Incorporating textual and management factors into financial distress prediction: A comparative study of machine learning methods

Financial distress prediction (FDP) has been widely considered as a promising approach to reducing financial losses. While financial information comprises the traditional factors involved in FDP, nonfinancial factors have also been examined in recent studies. In light of this, the purpose of this study is to explore the integrated factors and multiple models that can improve the predictive performance of FDP models. This study proposes an FDP framework to reveal the financial distress features of listed Chinese companies, incorporating financial, management, and textual factors, and evaluating the prediction performance of multiple models in different time spans. To develop this framework, this study employs the wrapper-based feature selection method to extract valuable features, and then constructs multiple single classifiers, ensemble classifiers, and deep learning models in order to predict financial distress. The experiment results indicate that management and textual factors can supplement traditional financial factors in FDP, especially textual ones. This study also discovers that integrated factors collected 4 years prior to the predicted benchmark year enable a more accurate prediction, and the ensemble classifiers and deep learning models developed can achieve satisfactory FDP performance. This study makes a novel contribution as it expands the predictive factors of financial distress and provides new findings that can have important implications for providing early warning signals of financial risk.     

A comparison of conditional predictive ability of implied volatility and realized measures in forecasting volatility

In a conditional predictive ability test framework, we investigate whether market factors influence the relative conditional predictive ability of realized measures (RMs) and implied volatility (IV), which is able to examine the asynchronism in their forecasting accuracy, and further analyze their unconditional forecasting performance for volatility forecast. Our results show that the asynchronism can be detected significantly and is strongly related to certain market factors, and the comparison between RMs and IV on average forecast performance is more efficient than previous studies. Finally, we use the factors to extend the empirical similarity (ES) approach for combination of forecasts derived from RMs and IV.     

国际重要检索系统与甘肃省科技期刊

对国际重要检索系统进行了论述,并对甘肃省科技期刊被国际重要检索系统收录情况进行了统计与分析。     

A new DFM flow for sub-100nm standard cells

DFM （Design-For-Manufacturability） method, which aims to improve manufacturability of ICs through specific design considerations, is becoming important nowadays. In particular, standard cells now should be designed by DFM method. This paper reports a new DFM flow for sub-100 nm standard cell design with a group of technologies for process modeling, manufacturability simulation and trial RETs. Based on this flow, a set of DFM-friendly 90nm standard cells were designed.     

Engineering of multiferroic BiFeO3 grain boundaries with head-to-head polarization configurations

Confined low dimensional charges with high density such as two-dimensional electron gas (2DEG) at interfaces and charged domain walls in ferroelectrics show gre...     

在J2EE架构中数据对象的设计与实现

从数据流角度出发,基于MVC模式设计要求,对数据对象在不同层之间的传输和转换问题进行了深入分析,设计出基于对象化数据在不同层之间的实现思路,基于网络传输和跨平台性考虑,提出了VO和XAO的解决方案,并采用了COMMAND模式进行设计实现。     

UFPA器件微桥腐蚀工艺的研究

利用硅单晶的各向异性腐蚀技术,研究了UFPA探测器的微桥腐蚀工艺.采用独特的腐蚀装置在厚度为300 μm的硅基片上成功地制备了腐蚀坑深度为260 μm,桥面宽度为2 mm的微桥结构.该装置能有效保护硅基片正面免受腐蚀液的漏蚀,从而可实施热释电薄膜的沉积先于微桥制备的技术线路,对提高器件的成品率具有重要的意义.     

VISA存储网络系统元数据管理的研究

为了提高虚拟接口存储结构(VISA)存储网络系统的性能,设计实现了基于块级的元数据管理子系统.该系统的元数据管理子系统实现了物理设备和逻辑设备的块地址空间之间的映射,支持动态地址映射、动态块重分配和热块冗余技术,可以对I/O请求的路径和数据传输的路径完全控制,从而有效地改善了VISA存储网络系统的I/O性能,使数据布局更加合理,提高了存储管理的灵活性,初步实现了负载均衡,并且使VISA存储网络系统具备了容错能力和节点的动态增加能力.测试结果表明:在加入了基于块级的元数据管理功能带来相应开销的情况下,VISA存储网络系统原型与传统存储网络系统iSCSI Linux MD相比,传输延迟减少了8.2%～21.0%,传输吞吐率提高了8.7%～11.9%.     

基于两相流模拟的高抗堵滴灌灌水器开发方法

提出了一种基于两相流(水和固相物)数值模拟并结合快速原形/快速制模(RP/RT)技术的滴灌灌水器快速低成本开发方法,辅助新型灌水器设计与开发.对比传统的开发方法,该方法不仅保证了灌水器高的抗堵塞性能,而且其开发成本和周期均降低超过70%以上.灌水器内流场两相流模拟采用了分离相模型,不仅可视化了水流场微观特性,而且得出了固相物在灌水器内流场水流中的流动轨迹及固相物在灌水器中密度分布,为灌水器的结构优化提供了直接的依据.采用RP/RT制模制作实验样件,保证了样件材料与注塑产品的一致性,提高了定型精度.     

基于三维参数化斜Haar变换彩色图像压缩编码

提出基于三维参数化斜Haar变换的静止彩色图像压缩编码方法,采用计算复杂度低、变换效果好且变换矩阵可随参数灵活变化的新型参数化斜Haar变换,并将彩色图像的R,G,B 3个分量看作一个整体同时进行变换,不仅有效地去除了各分量内像素的相关性,还去除了各分量间的相关性.理论分析和实验结果表明:参数化斜Haar变换的重建图像质量接近于准最优的DCT变换,同时,提高了压缩比.该方法计算量较小,尤其适合于编码效率更高的16×16分块方法,可推广应用于画面质量要求不太高的实时视频编码中.