Who herds?

This paper develops a test for herding in forecasts by professional financial analysts that is robust to (a) correlated information amongst analysts; (b) common unforecasted industry-wide earnings shocks; (c) information arrival over the forecasting cycle; (d) the possibility that the earnings that analysts forecast differ from what the econometrician observes; and (e) systematic optimism or pessimism among analysts. We find that forecasts are biased, but that analysts do not herd. Instead, analysts “anti-herd”: Analysts systematically issue biased contrarian forecasts that overshoot the publicly-available consensus forecast in the direction of their private information.     

COVID-19: Forecasting confirmed cases and deaths with a simple time series model

Forecasting the outcome of outbreaks as early and as accurately as possible is crucial for decision-making and policy implementations. A significant challenge faced by forecasters is that not all outbreaks and epidemics turn into pandemics, making the prediction of their severity difficult. At the same time, the decisions made to enforce lockdowns and other mitigating interventions versus their socioeconomic consequences are not only hard to make, but also highly uncertain. The majority of modeling approaches to outbreaks, epidemics, and pandemics take an epidemiological approach that considers biological and disease processes. In this paper, we accept the limitations of forecasting to predict the long-term trajectory of an outbreak, and instead, we propose a statistical, time series approach to modelling and predicting the short-term behavior of COVID-19. Our model assumes a multiplicative trend, aiming to capture the continuation of the two variables we predict (global confirmed cases and deaths) as well as their uncertainty. We present the timeline of producing and evaluating 10-day-ahead forecasts over a period of four months. Our simple model offers competitive forecast accuracy and estimates of uncertainty that are useful and practically relevant.     

智能电网与负荷调度

在现代经济社会发展中,离不开电网的支持,电网系统的安全运行已经是这个会前进中必须要保障的,虽然现在电网系统越来越完善,但是在巨大的客观环境中,随着电网负荷的不断加大,电网系统还是面临着巨大的挑战,比如说全球气候变暖的影响、恶劣环境的影响、电力市场运行等原因都给电网安全稳定运行的工作带来了一定的困难。本文主要是针对智能电网与负荷调度两个方面来分析解决电力系统中的问题。     

减量训练和停训对大鼠坐骨神经超微结构的影响

研究大负荷运动损伤后减量训练和停训大鼠坐骨神经超微结构的变化。方法:建立动物运动损伤模型及减量训练和停训模型。利用透射电子显微镜观察各组大鼠坐骨神经超微结构的变化。结果:①大负荷运动组坐骨神经超微结构严重损伤。②减量训练组坐骨神经超微结构基本恢复正常,新生神经纤维产生。③停训组部分髓鞘结构基本完整,但仍有灶状髓鞘脱失和崩解。结论:减量训练更有利于损伤坐骨神经组织结构的修复。     

Under weighting of Private Information by Top Analysts

It is conventionally perceived in the literature that weak analysts are likely to under weight their private information and strategically bias their announcements in the direction of the public beliefs to avoid scenarios where their private information turns out to be wrong, whereas strong analysts tend to adopt an opposite strategy of over weighting their private information and shifting their announcements away from the public beliefs in an attempt to stand out from the crowd. Analyzing a reporting game between two financial analysts, who are compensated based on their relative forecast accuracy, we demonstrate that it could be the other way around. An investigation of the equilibrium in our game suggests that, contrary to the common perception, analysts who benefit from information advantage may strategically choose to understate their exclusive private information and bias their announcements toward the public beliefs, while exhibiting the opposite behavior of overstating their private information when they estimate that their peers are likely to be equally informed.     

Multigeneration diffusion model for economic assessment of new technology

In the era of 21st century, development of emerging information technology is the essence of the advancement. This kind of new technology, however, often requires a great deal of amount of initial investment for both procedures of R&D and commercialization. As cost invested in developing the specified technology is increasing, investors are paying more attention to cost to benefit analysis (CBA). One of the basic elements of CBA for new technological development is the diffusion pattern of demand of such technology. Typically, it would be hard to presume the diffusion pattern of demand when the new product or the technology is under development. In this case, a simulation study is necessary. Many studies of technology evaluation have adopted a single generation model to simulate the diffusion pattern of demand. This approach, however, considers the diffusion of the new technology itself, not taking into account newer generation, which can replace the one just invented. In the real market situation, one must consider the competition and substitution phenomena between old and new technologies. In this paper, we show how multigeneration technology diffusion model can be applied for more accurate CBA for information technology. Additionally, Monte Carlo simulation is performed to find influential factors on the CBA of a cybernetic building system (CBS).     

财务危机预测模型的构建

基于Logistic回归模型,选取中国制造业上市公司作为样本对财务危机预测进行研究。从企业的盈利能力、营运能力、偿债能力、成长能力、现金流量等方面出发,选取了10个财务预警指标,经过回归分析得出,总资产收益率、总资产周转率、资产负债率、主营业务增长率、经营活动现金净流量对负债的比率五项财务指标对上市公司发生财务危机有重要影响。从而提出要从提高盈利能力、提升营运能力、增强偿债能力、提高成长能力、保障现金流的充足几方面来应对财务危机。     

改进灰色预测模型在我国船舶订单预测中的应用

面时人民币升值、钢材等原材料价格上涨、国际金融危机的冲击和市场出现的急剧变化,全年全国承接新船订单5818万载重吨．同比下降40．9％;手持船舶订单2．046亿载重吨,同比增长28．7％。未来几年,世界造船市场的需求如何,中国船舶制造企业该如何积极应对？这些都是中国造船业必须要面对和思考的问题。文章从手持订单量出发,借助改进后的灰色预测模型,对未来两年我国造船行业做一个简单预测,以期对我国造船业的发展提供借鉴和参考。     

个人信用评估的加权组合预测模型

目前单一的个人信用评估模型发展的很快,而精确性与稳定性却不能同时具备,且第二类误判率的能力弱,本文立足于用线性和非线性方法在个人信用评估中体现的优势,选择具有代表性的logistic回归和径向基函数神经网络方法,通过加权组合对个人信用进行预测评估,提高了评估模型的精确性与稳健性。     

工控系统感性负载所引起的干扰及其抗干扰设计

由于工业现场存在着大量的感性负载,如交、直流继电器、接触器、变压器和交直流电磁铁等,当对其进行投切操作时,会在电感线圈的两端产生极高反向电动势,引起强烈的高频电磁干扰,而且会使触点间隙产生电弧击穿,并通过传导作用而施于电源侧的计算机,严重影响附近工作的计算机控制系统的正常运行。