Forecasting value at risk and expected shortfall with mixed data sampling

I propose applying the Mixed Data Sampling (MIDAS) framework to forecast Value at Risk (VaR) and Expected shortfall (ES). The new methods exploit the serial dependence on short-horizon returns to directly forecast the tail dynamics of the desired horizon. I perform a comprehensive comparison of out-of-sample VaR and ES forecasts with established models for a wide range of financial assets and backtests. The MIDAS-based models significantly outperform traditional GARCH-based forecasts and alternative conditional quantile specifications, especially in terms of multi-day forecast horizons. My analysis advocates models that feature asymmetric conditional quantiles and the use of the Asymmetric Laplace density to jointly estimate VaR and ES.     

When Auditors Say ‘No,’ Does the Market Listen?

Previous research on whether the market responds to auditors’ opinions has provided mixed results. We revisit this issue in China, where individual investors who are more likely to neglect value-relevant information dominate the stock market. In addition to going concern opinions (GCOs), China permits modified audit opinions (MAOs) on violations of accounting standards or disclosure rules (GAAP/DISC MAOs), providing an opportunity not available in the literature to enrich the study of audit-opinion pricing. We find that, ceteris paribus, MAO recipients underperform in the future and have a higher incidence of adverse outcomes such as misreporting and stock delisting, and the market reacts negatively to MAOs during the short window around MAO disclosure. Importantly, MAO disclosure is not followed by negative long-term stock returns, suggesting stock price adjustments to MAOs are speedy and unbiased. These findings hold for both GCOs and GAAP/DISC MAOs. Together, our findings support the informativeness of audit opinions and cast doubt on the argument that investors inefficiently price audit opinions due to information-processing bias.     

The effect of mergers and acquisitions on environmental,social and governance performance and market value: Evidence from EU acquirers

This study explores the effect of environmental, social, and governance (ESG) performance on market value and performance in the context of mergers and acquisitions. We examine whether acquisition of targets with better ESG performance can help acquirers to increase their own ESG performance and whether the market values the increased ESG performance positively. Moreover, we explore whether the acquisition of targets with better ESG performance affects the market value of acquirers. For this study, we utilize a sample of 100 European mergers and acquisitions between 2003 and 2017, for which matching data on the ESG performance of both the target and acquiring firms are available. Our results show that the postmerger ESG performance of the acquirer increases following the acquisition of a target that has higher ESG performance than that of the acquirer in the premerger stage, whereas the postmerger market value of the acquirer increases following an increase in the acquirer's postmerger ESG performance in relation to its premerger ESG performance. Finally, we provide partial evidence of a positive relationship between the postmerger market value of the acquirer and the acquisition of a target with higher ESG performance than itself in the premerger stage.     

Do institutional investors drive corporate transparency regarding business contribution to the sustainable development goals?

Institutional investors show increasing interest in how companies align their corporate social responsibility strategies with the sustainable development goals (SDGs) proposed by the United Nations (UN). The information disclosed in this regard is essential to know and monitor business contribution to the 2030 Agenda. In this paper, we analyze the influence that institutional investors have on the adoption of the disclosure strategy established by UN and the Global Reporting Initiative (GRI)—GRI‐SDG Compass. The results obtained for a sample of 989 international companies, which prepare their sustainability reports following the GRI guidelines, show that ownership by foreign investors, pension funds, and “other” investors boosts the relevance of the information disclosed in relation to the 2030 Agenda. On the contrary, government, financial institutions, and cross holdings have no impact on the information systems developed.     

利用ACE值构造QC-LDPC码

为进一步提升中短码长下准循环低密度奇偶校验(Quasi-cyclic Low-density Parity-check,QC-LDPC) 码的纠错性能，提出了一种综合短环数目和环连通性的QC-LDPC码构造方法。首先，采用Golomb规则构造QC-LDPC码，对基矩阵中的部分元素进行替换预处理，初步降低短环数目；其次，采用所提的利用近似环外信息度（Approximate Cycle Extrinsic message degree，ACE）的消环掩模算法来优化QC-LDPC码，使得掩模后的校验矩阵具有较大的ACE平均值，最终完成QC-LDPC码的构造。该构造方法简单、通用性强，在短环数目和连通性间进行了平衡。与只考虑减少短环数目、增大围长等方法相比，该方法构造的QC-LDPC码有更加优异的纠错性能。     

人工智能在我国公共卫生建设中的应用与思考

新冠疫情的暴发以及长期防治对中国的公共卫生体系造成深远影响，给我国突发公共卫生事件应急与防控机制带来巨大的考验。在疫情防控的过程中，信息化技术为传统医疗机构带来瞩目的帮助与改变，人工智能、大数据、5G高速网络等新兴高科技的蓬勃发展在直接提升医疗水平方面表现出巨大潜力。本文就人工智能在疫情期间的医疗辅助功能展开讨论，并对未来我国公共卫生体系的建设进行了思考。     

基于ADS-B报文的“北斗”便携式终端实现

针对单个广播式自动相关监视（Automatic Dependent Surveillance-Broadcast，ADS-B）发射机传输距离受限、多地面站组网复杂以及成本较高等问题，在分析ADS-B报文编码与解码算法的基础上，探讨了基于无线网络传输的ADS-B报文信息技术，并设计了基于“北斗”卫星导航（BeiDou Satellite Navigation System，BDS）/嵌入式控制器以及无线网络的便携式监视终端系统。利用实测ADS-B数据联合搭建的监视中心对算法和系统进行测试，结果表明数据传输稳定，实现了低空空域通用航空飞机ADS-B态势信息的网络传输功能，丰富了监视信息的链路传输方式，为低空通航飞行器安全飞行和全面监视提供了新的方法。     

NTRU格上高效的身份基线性同态签名方案

针对现有的格上身份基线性同态签名方案密钥存储量大、结构复杂导致方案实际运行效率相对偏低的问题，提出了一个NTRU（Number Theory Research Unit）格上高效的身份基线性同态签名方案。首先在密钥生成阶段利用NTRU密钥生成算法产生主密钥，接着采用格基委派算法给出身份签名私钥，最后运行NTRU格上原像抽样算法产生出线性同态签名。对方案的安全性证明与性能分析结果表明，新方案满足正确性，具有弱内容隐私性。在随机预言机模型下，该方案在小整数解问题困难性条件下满足适应性选择身份和选择消息的存在性不可伪造性。同时，由于采用NTRU格的特殊结构，新方案在密钥量与运行效率方面与已有方案相比较均具有显著的优势，这对于计算资源受限环境的同态认证中具有重要的应用价值。     

基于显著区域提取的红外图像舰船目标检测

针对复杂海面背景下红外图像舰船目标由于灰度不均匀、海杂波干扰大等因素造成的自动检测虚警率高、准确率低的问题，提出了一种显著区域提取和目标精确分割相结合的红外舰船目标检测方法。首先，利用基于图论的视觉显著性(Graph-based Visual Saliency ,GBVS)模型计算待检测图像的显著图，使得目标区域信息增强；其次，结合舰船目标先验信息（长短轴、面积等），利用多级阈值划分算法提取关注的显著区域，并确定原图中候选目标区域；最后，利用空间约束模糊C均值(Fuzzy C-Means,FCM)算法对候选区域进行分割，结合目标先验知识对分割区域筛选并输出目标位置。所提方法在公开数据集IRShips上与相关方法进行比较，结果表明，相比直接进行全图目标搜索的方法，所提方法不仅准确率高、执行速度快，且检测目标的位置更加精确。     

偏光显微镜法在空气粉尘中石棉纤维鉴别中的应用

本文采用偏光显微镜法鉴别空气粉尘中的微量石棉纤维。经滤膜收集的粉尘样品通过高温灰化及酸洗过程去除大部分干扰物质,经乙醇分散后均匀沉积在玻璃片上,滴加具有固定折射率的浸油制成试片。在正交偏光系统下观察到粉体中存在纤维状颗粒,且纤维呈现四次平行消光特性,比对6种常见石棉的偏光显微镜图,综合分析试样粉尘的光学性质,推断样品中含有温石棉。