基于人工神经网络的互联网公司估值方法研究

资本市场认为互联网公司市值的驱动因素应包括盈利因子、运营因子、流量因子和协同因子。将协同效应指标考虑到公司估值体系中,意图构造互联网公司优化估值模型。使用美股上市的互联网企业数据建立了评价指标体系,通过因子分析实现了二级指标降维,通过实证分析确认了四个因子与公司市值的相关关系,最后构建了基于人工神经网络BP算法的互联网公司估值模型,通过预测数据的检验发现模型的准确度较高。随着2018年互联网公司美股上市潮的持续,该模型能有效为资本市场估值提供参考。     

Connectedness and systemic risk spillovers analysis of Chinese sectors based on tail risk network

This paper investigates the systemic risk spillovers and connectedness in the sectoral tail risk network of Chinese stock market, and explores the transmission mechanism of systemic risk spillovers by block models. Based on conditional value at risk (CoVaR) and single index model (SIM) quantile regression technique, we analyse the tail risk connectedness and find that during market crashes, stock market exposes to more systemic risk and more connectedness. Further, the orthogonal pulse function shows that Herfindahl-Hirschman Index (HHI) of edges has a significant positive effect on systemic risk, but the impact shows a certain lagging feature. Besides, the directional connectedness of sectors shows that systemic risk receivers and transmitters vary across time, and we adopt PageRank index to identify systemically important sector released by utilities and financial sectors. Finally, by block model we find that the tail risk network of Chinese sectors can be divided into four different spillover function blocks. The role of blocks and the spatial spillover transmission path between risk blocks are time-varying. Our results provide useful and positive implications for market participants and policy makers dealing with investment diversification and tracing the paths of risk shock transmission.     

简析数据加密技术在计算机网络安全中的应用

随着我国科学技术的不断发展,计算机被广泛应用于各行各业的发展建设以及人们日常生活和学习中,在给人们带来较大便利的同时,也存在安全隐患。网络安全问题威胁到了计算机信息的保密性,给计算机的可持续发展带来了安全隐患,若用户的信息被泄露会给用户带来巨大的财产损失及心理伤害。因此,出现了数据加密技术,其为计算机网络安全提供了很好的保障。基于此,论文对数据加密技术在提高网络安全性中的应用方面作了简要阐述。     

Dynamics of firm's network community associations and firm's innovation performance

ABSTRACT

R&D network structures have crucial impacts on firm's innovation performance. However, most previous studies have been based on the whole or ego network perspective, few studies have investigated the influence of community structure that a firm is engaged in on its innovation performance, and it is still unclear how a firm's relation to network community affect its innovation performance. This research aims to address this gap by focusing on the dynamics of firm's network community associations, empirically investigate the relationship between dynamics of firm's network community associations and its innovation performance. Based on the unbalanced panel data of smartphone R&D network during year 2004–2017, the results demonstrate that change in community member associations and movement across communities both have inverted-U-shaped effects on firm's innovation performance. Moreover, innovation openness depth has moderating effects on the relationships between dynamics of firm's network community associations and its innovation performance.     

The impact of dual network structure on firm performance: the moderating effect of innovation strategy

ABSTRACT

Firm innovation is embedded in a collaboration network among researchers and a knowledge network composed of knowledge elements; the two networks are decoupled. Guided by social network theory, this study puts forward the definition and the classification of firm dual network structure, probes into the influence of dual network structure on firm performance, and explores the alignment between innovation strategy and firm dual network structure. We conduct an empirical study of 183 listed companies in China from 2004 to 2018. It is found that the four types of dual network structure all have positive impacts on firm performance, and the impact of a collaboration network is slightly higher than that of a knowledge network. Besides, innovation strategy plays a positive moderating role in the relationship between dual network structure and firm performance. Our findings provide new ideas for firms to identify and optimise knowledge and collaboration network structures and match them with innovation strategy to improve performance.     

《经济地理》创刊以来的知识溢出特征与变化

基于引证关系,利用知识图谱、社会网络分析等方法,对1981—2019年《经济地理》创刊以来知识溢出的特征与变化规律进行分析。经济地理学研究的专业综合性、学科交叉性特点,在《经济地理》期刊知识溢出的特征与变化中得以充分诠释。期刊知识溢出的作用与变化,不仅体现在促进作者合作网络形成与机构合作关系的深化上,也体现在对城市化、区域经济发展、区域旅游发展等研究领域的推动作用与变化上。期刊知识溢出的特征与变化在其主题构成、作者贡献、机构力量与前沿引领等的探讨中进一步得以明确。具体地,城市化研究的知识溢出作用,从城市化和城镇化、土地利用、生态环境等方面,逐渐转向新型城镇化、城市网络、生态环境、协调发展等主题;区域经济发展研究的知识溢出作用,经历了从经济联系转向产业集群、再转向空间相互作用关系的主题变化;区域旅游发展研究的知识溢出作用,则从旅游资源、旅游业、生态旅游等方面,逐步转向乡村旅游、旅游经济与协调发展等主题。以国家战略与发展政策为主要导向,促进国内经济地理学的研究与发展,是《经济地理》期刊知识溢出的核心内容与集中反映。     

制度变迁下国有商业银行农村服务网络演化——以农业银行兰考县支行为例

经济转轨背景下农村的银行服务网络呈现出不同于城市的演化特征。从制度变迁角度建构分析框架,基于历史、调查与访谈数据,以农业银行兰考县支行为例,探讨我国商业银行农村服务网络演化动力机制。研究表明:国有商业银行农村服务网络经历了恢复成立后的快速扩张和密集的人工网点服务,市场化改革中农村业务收缩和大规模网点撤并,到新时期人工、自助、电子、代理等多元服务渠道扩张;农村银行服务网络演化是商业银行和制度环境相互作用的空间过程,普惠金融战略下我国特别强调金融服务的均等化和基础金融网点的全覆盖,商业银行不断借助新的伙伴关系开拓农村市场,其中合作代理日益发挥重要作用。不同地区、不同商业银行农村服务网络模式的差异,农村银行服务网络转型对农村社会经济发展、金融生态环境改善、农民金融素养提升的影响等还需进一步研究。     

基于数字足迹的乡村旅游流空间结构特征--以浙江省湖州市为例

乡村旅游是乡村振兴的有效路径,也是近年来研究热点,而在乡村旅游流领域研究相对不足。以湖州乡村旅游地为案例,通过对大样本数字足迹的数据处理,分析乡村旅游流空间结构特征,总结空间行为偏好。结果表明:①乡村旅游数字足迹呈现全年双峰值、月度差异不大的时间特征,"双核"多组团的空间分布特征,以及古镇、古村、民宿等带有文化符号旅游景观导向的空间偏好特征;②网络密度0.27的乡村旅游流空间结构由连接度高的34个节点构成,除核心吸引的双核外,民宿集聚区构成了网络结构的核心点;③传统旅游吸引物、民宿集聚区等节点呈现较强的网络中心性,节点的网络结构特征反映乡村旅游流空间呈现的地理临近性,以及区域空间集聚、扩散与联动发展效应。依据研究结论提出"完善与发挥节点集聚扩散功能,增强节点对数字足迹的有效吸引力,提升乡村旅游经济发展质量,助力乡村振兴"的发展策略。     

Stock market reactions to domestic sentiment: Panel CS-ARDL evidence

This study sets out to explore the effects of business and consumer sentiment on stock market performance, within the separate contexts of advanced and emerging markets. The empirical analysis is carried out using the cross-sectionally augmented autoregressive distributed lag (CS-ARDL) modeling approach, which considers time dynamics, cross-sectional heterogeneity, and cross-sectional dependence. The findings for developed markets suggest that business sentiment has positive leading effects on stock returns, across short- and long-term time horizons, while for emerging markets, the price impact of business sentiment turns out to be short-lived. On the other hand, consumer sentiment tends to affect positively both market types, albeit only in the short run. Furthermore, the influence of sentiment indicators seems to be stronger in emerging- than in developed-market countries. The results remain robust, even after controlling for a rich range of potential predictors of stock returns. Generally, such evidence highlights the relevance of psychological factors, such as business and consumer sentiment, in determining the future trajectory of asset prices.     

Uncovering the global network of economic policy uncertainty

This study uncovers the static and dynamic network of economic policy uncertainty (EPU) across 17 developed and emerging economies. We build a centrality network using the minimal spanning tree (MST) as well as a dependency network using partial correlations. Results from the MST show that EPU exhibits some degree of geographical connections with EPUs in seven countries in the sample directly linked to the US EPU. Evidence from dynamic time-varying MST reveals that the nature and dominance of the EPU network have changed significantly over time. Further, the US and German EPUs dominate a close-knit global policy uncertainty network with the highest net (To and From) transmitter of information flow in the dependency network. Greece, Russia, and Brazil are the top three net receivers of information in the global network of EPU. The policy implication of these results relates to the renewed and ongoing international debate on policy coordination.