A large factor model for forecasting macroeconomic variables in South Africa

This paper uses large Factor Models (FMs), which accommodate a large cross-section of macroeconomic time series for forecasting the per capita growth rate, inflation, and the nominal short-term interest rate for the South African economy. The FMs used in this study contain 267 quarterly series observed over the period 1980Q1-2006Q4. The results, based on the RMSEs of one- to four-quarter-ahead out-of-sample forecasts from 2001Q1 to 2006Q4, indicate that the FMs tend to outperform alternative models such as an unrestricted VAR, Bayesian VARs (BVARs) and a typical New Keynesian Dynamic Stochastic General Equilibrium (NKDSGE) model in forecasting the three variables under consideration, hence indicating the blessings of dimensionality.     

Comparing face-to-face meetings, nominal groups, Delphi and prediction markets on an estimation task

We conducted laboratory experiments for analyzing the accuracy of three structured approaches (nominal groups, Delphi, and prediction markets) relative to traditional face-to-face meetings (FTF). We recruited 227 participants (11 groups per method) who were required to solve a quantitative judgment task that did not involve distributed knowledge. This task consisted of ten factual questions, which required percentage estimates. While we did not find statistically significant differences in accuracy between the four methods overall, the results differed somewhat at the individual question level. Delphi was as accurate as FTF for eight questions and outperformed FTF for two questions. By comparison, prediction markets did not outperform FTF for any of the questions and were inferior for three questions. The relative performances of nominal groups and FTF were mixed and the differences were small. We also compared the results from the three structured approaches to prior individual estimates and staticized groups. The three structured approaches were more accurate than participants’ prior individual estimates. Delphi was also more accurate than staticized groups. Nominal groups and prediction markets provided little additional value relative to a simple average of the forecasts. In addition, we examined participants’ perceptions of the group and the group process. The participants rated personal communications more favorably than computer-mediated interactions. The group interactions in FTF and nominal groups were perceived as being highly cooperative and effective. Prediction markets were rated least favourably: prediction market participants were least satisfied with the group process and perceived their method as the most difficult.     

内部评级体系定量验证模型及在中国银行业的应用

定量验证是运用一定的统计方法来检验商业银行已运行内部客户评级体系的准确性、审慎性及稳定性。准确性验证主要检验商业银行的内部评级模型对授信客户信用状况好坏的风险识别能力;审慎性验证主要检验银行所采用的政策与标准在辨别其内部评级和风险参数量化上的保守程度;稳定性验证则主要检验在风险不变的情况下,银行所采用政策和标准能够保持评级与估值总体上不发生变化。本文介绍了常用的定量验证模型及流程,并以中国某商业银行进行定量验证的实践为例,介绍了如何进行银行内部评级体系的定量验证及在具体实践中可能遇到的问题及解决方案。     

基于主成分分析和支持向量机的个人信用评估

本文针对信用评估指标维数较高的问题,运用主成分分析与支持向量机理论建立了一个新的个人信用评估预测模型。为反映该模型在信用评估分类方面的优越性,又分别建立了基于神经网络、K近邻判别分析等多种理论的信用评估模型,并用同一组数据对不同的模型分别进行训练,然后比较其预测分类正确率。实验结果表明,基于主成分分析与支持向量机理论的个人信用评估模型具有较优的预测分类正确率。     

Using Leading Indicators to Forecast U.S. Home Sales in a Bayesian Vector Autoregressive Framework

This article uses Bayesian vector autoregressive models to examine the usefulness of leading indicators in predicting U.S. home sales. The benchmark Bayesian model includes home sales, price of homes, mortgage rate, real personal disposable income, and unemployment rate. We evaluate the forecasting performance of six alternative leading indicators by adding each, in turn, to the benchmark model. Out-of-sample forecast performance over three periods shows that the model that includes building permits authorized consistently produces the most accurate forecasts. Thus, the intention to build in the future provides good information with which to predict U.S. home sales. Another finding suggests that leading indicators with longer leads outperform the short-leading indicators.     

定量分析中准确报告最终结果的方法

准确地出具检测数据对于各种实验室都是至关重要的。本文简要介绍了国际标准ISO5725-6:1994中对报告最终结果的统计处理方法。     

三基地雷达最佳空间定位算法

将三基地雷达二维定位最佳算法加以推广,在不增加设备量的前提下,充分利用各雷达站的测量信息,对三基地雷达三维空间直线布站的最佳算法进行推导和研究.仿真结果显示,空间相关数据压缩算法比独立数据压缩算法更加有效地提高了目标定位精度,特别是较好地改善了发射站附近区域的定位性能,有效解决了双基地雷达空间定位的基线盲区问题.     

On the selection of forecasting models

It is standard in applied work to select forecasting models by ranking candidate models by their prediction mean squared error (PMSE) in simulated out-of-sample (SOOS) forecasts. Alternatively, forecast models may be selected using information criteria (IC). We compare the asymptotic and finite-sample properties of these methods in terms of their ability to mimimize the true out-of-sample PMSE, allowing for possible misspecification of the forecast models under consideration. We show that under suitable conditions the IC method will be consistent for the best approximating model among the candidate models. In contrast, under standard assumptions the SOOS method, whether based on recursive or rolling regressions, will select overparameterized models with positive probability, resulting in excessive finite-sample PMSEs.     

直升机载雷达侦察系统目标定位精度分析

本文介绍了直升机载侦察雷达对目标的定位原理和定位过程,分析了定位过程中载机自身定位的方法和坐标转换的过程,并在此基础上给出了影响直升机载侦察雷达对目标定位误差的因素及误差组成。     

经贸文体翻译之生命——准确性

实现经贸文体翻译的准确性,必须准确把握词汇含义,理解文化内涵,表现文体风格。