Does a lot help a lot? Forecasting stock returns with pooling strategies in a data‐rich environment

A variety of recent studies provide a skeptical view on the predictability of stock returns. Empirical evidence shows that most prediction models suffer from a loss of information, model uncertainty, and structural instability by relying on low‐dimensional information sets. In this study, we evaluate the predictive ability of various lately refined forecasting strategies, which handle these issues by incorporating information from many potential predictor variables simultaneously. We investigate whether forecasting strategies that (i) combine information and (ii) combine individual forecasts are useful to predict US stock returns, that is, the market excess return, size, value, and the momentum premium. Our results show that methods combining information have remarkable in‐sample predictive ability. However, the out‐of‐sample performance suffers from highly volatile forecast errors. Forecast combinations face a better bias–efficiency trade‐off, yielding a consistently superior forecast performance for the market excess return and the size premium even after the 1970s.     

随机和认知混合不确定系统的全局灵敏度分析方法

为计算具有随机不确定性和认知不确定性的混合不确定系统灵敏度,提出一种基于证据理论和条件概率理论的全局灵敏度分析方法.用证据理论对认知不确定性变量进行表征,并提出两种基于证据理论的随机采样方法,包括一次随机抽样法和二次随机抽样法.运用条件概率理论,提出存在认知不确定性条件下混合不确定系统的Sobol'全局灵敏度指标,经过理论推导给出一阶灵敏度及总灵敏度的计算公式,并设置单循环的拟蒙特卡罗方法实现灵敏度的近似数值计算.开发了灵敏度分析程序,并给出了典型应用实例.实例表明,新方法的分析结果正确,计算工作量可控.     

双重不确定冷贮备系统的可靠性分析

运用不确定理论研究了无充足样本的冷贮备冗余系统。假设系统所有元件的寿命服从具有不确定参数且相互独立的不确定分布,基于可靠度函数和平均寿命建立了3类冗余系统可靠性的数学模型:转换开关完全可靠型、转换开关离散型、转换开关连续型的冷贮备系统。此外,针对元件寿命为独立同分布的特殊情况进行了分析,给出数值算例,进一步印证模型的合理性。     

火焰原子吸收分光光度法测定地表水中铜含量的不确定度评定

根据GB 7475—87《水质铜、锌、铅、镉的测定火焰原子吸收分光光度法》建立地表水样测定的数学模型,并根据JJF 1059.1—2012《测量不确定度评定与表示》的要求,计算测量过程中的不确定度分量,最终得出扩展不确定度.经检测计算,该地表水样品中的铜含量为1.53 mg/L,其扩展不确定度为0.036 mg/L,包含因子k=2,地表水样品中铜含量的测量结果应报告为(1.53±0.036) mg/L, k=2.结果表明,火焰原子吸收分光光度法测定地表水样中铜含量的不确定度主要来源于标准曲线拟合、标准溶液配制和样品重复测量.     

新不确定度量下的冲突证据融合

针对证据高度冲突的情况下,DS证据理论在实际应用中出现错误融合结果的问题,提出基于不确定度的冲突解决方法.首先分析现有的不确定度量方法的不足,研究基本概率赋值本身所包含的信息,提出一种新的对证据不确定性度量的方法;依据新的不确定度量,结合证据距离生成权重来修正待组合证据体,再利用Dempster规则完成证据组合,可有效解决证据高度冲突情况下的信息融合问题,最后通过算例验证了该方法的有效性.     

电网故障下双馈风力发电机控制改进与仿真

随着风电装机规模的不断增加,作为未来能源互联网中重要的一环,风电机组应对电网故障的能力越加显得重要。针对双馈风力发电机组在电网故障下的暂态特性,提出了一种基于电网故障类型区分、控制器设计和辅助设备穿越的综合控制策略。相比于传统的控制方法,克服了控制误差大和响应滞后的问题,真正实现了系统的精细化控制。基于MATLAB和VC++联合建模,利用MEX技术搭建了电网故障下的1.5 MW双馈风力发电系统模型,仿真结果验证了所提出的综合控制策略在电网故障下提高双馈风力发电机控制的有效性。     

Multi-model ensembles in climate science: Mathematical structures and expert judgements

Projections of future climate change cannot rely on a single model. It has become common to rely on multiple simulations generated by Multi-Model Ensembles (MMEs), especially to quantify the uncertainty about what would constitute an adequate model structure. But, as Parker points out (2018), one of the remaining philosophically interesting questions is: “How can ensemble studies be designed so that they probe uncertainty in desired ways?” This paper offers two interpretations of what General Circulation Models (GCMs) are and how MMEs made of GCMs should be designed. In the first interpretation, models are combinations of modules and parameterisations; an MME is obtained by “plugging and playing” with interchangeable modules and parameterisations. In the second interpretation, models are aggregations of expert judgements that result from a history of epistemic decisions made by scientists about the choice of representations; an MME is a sampling of expert judgements from modelling teams. We argue that, while the two interpretations involve distinct domains from philosophy of science and social epistemology, they both could be used in a complementary manner in order to explore ways of designing better MMEs.     

Forecasting and nowcasting emerging market GDP growth rates: The role of latent global economic policy uncertainty and macroeconomic data surprise factors

In this paper, we assess the predictive content of latent economic policy uncertainty and data surprise factors for forecasting and nowcasting gross domestic product (GDP) using factor-type econometric models. Our analysis focuses on five emerging market economies: Brazil, Indonesia, Mexico, South Africa, and Turkey; and we carry out a forecasting horse race in which predictions from various different models are compared. These models may (or may not) contain latent uncertainty and surprise factors constructed using both local and global economic datasets. The set of models that we examine in our experiments includes both simple benchmark linear econometric models as well as dynamic factor models that are estimated using a variety of frequentist and Bayesian data shrinkage methods based on the least absolute shrinkage operator (LASSO). We find that the inclusion of our new uncertainty and surprise factors leads to superior predictions of GDP growth, particularly when these latent factors are constructed using Bayesian variants of the LASSO. Overall, our findings point to the importance of spillover effects from global uncertainty and data surprises, when predicting GDP growth in emerging market economies.     

双时相影像联合不确定性对变化检测精度的影响机理探索

研究了双时相影像的联合不确定性对变化检测结果精度的影响机理，为通过抑制不确定性的方法提高变化检测精度的工作奠定理论基础.首先利用联合熵对双时相影像的联合不确定性进行量化评估；进而基于空间统计相关方法，研究影像的联合不确定性与双时相影像变化检测精度指标之间的关系；最后建立双时相影像联合不确定性对变化检测结果精度的作用模型.实验结果表明：双时相影像的联合不确定性与变化检测结果的精度之间呈现出强负相关性，且对变化检测结果精度的影响模式具有线性特征.     

含螺栓联接的转子系统轴向刚度不确定性分析

转子系统中螺栓联接结构轴向联接刚度的不确定性对转子系统动力学特性具有重要影响,为此,在构建螺栓联接结构有限单元基础上,建立了转子系统整体有限元模型,采用非嵌入多项式混沌展开法分析轴向联接刚度不确定性对转子系统动力学特性的影响.结果表明:轴向联接刚度在一定范围内变化会导致临界转速及临界转速对应的稳态响应幅值偏离预期,随着轴向刚度不确定性的标准差增大,盘竖直方向稳态响应均值降低.研究结果可为螺栓联接转子的设计提供理论参考.