Determining an optimal hierarchical forecasting model based on the characteristics of the data set: Technical note

The efficient flow of goods and services involves addressing multilevel forecast questions, and careful consideration when aggregating or disaggregating hierarchical estimates. Assessing all possible aggregation alternatives helps to determine the statistically most accurate way of consolidating multilevel forecasts. However, doing so in a multilevel and multiproduct supply chain may prove to be a very computationally intensive and time-consuming task. In this paper, we present a new, two-level oblique linear discriminant tree model, which identifies the optimal hierarchical forecast technique for a given hierarchical database in a very time-efficient manner. We induced our model from a real-world dataset, and it separates all historical time series into the four aggregation mechanisms considered. The separation process is a function of both the positive and negative correlation groups' variances at the lowest level of the hierarchical datasets. Our primary contributions are: (1) establishing a clear-cut relationship between the correlation metrics at the lowest level of the hierarchy and the optimal aggregation mechanism for a product/service hierarchy, and (2) developing an analytical model for personalized forecast aggregation decisions, based on characteristics of a hierarchical dataset.     

A model of medium term exchange rate forecast in an open economy The case of the mexican peso

Keynes (1930) and Samuelson (1965) proposals open the possibility of matching predictability and efficiency, as evidenced by the seminal study by Fisher (1930). Recent findings suggest that the foreign exchange market gradually incorporates relevant information allowing the formation of prices in a rational manner but not randomly. Models of exchange rate by term based on asset valuation suggest that the inclusion of risk in the spot rate increases the degree of predictability. The results show that after incorporating an accurate measure of risk, predictability of medium term foreign exchange rate increases.     

基于马尔柯夫分析的计算机预测和决策应用

从DSS应用现状出发,介绍了马尔柯夫分析的定义和数学原理,阐述了马尔柯夫分析的过程和预测的基本步骤,利用Excel设计了进行市场占有率预测的应用模型,并进行了仿真预测和决策分析。测试表明,应用模型简便通用,操作方便,提高了预测的计算精度和效率。     

基于指数平滑法的组合模型对住房需求量的预测研究

以哈尔滨市2000—2015年的城市人均住房使用面积和总人口数为基础，分别对总人口数建立三次指数平滑法模型，对人均住房使用面积建立二次指数平滑法模型，预测出哈尔滨市未来五年总人口数和人均住房使用面积，将总人口数和人均住房使用面积的预测结果代入M-W优化后的预测模型，更加精准的预测出了哈尔滨市未来五年的住房需求量，并对此提出对策和建议。     

配件物流中产品不同生命周期的配件库存预测

研究同一产品在不同生命周期对配件的库存预测方法,生命周期包括新产品,成熟产品,产品生命后周期。其中对成熟产品,产品生命后周期的配件预测给出了预测公式。     

浅析机队规划

随着世界金融危机的出现,航空公司的运营效益受到了很大的影响,如何提高航空公司的经济效益是当今民航界的又一主题。文章对提高我国航空公司运行效率有一定的理论指导意义。     

我国锦纶帘子布市场前景预测与应对措施

文章从国内外帘子布行业的现状及其格局的重新调整，汽车、公路运输业、轮胎相关行业的现状及发展前景，加入WTO和国家宏观政策变化对帘子布行业的影响等方面进行全面、深层次的分析，应用两种数学公式模型对未来15年的国内帘子布市场需求量的上下限进行预测，并提出应对措施。     

Does the financial analysts' usage of non-financial information influence the analysts' forecast accuracy? Some evidence from the Belgian sell-side financial analyst

This paper examines whether the use of non-financial information by sell-side financial analysts influences the accuracy of analysts’ forecasts. The research findings, based on a survey of Belgian financial analysts, suggest that financial analysts who use more forward-looking information and more internal-structure information offer more accurate forecasts. Furthermore, the listed Belgian firms examined in this study have improved their non-financial information reporting over time. However, neither the frequency nor the quantity of non-financial information mentioned by financial analysts in their reports appears to have increased over time.     

上市公司信息披露质量与证券分析师盈利预测

本文研究了上市公司信息披露状况与分析师预测行为之间的关系，结果发现，分析师的预测准确性总体上显著优于随机游走模型。进一步的研究发现，上市公司信息披露状况会对证券分析师的预测特征产生影响，信息披露透明度越高，分析师预测对会计盈利数据的依赖程度越低，预测准确性也随之提高。     

商品房价格与我国房地产业周期发展

相对持续高涨的房价,我国城市居民购房能力萎缩。房地产业连续9年的快速增长,使其到了发展的巅峰。发展过热的争论和投资过快引发的经济问题,实际是房地产业周期性发展规律的必然表现。房地产业周期性发展的拐点近年将会出现,未雨绸缪应引起高度重视。