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。     

影响食品检验准确性的因素及管理策略研究

随着我国社会经济水平的逐渐提高,食品消费量逐渐增加,人们对食品质量也提出更高的要求和标准。但很多食品制造商不重视食品安全,导致市场上存在很多劣质食品,给人们带来了极大的安全隐患,不利于保障食品安全质量。因此社会对食品检验工作提出了更高的要求,相关部门需要做好食品安全监督管理工作,构建完善的食品检验体制,强化食品安全监察力度,以此来全面提升食品检验的准确性,确保食品的安全。本文针对影响食品检验准确性的因素进行讨论,并提出了有效的管理措施,以期为相关行业提供参考,推动食品检验行业的健康发展。     

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。     

企业战略差异度会影响分析师盈余预测吗？

随着我国资本市场的发展,证券分析师的作用日益凸显,关于分析师盈余预测的研究一直是各界关注的重点。采用我国沪深两市A股上市公司2011—2015年分析师盈余预测数据,检验了企业战略差异度对分析师盈余预测精度和分析师跟踪偏好的影响。实证结果表明：（1）企业战略差异度越大,分析师盈余预测准确度越低;（2）企业战略差异度越大,分析师盈余预测分歧度越大;（3）企业战略差异度越大,分析师跟踪人数越少。进一步研究还发现：国有产权会削弱战略差异度对分析师盈余预测准确度和跟踪人数的不利影响。     

Forecasting the past: the case of US interest rate forecasts

This study evaluates 10-year US government bond yield forecasts and three-month US Treasury bill rate forecasts for the period between October 1989 and December 2004. In total, 136 forecast time series with approximately 13,800 forecast data were scrutinized, making this the most extensive analysis of interest rate forecasts to date. Not one of the forecast time series proved to be unbiased. In the majority of cases, information from the past was not efficiently integrated into the forecasts. The sign accuracy is significantly better than random walk forecasts in only a very few of the forecast time series. The modified Diebold–Mariano test for forecast encompassing reveals that the information content of most of the forecast time series is lower than that of the naïve forecasts, the simple ARIMA models, the implicit forward rates, or average interest rate expectations. The forecasting process is dominated by the present and past market situation.     

Does foreign investor demand for information affect forecast accuracy? Evidence from the Chinese stock markets

Prior international accounting studies have examined mainly the supply side of analyst research. Specific trading rights and financial reporting systems in China provide a unique opportunity to test both demand and supply factors of analyst information. For shares traded only by less-informed foreign investors, the increased information demand may create incentives for analysts to exert greater efforts than for shares traded by local investors. This study provides evidence that analyst effort (proxied by analyst coverage) and expertise (proxied by consensus cross-analyst forecast variability) affect forecast accuracy more significantly for shares traded by foreign investors than for shares traded by local investors. Additionally, I find that the relation between analyst characteristics and relative forecast accuracy is stronger for shares traded by the foreign investors. The findings are consistent with analysts responding to demands for information by less-informed investors.