A three-frequency dynamic factor model for nowcasting Canadian provincial GDP growth

This paper estimates a three-frequency dynamic factor model for nowcasting the Canadian provincial gross domestic product (GDP). The Canadian provincial GDP at market prices is released by Statistics Canada annually with a significant lag (11 months). This necessitates a mixed-frequency approach that can process timely monthly data, the quarterly national accounts, and the annual target variable. The model is estimated on a wide set of provincial, national and international data. In a pseudo real-time exercise, we find that the model outperforms simple benchmarks and is competitive with more sophisticated mixed-frequency approaches (MIDAS models). We also find that variables from the Labour Force Survey are important predictors of real activity. This paper expands previous work that has documented the importance of foreign variables for nowcasting Canadian GDP. This paper finds that including national and foreign predictors is useful for Ontario, while worsening the nowcast performance for smaller provinces.     

Modelling the iron ore price index: A new perspective from a hybrid data reconstructed EEMD-GORU model

As iron ore is the fundamental steel production resource, predicting its price is strategically important for risk management at related enterprises and projects. Based on a signal decomposition technology and an artificial neural network, this paper proposes a hybrid EEMD-GORU model and a novel data reconstruction method to explore the price risk and fluctuation correlations between China’s iron ore futures and spot markets, and to forecast the price index series of China’s and international iron ore spot markets from the futures market. The analysis found that the iron ore futures market in China better reflected the price fluctuations and risk factors in the imported and international iron ore spot markets. However, the forward price in China’s iron ore futures market was unable to adequately reflect the changes in the domestic iron ore market, and was therefore unable to fully disseminate domestic iron ore market information. The proposed model was found to provide better market risk perceptions and predictions through its combinations of the different volatility information in futures and spot markets. The results are valuable references for the early-warning and management of the related enterprise project risks.     

Forecasting dynamic return distributions based on ordered binary choice

We present a simple approach to the forecasting of conditional probability distributions of asset returns. We work with a parsimonious specification of ordered binary choice regressions that imposes a connection on sign predictability across different quantiles. The model forecasts the future conditional probability distributions of returns quite precisely when using a past indicator and a past volatility proxy as predictors. The direct benefits of the model are revealed in an empirical application to the 29 most liquid U.S. stocks. The forecast probability distribution is translated to significant economic gains in a simple trading strategy. Our approach can also be useful in many other applications in which conditional distribution forecasts are desired.     

货运车辆燃油消耗与运输效率关系研究

文中采用理论分析与模型构建相结合的方式,研究货运车辆的燃油消耗与运输效率之间的关系,基于调研数据,采用回归分析的方法构建模型,得到了不同车型车辆的百吨公里燃油消耗量与实载率的倒数关系模型,为企业提高车辆运输效率,降低燃油消耗提供数据参考。     

基于回归BP神经网络的短期负荷预测

负荷的形成受多方面因素的影响,在建立短期负荷预测模型时,需要综合考虑多种因素。同时,负荷是一种时间序列信号,目前的数据能够对以后的数据产生重要的影响,所以文章采用回归BP神经网络模型应用于短期负荷预测。实例计算表明,该方法有效,预测精度比常规方法高,收敛性好,运算速度快。     

Measuring and testing Granger causality over the spectrum: An application to European production expectation surveys

Decomposing Granger causality over the spectrum allows us to disentangle potentially different Granger causality relationships over different frequencies. This may yield new and complementary insights compared to traditional versions of Granger causality. In this paper, we compare two existing approaches in the frequency domain, proposed originally by Pierce [Pierce, D. A. (1979). R-squared measures for time series. Journal of the American Statistical Association, 74, 901–910] and Geweke [Geweke, J. (1982). Measurement of linear dependence and feedback between multiple time series. Journal of the American Statistical Association, 77, 304–324], and introduce a new testing procedure for the Pierce spectral Granger causality measure. To provide insights into the relative performance of this test, we study its power properties by means of Monte Carlo simulations. In addition, we apply the methodology in the context of the predictive value of the European production expectation surveys. This predictive content is found to vary widely with the frequency considered, illustrating the usefulness of not restricting oneself to a single overall test statistic.     

基于企业景气状况的财务预测研究——以企业调查数据为样本

以权威机构数千家企业调查数据为样本,分析了企业财务指标与企业景气指数之间的相关关系,并构建了基于企业景气指数的财务预测模型。经过分析和对模型的改进及对模型的预测评价,最后得到了7个具有较强预测能力的模型,为财务预测开拓了新的视角。     

浅谈干线公路旧桥检测评估

通过对湖南干线公路近50座公路旧桥梁检测评估实践,文章介绍了公路旧桥检测、评估的内容和方法,总结了技术状况评估的经验。     

在线品牌社区负面顾客契合演化过程:是愈演愈烈?还是否极泰来?

文章聚焦于在线品牌社区,从时间序列角度出发,选取小米在线社区论坛作为研究对象,采用网络志方法分析了负面顾客契合演化过程中的阶段划分及不同阶段的契合状态,厘清了负面顾客契合短期和长期演化过程的差异。研究结果表明,在线品牌社区负面顾客契合的短期演化可以划分为发泄、建设性讨论、威胁性退出、协商、报复（或回避、或妥协）五个子过程;从长期来看,能够形成社区认同的顾客会逐渐转向持续性正面契合,而那些无法形成社区认同的顾客则会产生回避。研究结论在丰富和完善顾客契合领域成果的同时,对中国情境下在线品牌社区的营销管理实践具有一定的参考价值。     

大秦线增加资本投入提高运输密度的分析

资本投入对产出数量起决定性作用。通过对大秦线的资本投入对运量增加的影响情况进行分析,说明加强影响列车质量和密度相关设施的资本投入,对提高产出起到重要作用。同时指出对投向大秦线的资本,应向发展重载技术方面倾斜,能对大秦线运输能力的提高起持续性影响作用。