Does non-linearity help us understand,model and forecast UK stock and bond returns: evidence from the BEYR

The usefulness of non-linear models to provide accurate estimates and forecasts remains an open empirical debate. This paper examines the nature of the estimated relationships and forecasting power of smooth-transition models for UK stock and bond returns using a range of financial and macroeconomic variables as predictors. Notably, evidence of non-linearity is stronger when the bond-equity yield ratio is used as the transition variable. This ratio measures whether stocks are over (under)-valued relative to bonds and can act as a signal for portfolio managers. In-sample results reveal noticeable differences regarding the nature of relationships between the linear and non-linear setting, while results of a recursive forecasting exercise reveal both statistical and economic improvement over a linear model. Overall, these results support the view that non-linear estimates and forecasts can provide useful information for stock market traders, portfolio managers and policy-makers.     

Volatility forecasting: long memory,regime switching and heteroscedasticity

In this article, we account for the first time for long memory, regime switching and the conditional time-varying volatility of volatility (heteroscedasticity) to model and forecast market volatility using the heterogeneous autoregressive model of realized volatility (HAR-RV) and its extensions. We present several interesting and notable findings. First, existing models exhibit significant nonlinearity and clustering, which provide empirical evidence on the benefit of introducing regime switching and heteroscedasticity. Second, out-of-sample results indicate that combining regime switching and heteroscedasticity can substantially improve predictive power from a statistical viewpoint. More specifically, our proposed models generally exhibit higher forecasting accuracy. Third, these results are widely consistent across a variety of robustness tests such as different forecasting windows, forecasting models, realized measures, and stock markets. Consequently, this study sheds new light on forecasting future volatility.     

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。     

谈高压配网输变电工程可研阶段系统规划设计收资

文章就高压配网输变电工程可研阶段的系统规划设计收资情况作简要的分析,并通过工程实例,罗列出进行系统规划设计前所需要收集的大量数据及收资方法,以供同行参考。     

区域物流通道容量预测研究

将偏最小二乘回归模型与灰色GM(1,1)校正模型进行有机结合,建立组合预测模型,取得了令人满意的预测精度,为区域物流通道容量预测提供了一种新的思路和方法。     

基于重心法与物流量预测的物流园区选址

在研究物流园区选址理论的基础上,为使物流运输成本最小和物流园区的建设符合长远发展,在对物流园区选址时使用理论中的重心法并建立相应选址数学模型,将数学模型与趋势外推预测法预测的物流园区物流量结合,在定量的基础上计算得到物流园区的选址位置,同时为精确地得到选址位置开发了基于重心法的选址模型软件。最后通过吉木乃县物流园区选址说明该方法的可行性。     

Judgmental aggregation strategies depend on whether the self is involved

We report the results of a novel experiment that addresses two unresolved questions in the judgmental forecasting literature. First, how does combining the estimates of others differ from revising one’s own estimate based on the judgment of another? The experiment found that participants often ignored advice when revising an estimate but averaged estimates when combining. This was true despite receiving identical feedback about the accuracy of past judgments. Second, why do people consistently tend to overweight their own opinions at the expense of profitable advice? We compared two prominent explanations for this, differential access to reasons and egocentric beliefs, and found that neither adequately accounts for the overweighting of the self. Finally, echoing past research, we find that averaging opinions is often advantageous, but that choosing a single judge can perform well in certain predictable situations.     

Booking horizon forecasting with dynamic updating: A case study of hotel reservation data

A highly accurate demand forecast is fundamental to the success of every revenue management model. As is often required in both practice and theory, we aim to forecast the accumulated booking curve, as well as the number of reservations expected for each day in the booking horizon. To reduce the dimensionality of this problem, we apply singular value decomposition to the historical booking profiles. The forecast of the remaining part of the booking horizon is dynamically adjusted to the earlier observations using the penalized least squares and historical proportion methods. Our proposed updating procedure considers the correlation and dynamics of bookings both within the booking horizon and between successive product instances. The approach is tested on real hotel reservation data and shows a significant improvement in forecast accuracy.     

一种多功能液压试验台控制系统设计

本文介绍了一种多功能液压试验台控制系统设计,液压控制模块的设计采用了模块化设计方式,可以缩短产品设计开发周期减少开发成本。液压系统采用LUDV负载反馈控制技术能实现对不同负载压力的多个执行元件同时系统流量自动按比例分配。     

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。