Forecasting the term structures of Treasury and corporate yields using dynamic Nelson-Siegel models

We extend Diebold and Li’s dynamic Nelson-Siegel three-factor model to a broader empirical prospective by including the evaluation of the state space approach and by using nine different ratings for corporate bonds. We find that the dynamic Nelson-Siegel factor AR(1) model outperforms other competitors on the out-of-sample forecast accuracy, especially on the investment-grade bonds for the short-term forecast horizon and on the high-yield bonds for the long-term forecast horizon. The dynamic Nelson-Siegel factor state space model, however, becomes appealing on the high-yield bonds in the short-term forecast horizon, where the factor dynamics are more likely time-varying and parameter instability is more probable in the model specification.     

Scoring rules and survey density forecasts

This article provides a practical evaluation of some leading density forecast scoring rules in the context of forecast surveys. We analyse the density forecasts of UK inflation obtained from the Bank of England’s Survey of External Forecasters, considering both the survey average forecasts published in the Bank’s quarterly Inflation Report, and the individual survey responses recently made available to researchers by the Bank. The density forecasts are collected in histogram format, and the ranked probability score (RPS) is shown to have clear advantages over other scoring rules. Missing observations are a feature of forecast surveys, and we introduce an adjustment to the RPS, based on the Yates decomposition, to improve its comparative measurement of forecaster performance in the face of differential non-response. The new measure, denoted RPS*, is recommended to analysts of forecast surveys.     

A measure of regional influence with the analytic network process

The metropolitan region is commonly defined by a socio-spatial network of urban nodes that are linked in territory and function. Such a network is differentiated by size and dominance of the linked nodes, characterized by physical or virtual flows of a wide-ranging variety. The analytic network process (ANP) is a multi-criteria analytic method that measures the influence or dominance of the nodes in a network with feedback. We illustrate how ANP determines county rank as a measure of influence in a metropolitan statistical area (MSA) defined by its interrelated socio-economic and spatial elements qualitatively and quantitatively. We compare the ANP results to similar measures of regional influence in the literature.     

Mixture of MLP-experts for trend forecasting of time series: A case study of the Tehran stock exchange

A new method for forecasting the trend of time series, based on mixture of MLP experts, is presented. In this paper, three neural network combining methods and an Adaptive Network-Based Fuzzy Inference System (ANFIS) are applied to trend forecasting in the Tehran stock exchange. There are two experiments in this study. In experiment I, the time series data are the Kharg petrochemical company’s daily closing prices on the Tehran stock exchange. In this case study, which considers different schemes for forecasting the trend of the time series, the recognition rates are 75.97%, 77.13% and 81.64% for stacked generalization, modified stacked generalization and ANFIS, respectively. Using the mixture of MLP experts (ME) scheme, the recognition rate is strongly increased to 86.35%. A gain and loss analysis is also used, showing the relative forecasting success of the ME method with and without rejection criteria, compared to a simple buy and hold approach. In experiment II, the time series data are the daily closing prices of 37 companies on the Tehran stock exchange. This experiment is conducted to verify the results of experiment I and to show the efficiency of the ME method compared to stacked generalization, modified stacked generalization and ANFIS.     

北京市人地关系现状及预测——基于生态足迹和GM模型的分析

采用改进过的生态足迹模型对北京市的人地关系现状进行了分析,并应用GM(1,1)模型对其耕地面积和人口数量的未来变动趋势进行了预测。结果表明,北京市近十年来耕地生态足迹逐年增加,其中区域耕地生态足迹的变化幅度比人均耕地生态足迹的变化幅度大;耕地生态承载力逐年降低,其中人均耕地生态承载力的降幅较区域耕地生态承载力的降幅更加明显。耕地生态足迹与耕地承载力异向变化,加剧了生态赤字逐年加大的幅度。在此基础上提出了控制人口规模、提高耕地产出能力及保持耕地产品地区间流动性等措施。     

基于DEA的物流公司绩效评价

鉴于传统绩效评价方法的局限性,运用数据包络分析（DEA）法,并以2008和2009年19家中国物流上市公司为样本进行实证研究,为各物流企业客观了解和评价自身物流竞争力和相对物流绩效水平提供参考。     

化工行业循环经济评价指标体系建立及应用研究

化工产业是循环经济建设的重点,循环经济评价指标体系建设是一项重要的工作。在已有的研究成果基础上,建立可以量化评价的化工行业循环经济评价指标体系,运用层次分析法,给出该指标体系的权重,通过案例分析,验证了其合理性。     

一种面向智能变电站和生产管理系统设备在线监测的数据转换模型

在线监测是实现电网设备状态检修和生命周期管理的前提,而有效的设备数据转换模型是在线监测的基础。通过对智能变电站及生产管理系统的标准、规范进行分析,提出一种用于智能变电站和生产管理系统设备在线监测的数据转换模型。对生产管理系统的设备信息数据模型进行分类总结,基于交换用XML数据对生产管理系统和IEC 61850标准数据模型进行对比,对变电站设备的铭牌信息、运行信息以及监测信息采用标签映射与ID索引相结合的方法,实现智能变电站到生产管理系统的数据转换。     

高速公路智能交通系统(ITS)组成与应用

本文介绍了智能交通系统的主要研究内容,通过对智能交通系统主要研究内容的分析,总结出ITS在高速公路上的应用。     

Usage‐based insurance and its acceptance: An empirical approach

This study aims to explore the motor insurance market's attitude towards usage‐based insurance (UBI), and thus its readiness for a launch in the near future. Data on client perception was collected using a structured questionnaire. On the basis of this, an initial selection of factors, other than income, that could influence the declared attitude of drivers was demonstrated showing that it is primarily dependent on certain demographic characteristics like their age, sex, or place of residence. A strong relationship was also demonstrated with respect to the intensity of the vehicle's use, to the amount of the insurance premium they have paid, and to the self‐assessment of the respondents' driving skills. Clients are likely to accept the concept of UBI once implemented, but that they are not ready yet to give up the traditionally used methods of premium calculation. Their attachment to discounts granted can be very strong in particular to the no‐claims bonus.