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.     

Technology fusion: Identification and analysis of the drivers of technology convergence using patent data

The concepts of technology convergence or technology fusion describe the phenomenon of technology overlap. Despite evidence of the higher value associated to interdisciplinary research and cross-industry innovation, few studies have investigated the characteristics of technology fusion based on patent data. This study identifies new cases of convergence relying on the International Patent Classification (IPC) of patents filed at the European Patent Office between 1991 and 2007: the first occurrence of a patent incorporating a combination of IPC subclasses signals a new instance of fusion. Duration models are employed to investigate the impact of field level characteristics derived from patent bibliometrics on the likelihood of identifying a new fusion. The results show that merges are more frequent if the focal technology fields are closely related (based on a higher number of cross citations), are characterized by wide technological scope, and are the result of an inter-firm collaboration. In contrast to previous findings, the results show that the more complex the technologies involved, the less the likelihood of their convergence or fusion. The correlation between fusion likelihood and the characteristics of the merging fields could help managers and policymakers to predict the emergence of new technology areas.     

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.     

From passenger growth to aircraft movements

Airlines are able to deal with passenger growth by either increasing the frequency or the aircraft size, which may entail different numbers of aircraft movements. Forecasting the latter is necessary for evaluating technologies, approaching future emissions or anticipating capacity constraints. Purpose of this paper is to forecast a typical fleet mix and the growth of aircraft movements on flight segments worldwide based on an assumed passenger growth. The methodology is implemented in a model called Forecast of Aircraft Movements. Basic approach is the assignment of each flight segment worldwide to a distance, passenger number and aircraft category. For each combination of distance and passenger numbers a typical fleet mix is defined. The forecasted worldwide growth of passenger demand and the empirically determined fleet mix is applied to all segments in order to derive a future scenario. Assuming a certain seat load factor, the frequency growth can be deduced from the aircraft movements generated for all segments. The paper includes a forecast for aircraft movements in a future scenario based on real schedule and passenger data and gives a detailed overview of the methodology and results considering airlines' behaviour.     

物流需求量灰色马尔科夫模型预测

针对物流信息的不确定性与复杂性,用灰色马尔科夫模型对黑龙江省物流需求的指标量"货运量"与"货物周转量"进行了预测。预测结果为黑龙江省物流产业的发展政策及物流基础设施的规划和设计提供了决策依据,对提高黑龙江省物流产业的发展水平具有一定的参考意义。     

基于灰色系统理论的江苏省入境旅游研究

入境旅游是旅游业的重要组成部分,本文运用灰色系统理论中的灰色关联度分析方法对江苏省旅游外汇收入与主要客源国入境旅游人次数之间的关联性进行分析,并建立了GM(1,1)灰色预测模型对江苏省典型创汇国未来的入境旅游客流规模进行预测,为江苏省入境旅游提供决策依据和方法参考。     

论如何提高地面气象测报工作质量

文章根据地面气象测报工作现状,结合笔者多年测报工作经验,谈几点提高地面测报工作质量的体会。     

岩滩水电站水文预报方案研究

文章介绍了红水河岩滩水电站水文预报的方案、内容及作业方法。     

论如何提高地面气象测报工作质量

文章根据地面气象测报工作现状,结合笔者多年测报工作经验,谈几点提高地面测报工作质量的体会。     

我国房地产市场的短期量价变化研究及预测

文章在对我国房地产市场走势进行定性分析的基础上,综合运用时间序列方法,对房地产市场的短期量价变化进行了研究和预测。文章认为,应通过加大落实保障性住房建设力度,保障城市中低收入居民利益;加强房地产价格调控力度,坚决打击房地产投机行为;拓宽都市圈系统建设范围,促使更多地区推进城市化建设等措施促进房价稳定以及房地产市场的健康发展。