A Multiplicative Error Model with Heterogeneous Components for Forecasting Realized Volatility

To forecast realized volatility, this paper introduces a multiplicative error model that incorporates heterogeneous components: weekly and monthly realized volatility measures. While the model captures the long‐memory property, estimation simply proceeds using quasi‐maximum likelihood estimation. This paper investigates its forecasting ability using the realized kernels of 34 different assets provided by the Oxford‐Man Institute's Realized Library. The model outperforms benchmark models such as ARFIMA, HAR, Log‐HAR and HEAVY‐RM in within‐sample fitting and out‐of‐sample (1‐, 10‐ and 22‐step) forecasts. It performed best in both pointwise and cumulative comparisons of multi‐step‐ahead forecasts, regardless of loss function (QLIKE or MSE). Copyright © 2015 John Wiley & Sons, Ltd.     

基于模型突变检测的管道泄漏检测定位方法

为了改进负压波法在管道微弱泄漏的检测和定位中的效果,提出了基于模型突变检测的特征提取和泄漏定位算法。首先运用广义似然比检测理论,建立压力信号变化的统计检验模型,计算广义似然比比率r和下降幅度d作为压力信号突变发生的敏感特征,并通过求得的压力变化时间点进行泄漏定位。针对缓慢泄漏时压力信号变化的特点,提出了相应的改进模型,更精确的求出缓慢泄漏压力信号的下降拐点。实验证明,参数r和d对不同变化类型的压力信号有较好的区分度,利用管道内压力和流量信号的特征值作为神经网络的特征向量可以实现管道的微弱泄漏识别,且基于改进模型的定位算法在缓慢泄漏定位中有较好的定位结果和稳定度。     

Estimating and Predicting the General Random Effects Model

This paper extends the ‘remarkable property’ of Breusch (Journal of Econometrics 1987; 36 : 383–389) and Baltagi and Li (Journal of Econometrics 1992; 53 : 45–51) to the three‐way random components framework. Indeed, like its one‐way and two‐way counterparts, the three‐way random effects model maximum likelihood estimation can be obtained as an iterated generalized least squares procedure through an appropriate algorithm of monotonic sequences of some variance components ratios, θ_i (i = 2, 3, 4). More specifically, a search over θ_iwhile iterating on the regression coefficients estimates β and the other θ_jwill guard against the possibility of multiple local maxima of the likelihood function. In addition, the derivations of related prediction functions are obtained based on complete as well as incomplete panels. Finally, an application to international trade issues modeling is presented. Copyright © 2014 John Wiley & Sons, Ltd.     

基层政府服务质量评估体系建立与实证分析——基于美国波多里奇国家质量奖模型

建设服务型政府己成为我国政府管理的核心价值理念,对基层政府服务质量的评估是确保服务型政府建立的关键。作为政府的服务也是服务业的一个组成部分,因此,根据西方国家工商管理理论评估服务行业服务质量的方法——波多里奇质量奖评奖标准引入到政府服务评估中来,建立政府服务质量评估模型并设计基层政府质量评估调查问卷,得出相应调查数据以便支持假设模型：运用克朗巴哈系数确定调查数据的信度后,再运用路径法进行分析并得出结论——所建模型假设成立。最后,运用因子分析方法得出最终政府服务质量评估权重,完成了整个质量评估体系的建立.     

Bayesian Forecasting for Financial Risk Management,Pre and Post the Global Financial Crisis

Value‐at‐risk (VaR) forecasting via a computational Bayesian framework is considered. A range of parametric models is compared, including standard, threshold nonlinear and Markov switching generalized autoregressive conditional heteroskedasticity (GARCH) specifications, plus standard and nonlinear stochastic volatility models, most considering four error probability distributions: Gaussian, Student‐t, skewed‐t and generalized error distribution. Adaptive Markov chain Monte Carlo methods are employed in estimation and forecasting. A portfolio of four Asia–Pacific stock markets is considered. Two forecasting periods are evaluated in light of the recent global financial crisis. Results reveal that: (i) GARCH models outperformed stochastic volatility models in almost all cases; (ii) asymmetric volatility models were clearly favoured pre crisis, while at the 1% level during and post crisis, for a 1‐day horizon, models with skewed‐t errors ranked best, while integrated GARCH models were favoured at the 5% level; (iii) all models forecast VaR less accurately and anti‐conservatively post crisis. Copyright © 2011 John Wiley & Sons, Ltd.