Assessment of Seismic Loss Dependence Using Copula

The catastrophic nature of seismic risk is attributed to spatiotemporal correlation of seismic losses of buildings and infrastructure. For seismic risk management, such correlated seismic effects must be adequately taken into account, since they affect the probability distribution of aggregate seismic losses of spatially distributed structures significantly, and its upper tail behavior can be of particular importance. To investigate seismic loss dependence for two closely located portfolios of buildings, simulated seismic loss samples, which are obtained from a seismic risk model of spatially distributed buildings by taking spatiotemporally correlated ground motions into account, are employed. The characterization considers a loss frequency model that incorporates one dependent random component acting as a common shock to all buildings, and a copula‐based loss severity model, which facilitates the separate construction of marginal loss distribution functions and nonlinear copula function with upper tail dependence. The proposed method is applied to groups of wood‐frame buildings located in southwestern British Columbia. Analysis results indicate that the dependence structure of aggregate seismic losses can be adequately modeled by the right heavy tail copula or Gumbel copula, and that for the considered example, overall accuracy of the proposed method is satisfactory at probability levels of practical interest (at most 10% estimation error of fractiles of aggregate seismic loss). The developed statistical seismic loss model may be adopted in dynamic financial analysis for achieving faster evaluation with reasonable accuracy.     

园桥刍议

文章论述了观念中桥的作用及国桥的类型，并对园桥空间的特性及构成进行了探讨。     

Approximating the equilibrium quantity traded and welfare in large markets

We consider the efficient outcome of a canonical economic market model involving buyers and sellers with independent and identically distributed random valuations and costs, respectively. When the number of buyers and sellers is large, we show that the joint distribution of the equilibrium quantity traded and welfare is asymptotically normal. Moreover, we bound the approximation rate. The proof proceeds by constructing, on a common probability space, a representation consisting of two independent empirical quantile processes, which in large markets can be approximated by independent Brownian bridges. The distribution of interest can then be approximated by that of a functional of a Gaussian process. This methodology applies to a variety of mechanism design problems.     

End-Point Estimation for Decreasing Densities: Asymptotic Behaviour of the Penalized Likelihood Ratio

Abstract.  We consider the problem of estimating the modal value of a decreasing density on the positive real line. This has application in several interesting phenomena arising, for example, in renewal theory, and in biased and distance samplings. We use a penalized likelihood ratio-based approach for inference and derive the scale-free universal large sample null distribution of the log-likelihood ratio, using a suitably chosen penalty parameter. We present simulation results and a real data analysis to corroborate our findings, and compare the performance of the confidence sets with the existing results.     

Nonparametric Bayesian Methods for Benchmark Dose Estimation

The article proposes and investigates the performance of two Bayesian nonparametric estimation procedures in the context of benchmark dose estimation in toxicological animal experiments. The methodology is illustrated using several existing animal dose‐response data sets and is compared with traditional parametric methods available in standard benchmark dose estimation software (BMDS), as well as with a published model‐averaging approach and a frequentist nonparametric approach. These comparisons together with simulation studies suggest that the nonparametric methods provide a lot of flexibility in terms of model fit and can be a very useful tool in benchmark dose estimation studies, especially when standard parametric models fail to fit to the data adequately.     

Econometric Analysis of Costing System Components in Rail Rate Regulation

In response to Congressional directive, the Interstate Commerce Commission (ICC) has created a railroad costing system that includes as key components ratios designed to estimate variable costs associated with freight transportation. The estimated variability ratios are used to determine freight surcharges, jurisdictional threshold rates, and basic rail rates in administrative law and federal court proceedings. In this article we assess the quality and reliability of the estimated variability ratios and their components against standards from economic theory and statistical theory and practice. Our work includes reproduction of the naive ICC regressions, updated naive regressions for the latest data set, estimation based on more secure econometric foundations, and sensitivity analyses comparing alternative estimation procedures. Fundamental questions arise concerning the scientific and evidentiary standards that are required for econometric methodology in policy making and regulatory activities.     

Parameter Identification for Drift Fractional Brownian Motions with Application to the Chinese Stock Markets

This article deals with the problem of estimating all the unknown parameters in the drift fractional Brownian motion with discretely sampled data. The estimation procedure is built upon the marriage of the variation method and the ergodic theory. The strong consistencies of these estimators are provided. Moreover, our method and two existing approaches are compared based on the computational running time and the accuracy of estimation via simulation studies. We also apply the proposed method to the real high-frequency financial data within a window of 4 h in the trading day from the Chinese mainland stock market.     

世界原油价格风险度量——基于EGARCH-EVT-t Copula模型

从原油现货市场收益率的特征分析入手,为了更好地描述原油现货市场收益率的尖峰厚尾、偏态和波动集聚等特征,运用EGARCH 对条件波动率进行建模,进而运用极值理论对标准残差序列的尾部分布进行建模,刻画原油现货市场极值风险,同时结合Copula函数和Monte Carlo模拟技术来度量不同持有期相应的VaR值.实证结果表明:原油市场随着置信度的提高和持有期的延长,VaR的绝对值在增大.同时,回测检验结果表明基于EGARCH-EVT-t Copula的模型能够精确有效地度量原油现货市场极端风险.