(DRD)模型来刻画收益率的高阶矩动态特征。该模型能灵活地设置条件... 详细信息

本文基于收益率分解方法,将收益率表示成符号部分和绝对值部分的乘积形式,通过对符号部分、绝对值部分以及这两部分间的相关性分别进行时变性设定,构建了动态收益率分解(DRD)模型来刻画收益率的高阶矩动态特征。该模型能灵活地设置条件偏度和条件峰度的时变演化方式,还能通过对符号部分和绝对值部分间相关性的时变copula设定来刻画收益率变动的非线性特征,因而使得该模型对收益率的预测具有优势。本文还利用上证综合指数和深证成份指数的收益率数据对DRD模型进行了实证研究,结果表明:两种股指收益率序列均表现出了显著的高阶矩动态特征,条件偏度和条件峰度存在一定程度的波动聚集特征。相较于其他时变高阶矩模型,DRD模型不仅具有更好的样本内模型拟合效果,而且在样本外的风险价值预测和经济价值评价等方面均表现出一定的优越性。

关键词：时变高阶矩收益率分解 copula 风险测度

Joint probability analysis of water and sediment and predicting sediment load based on copula function

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International Journal of Sediment Research 2022年第5期37卷 639-652页

作者： Haoyu Jin Xiaohong Chen Ruida Zhong Yingjie Pan Tongtiegang Zhao Zhiyong Liu Xinjun Tu School of Civil Engineering Sun Yat-sen University Guangdong Engineering Technology Research Center of Water Security Regulation and Control for Southern China Sun Yat-sen University Key Laboratory of Water Cycle and Water Security in Southern China of Guangdong High Education Institute Sun Yat-sen University Dongjiang Water Source Project Management Division of Shenzhen

The Jinsha River comprises the upper reaches of the Yangtze River, which is the river section with the highest sediment content. Monitoring of sediment transport in the Jinsha River is done to the guarantee for the normal operation of the Three Gorges Reservoir. In the current study, a copula function was used to do a joint probability analysis of the water and sediment in the Jinsha River Basin(JRB), further a sediment load prediction model based on the copula function also was constructed. The results show that the average annual flow from 2001 to 2018 at the outlet of the Jinsha River(Yibin station) is about60.43 billion m3, and the average annual sediment load is about 58.82 million t. The linear correlation coefficient between annual flow and annual sediment load is 0.28. The best marginal distribution for annual flow and sediment load is Pearson Type Three(PE3) and Generalized Normal(GNO), respectively,and the best fit for the combined distribution of the two variables is the Frank copula function. The synchronous probability of water and sediment occurrence is 0.459, and the asynchronous probability is0.541. Based on the copula prediction model, the sediment load can be effectively simulated, and the correlation coefficient between the simulated sequence and the measured sequence reached 0.93. The current study provides important significance for the analysis of water and sediment in the JRB, which is beneficial to the management of Three Gorges Reservoir sediment discharge in the upstream and downstream.

关键词： Marginal distribution Joint distribution copula Flow Sediment load Jinsha River Basin (JRB)

Tracking Interval to Select an Optimal Model Among Non-nested copula Functions

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Communications in Mathematics and Statistics 2022年第1期10卷 85-99页

作者： Parisa Torkaman Department of Statistics Faculty of Mathematical Sciences and StatisticsMalayer UniversityMalayerIran

One of the important issues in order to survey multivariate distribution or model dependency structure between interested variables is finding the proper copula function.Extensive studies have been done based on Akaike information criterion(AIC),copula information criterion(CIC),and pseudo-likelihood ratio and fitness test of the copula function.The previous methods of selecting copula functions when the sample size is too small are not satisfactory.Therefore,our method in this paper is based on tracking interval for the parametric copula function which is obtained using expected Kullback–Leibler risk between the two proposed non-nested parametric copulamodel.It can be find that optimal parametric copula between proposed copula functions in a good level of significance.Finally,efficiency and capability of our method using simulation and applied example have been shown.

关键词： copula Tracking interval Expected Kullback-Leibler risk

变暖环境下华北地区农业气象灾害风险评估Ⅲ：京津冀地区高温事件持续日数与强度联合重现期分析

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中国农业气象 2024年第7期 798-808页

作者：杨雨潇赵峻池张琪刘忠贤俞昕南京信息工程大学生态与应用气象学院江苏省农业气象重点实验室

基于京津冀地区27个气象站1960-2019年逐日最高气温数据识别高温事件，综合考虑高温事件持续日数和高温强度（≥35℃积温量）两个特征，利用copula函数拟合高温事件两个特征的联合累积概率分布，以分析京津冀地区高温事件的重现期特征... 详细信息

基于京津冀地区27个气象站1960-2019年逐日最高气温数据识别高温事件，综合考虑高温事件持续日数和高温强度（≥35℃积温量）两个特征，利用copula函数拟合高温事件两个特征的联合累积概率分布，以分析京津冀地区高温事件的重现期特征。结果表明：京津冀地区高温事件发生频次、严重程度的分布呈现南高北低，但发生频次、持续日数和日均强度的增幅呈现南低北高；对高温事件持续日数进行边缘分布拟合，POISS函数在所有站点效果均为最优；对高温强度进行拟合时，GEV函数在更多的站点效果最好；将高温持续日数和强度进行二维联合，应用最多的copula函数为Symmetrised Joe-Clayton函数，其次为Frank函数；研究区持续5d以上的高温事件重现期多在5a一遇以上，北部地区达百年一遇以上。

关键词：高温事件重现期 copula 京津冀

基于CoVaR和MES的系统性风险预测及其在我国股市中的应用

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基于CoVaR和MES的系统性风险预测及其在我国股市中的应用

作者：徐彩凤北方民族大学

学位级别：硕士

2008年的全球金融危机是由于美国次贷危机所引发的系统性风险,这场危机迅速蔓延到全球金融市场,导致许多金融机构破产,引起了全球范围内的经济危机。因此,政府需要及时进行系统性风险的研究和监测,保护金融体系的稳定和可持续发展。首先... 详细信息

2008年的全球金融危机是由于美国次贷危机所引发的系统性风险,这场危机迅速蔓延到全球金融市场,导致许多金融机构破产,引起了全球范围内的经济危机。因此,政府需要及时进行系统性风险的研究和监测,保护金融体系的稳定和可持续发展。首先,本文以上证指数与香港恒生指数以及上证指数与银行指数为研究对象,融合copula、广义自回归得分模型（Generalized Autoregressive Score,GAS）以及ARMA-GARCH模型,构建copula-GAS-ARMA-GARCH模型对我国股市的系统性风险进行预测。同时,结合copula-GAS-ARMA-GARCH模型和极端相依模型,基于尾部相依系数（Tail Dependence Coefficient,TDC）和残差相依系数（Coefficient of Residual Dependence,CRD）考察了上述指数间极端相依性的动态变化趋势。结果表明:以2008年3月为界,这之前的上证指数与香港恒生指数的负对数收益率间一直表现为渐近独立,但尾部呈现出正的残差相依,之后两个指数的负对数收益率之间出现渐近相依。在2007年1月至2023年1月期间,上证指数与银行指数负对数收益率间是渐近相依占主导地位。为进行对比,本文还使用t-copula-GAS模型对TDC进行估计,发现其缺乏时变性。此外,通过对我国股市系统性风险CoVaR进行预测,发现在金融危机期间,负对数收益率超出CoVaR预测的情况也没有出现聚集现象,各指数负对数收益率的违规率都在10%左右,在可接受范围内。其次,选取2007年1月至2023年1月上证指数、银行指数和保险指数的日收盘价数据,本文使用最小非对称加权平方（Least Asymmetrically Weighted Squares,LAWS）估计和基于分位数估计方法计算了上证指数负对数收益率极端期望分位数值和置信区间,并进行动态预测,且计算了银行指数和保险指数对系统性风险的边际贡献度。研究结果表明:基于上述两种方法计算出的上证指数负对数收益率极端期望分位数值,与使用Weissman极端分位数估计量估计的极端分位数相差不大,但使用Drees（2003）的方法和基于分位数估计构建的置信区间比基于LAWS方法计算的置信区间宽,说明基于LAWS方法精确度更高。在极端水平τ'_n=0.999下,本文基于LAWS和分位数估计对上证指数负对数收益率进行了滚动预测,发现LAWS的估计超出实际值与预期超出实际值相差个数比基于分位数估计的少,进一步说明了基于LAWS估计的效果好。此外,本文基于期望分位数估计了边际期望损失,以此来分析银行指数与保险指数对系统性风险的边际贡献度,发现银行指数对系统性风险的贡献大于保险指数。

关键词：系统性风险条件在险价值边际期望损失 copula 期望分位数