Modelling multiperiod patterns in stock-market reactions to events,with an application to serial acquisitions

In event studies, the now standard window of a few days may miss relevant price movements if the market’s reaction to the news announcement tends to be slow or if the initial reaction tends to be partially or wholly undone afterwards. We propose a parsimonious hybrid of splines and Almon lags to detect and classify various patterns of post-event reactions spread over many periods. The scheme can interact with one or more event characteristics (like deal size), and the resulting non-linear model can be estimated via maximum likelihood (ML).In our application, we study the returns pattern that follows takeover announcements by two leading serial acquirers, AB Inbev SA and Heineken. Our method confirms the presence of a drop-and-recovery pattern as reported in Doan and Sercu (2021), but the amplitude of the pattern shows no link with deal size. This last finding is not in line with the view that the pattern reflects a rise in uncertainty that is slowly resolved (Malatesta and Thomson, 1985).     

Some issues in blockchain for accounting and the supply chain,with an application of distributed databases to virtual organizations

This paper reviews some recent blockchain‐based applications for information capture, distribution and preservation. As part of that review, this paper examines two key concerns with current blockchain designs for accounting and supply chain transactions: data independence and multiple semantic models for the same information distribution problem. Blockchain applications typically integrate database, application and presentation tiers all in the same ledger. This results in a general inability to query information in the ledger and other concerns. Further, since most applications appear to be private blockchain applications, there is a concern of agents needing to accommodate multiple blockchains depending on who their trading partners are and what they request. Finally, this paper uses a distributed database to design a ‘blockchain‐like’ system for virtual organizations.     

分布式电动汽车充电桩信息安全防护技术研究与实现

论文对分布式电动汽车充电桩信息安全防护技术进行研究,分析充电桩信息安全防护技术应用,注重提高防护技术应用可行性与安全性。对分布式电动汽车充电桩通行特点进行分析,探究信息安全防护方案。     

Collaborative delay management towards demand-capacity balancing within User Driven Prioritisation Process

The concept of User Driven Prioritisation Process (UDPP) was introduced to give Airspace Users (AUs) more flexibility under demand-capacity imbalance. This paper presents two UDPP-DCB models, built on the UDPP principle, using the Selective Flight Protection (SFP) approach to minimize the total delay cost. AUs are enabled to adapt their operations in a more cost-efficient way in the presence of capacity constraints in airspace, optimizing their flights to keep the priorities track. Then, ATFM integrates the AUs’ decision to reassign the time slots and the preferred rerouting trajectories. Results suggest that the delay cost for AUs can be largely reduced through applying the UDPP-DCB models proposed in this paper, while allowing rerouting proves effective in reducing the system delay cost.     

Euro area sovereign yield spreads as determinants of private sector borrowing costs

We regress long-term private-sector borrowing rates on a money market rate, a term premium and credit risk. As a contribution to the current debate about European safe assets, our interest is in quantifying the impact of euro area sovereign bond spreads on private-sector lending by employing it as a proxy for private-sector credit risk. Panel estimates show significant, albeit rather small long-run effects. Another finding is large cross-country heterogeneity. Using linear country-specific estimates, we find the effect to be significant in only some countries, but the size of the maximum effect in these countries exceeds the average one more than three-fold. Furthermore, for one country, we find an asymmetrical effect with positive spread changes having greater impact on private-sector borrowing costs than negative ones. Substantial heterogeneity of the spillover effect between euro area countries indicates the presence of financial valuation effects based not only on economic fundamentals. This, in turn, implies that spillovers may entail contagion costs. Overall, our results suggest that these costs are considerable in the euro area and will remain so until an effective form of European safe assets is created.     

The Effects of Electronic Collaboration in Distributed Project Management

Abstact The emergence and widespread use of collaborative technologies for distributed project management has opened up opportunities for off-shore outsourcing and collaborative development. However, most tools and techniques for project management focus on on-site, long term relationships and sourcing strategies at a time when inter-organizational relationships are becoming more dynamic and geographically dispersed. This paper uses grounded theory to analyze data on virtual teams' projects. The analysis uncovers “effects” in the way in which distributed projects are managed. These effects relate to coordination, communication and adaptation to distributed electronic work environments. Following an analysis of these electronic collaboration “effects”, a model for distributed project management is presented.     

语音指导查询与数据自动传输方法

我国电子商务刚刚起步,应根据我国电子商务发展的现状,结合发达国家的先进经验,对相应的网上交易涉税问题尽早给予解决。电子商务的商品交易方式、支付方式等都与传统的方式有着很大的不同,这就给税收制度带来了挑战。本文将对电子商务所涉及的税收问题作一论述。     

广西税收增长与经济增长关系的实证分析

本文运用回归模型、自回归分布滞后模型和动态分布滞后模型对广西税收增长与经济增长的关系进行了实证分析。结果表明:广西税收对GDP的弹性过低,原因主要是税制结构不合理、税收征管存在问题。税收增长短期内具有较大惯性,就长期而言还是依赖于经济的持续稳定增长,广西的税收增长与经济增长之间存在长期协调增长的关系。     

Search reduction in hierarchical distributed problem solving

Knoblock and Korf have determined that abstraction can reduce search at a single agent from exponential to linear complexity (Knoblock 1991; Korf 1987). We extend their results by showing how concurrent problem solving among multiple agents using abstraction can further reduce search to logarithmic complexity. We empirically validate our formal analysis by showing that it correctly predicts performance for the Towers of Hanoi problem (which meets all of the assumptions of the analysis). Furthermore, a powerful form of abstraction for large multiagent systems is to group agents into teams, and teams of agents into larger teams, to form an organizational pyramid. We apply our analysis to such an organization of agents and demonstrate the results in a delivery task domain. Our predictions about abstraction's benefits can also be met in this more realistic domain, even though assumptions made in our analysis are violated. Our analytical results thus hold the promise for explaining in general terms many experimental observations made in specific distributed AI systems, and we demonstrate this ability with examples from prior research.This research has been sponsored, in part, by the National Science Foundation under grants IRI-9015423 and IRI-9010645, by the University of Michigan Rackham Graduate School, and by a Bell Northern Research Postgraduate Award.     

基于分布式数据挖掘的连锁商业企业经营决策分析

分布式经营系统是大型连锁商业企业发展的基础,采用分布式数据挖掘辅助连锁商业企业决策是一种理想选择。连锁商业企业经营决策可以通过基于分布式数据挖掘的全局控制站点决策模式和分站点决策模式,各站点的独立和全局的综合来实行;基于分布式数据挖掘的决策机制与集中式数据挖掘的决策机制相比有划分粒度小、分析与综合性强、面向顾客的灵活度高等特点;并实现了一个客户细分的决策过程。