基于Copula函数我国林业经济发展与气候之间的关系研究

我国林业经济在国民经济发展中有着重要的地位,森林与气候之间也有着密切的关系。通过历史数据基于Copula函数模型验证林业经济发展与气温、降水量、湿度与日照数等气候因素之间的相关关系,林业生产总值与气温正相关,与湿度、日照数负相关。当我们认识到林业经济总产值与气温、降水量、湿度、日照数之间的相依关系和相依结构,就可以采取相应的措施。这将会对制定宏观经济发展规划与森林资源开发战略,具有一定的指导与实践意义。     

Stochastic model specification search for Gaussian and partial non-Gaussian state space models

Model specification for state space models is a difficult task as one has to decide which components to include in the model and to specify whether these components are fixed or time-varying. To this aim a new model space MCMC method is developed in this paper. It is based on extending the Bayesian variable selection approach which is usually applied to variable selection in regression models to state space models. For non-Gaussian state space models stochastic model search MCMC makes use of auxiliary mixture sampling. We focus on structural time series models including seasonal components, trend or intervention. The method is applied to various well-known time series.     

异体内部混合经济论

量子力学的鼻祖薛定谔关于生命的三大猜想启示我们:混合是文明演化的真正奥秘,通过融入体制外资本异体内部混合对国有资本进行人格化改造,是国有企业实现创新力与控制力统一、国资保值增值的现实选择。     

基于经济资本的我国保险公司投资风险限额配置研究

投资风险限额管理是保险公司对投资风险进行管理的重要手段,是保险公司建立有效风险管理体系不可或缺的组成部分。保险公司投资风险限额管理主要包括投资风险限额配置、风险限额监控和风险限额动态调整三个环节,其中风险限额配置是整个风险限额管理流程的基础。运用GARCH模型和GJR模型,并结合Copula理论,探讨了投资风险限额配置的方法,通过实证分析证实投资组合之间存在分散化效应,各投资风险限额之和大于总风险限额,并得出投资风险限额优化配置模型调整资产配置,可以显著提高保险公司投资绩效。     

沥青混合料拌和质量的控制措施

沥青混合料拌和质量的控制措施主要着重于原材料的质量、拌和机的选择和改进、混合料配比的优化及计量的准确稳定、温度与拌和时间的控制等几个方面。     

A multivariate Poisson mixture model for marketing applications

This paper describes a multivariate Poisson mixture model for clustering supermarket shoppers based on their purchase frequency in a set of product categories. The multivariate nature of the model accounts for cross-selling effects between the purchases made in different product categories. However, for computational reasons, most multivariate approaches limit the covariance structure by including just one common interaction term, or by not including any covariance at all. Although this reduces the number of parameters significantly, it is often too simplistic as typically multiple interactions exist on different levels. This paper proposes a theoretically more complete variance/covariance structure of the multivariate Poisson model, based on domain knowledge or preliminary statistical analysis of significant purchase interaction effects in the data. Consequently, the model does not contain more parameters than necessary, whilst still accounting for the existing covariance in the data. Practically, retail category managers can use the model to devise customized merchandising strategies.     

Estimation of the scale matrix of a multivariate t-model under entropy loss

This paper deals with the estimation of the scale matrix of a multivariatet-model with unknown location vector and scale matrix to improve upon the usual estimators based on the sample sum of product matrix. The well-known results of the estimation of the scale matrix of the multivariate normal model under the assumption of entropy loss function have been generalized to that of a multivariatet-model. The paper is based on the first author’s unpublished Ph.D. dissertation ‘Estimation of the Scale Matrix of a Multivariate T-model’, University of Western Ontario, Canada. Present address: School of Mathematics and Statistics, The University of Sydney, NSW 2006, Australia.     

Prediction of the next hypercalcemia free period: application of random effect models with selection on first event

The length of repeated hypercalcemia free periods of patients with bone metastasis of breast cancer with at least one hypercalcemic event was modelled according to a generalized linear mixed model formulated in terms of transition probabilities and according to a latent variable model. In the former case the periods were assumed to be lognormally distributed with two variance components (patients and residue). In the latter case the conditional intensity given a patient was assumed to be the intensity of the Weibull distribution, while the random patient effect (frailty) was assumed to be drawn from a gamma distribution. In both cases the selection of only patients with at least one hypercalcemic event was taken into consideration. In both models the variance of the patient effect turned out to be negligible. For the second and later periods the Weibull appeared to fit better than the lognormal model. For the first period there was almost no information available.     

人民币外汇市场间不对称汇率变动的实证研究

现有关于人民币汇率各市场间关系的研究一般是基于多元GARCH模型,探讨各市场间的线性相关关系,未能考虑各市场间汇率变动可能存在的"不对称效应":面临正(反)向的较大冲击时,各市场汇率变动表现出同步性;而面临反(正)向的较大冲击时,各市场汇率变动不同步。本文运用SJC-Copula-MGARCH模型对人民币汇率境内SPOT市场、境内DF市场和境外NDF市场之间的相依关系进行实证分析,发现境内汇率市场(SPOT市场和DF市场)和境外NDF市场间的联系仍较弱;SPOT-DF市场在面临大的正冲击和负冲击时均表现出较强的联动性,而SPOT-NDF市场和DF-NDF市场在面临大的冲击时汇率变动表现出"不对称效应":在面临大的正冲击(人民币相对贬值)时,境内汇率市场和境外NDF市场汇率变动不同步,当面临大的负冲击(人民币相对升值)时,境内汇率市场和境外NDF市场汇率变动表现出较强的同步性。本文进一步分析了上述"不对称效应"的经济机理,探讨了其经济学含义。     

中美主要金融市场相关结构及风险传导路径研究——基于Copula理论与方法

金融危机背景下的股市表现出更加复杂的动荡性,本文在传统GARCH模型的基础上引入了风险值对收益率的影响因素,运用GARCH-M模型来刻画股票收益率序列边缘分布,通过构建GARCH-M-t边缘分布过滤模型获取收益率残差序列,最后采用Copula函数对边缘分布拟合后的残差序列建模构建出Copula-GARCH-M-t相关结构模型。经过参数估计及多种Copula函数的拟合优度检验,最终成功刻画出中美金融市场五大证券交易中心股票收益率之间的相关结构模型。通过秩相关系数、尾部相关系数等相关性度量工具对中美两国金融市场的相关性进行分析,最后通过对不同股票市场之间的尾部相关性分析确定两国金融市场之间风险传导路径。