Average skewness in global equity markets

This paper examines the predictive power of average skewness, defined as the average of monthly skewness values across stocks, documented by the prior literature for US market returns in an international setting. First, we confirm the validity of the results in the original study and show that the intertemporal relation between average skewness and aggregate returns becomes weaker in an alternative sample period. Second, when we repeat the analysis in 22 developed non-US markets, we find that average skewness has no robust predictive power for future market returns. The loss of forecasting power in the international sample does not depend on the method used to calculate average skewness or the regression specification and is supported by additional out-of-sample tests and subsample analysis.     

基于轻量级卷积神经网络的苹果表面缺陷检测方法

为了解决目前农业信息领域对苹果表面缺陷检测准确率低的问题,提出一种基于轻量级卷积神经网络的苹果表面缺陷检测方法.首先采集苹果缺陷样本图片制作实验数据集用于模型训练和测试;其次在AlexNet网络结构的基础上,引入深度可分离卷积代替原有网络中的标准卷积运算来进行图像特征的提取;最后利用全局平均池化方法代替原有网络中的全连...