基于因子分析的上市公司综合评价

利用SPSS软件,对17只煤发行业的股票2007年第三季度的9个财务指标进行因子分析,将9个指标浓缩为3个因子,利用主成分法并作方差最大旋转,计算出因子得分,并对上市公司的股票作出综合评价。     

股票数据初探——移动平均与烛状图分析

论文讲述了如何利用Python对多只股票进行数据分析,并且分析每只股票间的异同。运用Python,可将股票数据进行可视化处理,例如,运用线性图展现出股票随时间的变化情况;利用烛状图了解每只股票每日闭市与开市相比的盈利或者亏损情况;利用移动平均值直观地观察在规定时间内股票价格变动,了解股票价格是否稳定。论文以制定更好的决策为目的,从数据可视化入手,提供优质有效的数据信息,运用数据挖掘技术对微软、苹果、谷歌等多只股票价格波动趋势进行研究。     

我国上市公司股票涨跌与会计信息的相关性研究

从沪深300样本股的抽样统计研究来看,股票涨幅与净利润增长率指标相关性相对较强,每股收益、净资产增长率次之,与净资产增长率基本不相关。无论是在弱势还是在强势股市环境中,股票涨跌与每股收益、净资产收益率、净利润增长率的相关系数范围大约为0.1～0.3;股票涨跌与净资产增长率的相关系数范围大约为0.02～0.04。     

基于经营活动视角的财务指标与股票收益率相关性分析

本文借鉴IASB/FASB及王河流关于财务报表重构的方式方法,对2013-2017年135家上市医药公司进行财务报表列报及财务指标重构以突出经营活动对企业的价值创造能力,实证结果表明基于经营活动视角的财务指标对股票收益率有一定的解释能力,盈利能力、成长能力指标与股票收益率的相关性比较显著,是我国股票投资者较为关注的财务指标信息。     

成长股价值评估视角下的财务报表分析方法——以酒业上市公司为例

本文运用本杰明·格雷厄姆成长股价值评估模型考察了反映企业业务、业绩与管理的财务指标,阐述了企业未来财务指标的估计方法,最后以贵州茅台(600519)为例说明了股票估值的过程。     

成长股价值评估视角下的财务报表分析方法——以酒业上市公司为例

本文运用本杰明·格雷厄姆成长股价值评估模型考察了反映企业业务、业绩与管理的财务指标，阐述了企业未来财务指标的估计方法，最后以贵州茅台（600519）为例说明了股票估值的过程。     

模糊聚类分析在股票分析中的应用

在进行股票投资的时候,需要分析和选择那些获利能力强,财务状况良好的股票,以减少投资风险。但是股票评价指标又有许多种,他们的含义各有不同,如何把各种指标综合在一起是非常重要的。应用模糊聚类分析方法对股票市场上商业贸易板块样本股票进行了分类,综合多项财务指标来反映上市公司的盈利能力和发展水平,为分类和评估上市公司的优劣提供了很好的依据。     

数字偏好与股票市场反应——来自中国上市公司的经验证据

本文中国文化中的数字偏好为出发点,考察股票代码尾数为8和4对股票交易量以及股价涨跌的影响。结果发现:我国上市公司在选择股票代码时受到数字偏好的影响,股票代码尾数为4的公司数明显小于尾数为8的公司数;股票代码尾数为8对股票交易量的影响是正面的,反映出对数字8的偏好对股票交易量的影响是显著的;股票代码尾数为8能引起股价的上涨,表明中国文化中数字8的偏好对股价涨跌影响显著。     

股票收益率影响因素研究

本文选取2012年沪市制造业上市公司为研究样本,从上市公司财务指标中选取了6个具有代表性的影响股票收益率的因素进行多元回归分析。结果表明:净资产收益率、股东权益周转率、营业收入现金比率与股票收益率成正相关关系,而前两个指标可以有效解释股票收益,营业收入现金比率则不显著;贝塔系数、公司规模、公司成长性对股票收益率具有负效应。相信本研究对投资者提高投资决策水平及上市公司进行价值管理具有参考意义。     

中国股票收益率与宏观经济波动的关联性研究

文章基于我国名义汇率、名义利率、工业增加值以及货币供给量四个主要的宏观经济指标,利用多变量向量自回归（VAR）模型研究我国宏观经济变量冲击是否能够显著影响股票市场收益率的变动。经验结果表明,我国工业增加值以及货币供给量能够显著影响股票收益率,而名义利率以及名义汇率对股票收益率的影响相对较弱,此外,通过脉冲响应函数所得到的检验结果说明,我国宏观经济变量对股票收益率的冲击反应持续期均在一年以上。     

Analysis of the impact of Sino-US trade friction on China’s stock market based on complex networks

This paper analyzes the impact of the Sino-US trade friction incident in 2018 on China's stock market by using the complex network methods. Firstly, we divide the Sino-US trade friction incident in 2018 into four research periods. Based on the GARCH-BEKK model and the Planar Maximum Filter Graph (PMFG) algorithm, the volatility spillover network between China's stock market sectors and the stock price correlation network of China's stock market corresponding to the above four research periods are constructed. Next, from the perspective of sectors in stock market, we use various network centrality indicators to build a systematic importance comprehensive evaluation index of industry sectors in the stock market through the principal component analysis method, to explore the impact of the Sino-US trade friction incident on the risk spillover effects of sectors in China's stock market. From the perspective of the overall stock market, we analyze the impact of Sino-US trade friction incident on the overall stability of the stock market through calculating the network topology indicators and conducting simulation experiments. Finally, the main factors affecting the stability mechanism of China's stock market are studied through the probit model. The results show that: (1) The risk spillover effect of various sectors in China's stock market changes significantly in different periods of Sino-US trade friction, and there are obvious cyclical rotation effects among various sectors (2) When some weighted stocks in the stock market abnormally fluctuate or suffer targeted shocks, the China's stock market's ability to maintain stability is weak, and the Sino-US trade friction will reduce the stability of China's stock market, and the higher the intensity of trade friction incident is, the more obvious the impact of the incident is. (3) The important factors that affect the abnormal fluctuations in China's stock market include four types of indicators: the stock market network structure, the fluctuation of important international stock indexes, the fluctuation of commodity prices in the international market, and the domestic macroeconomic indicators. This study provides a reference for China's financial regulatory authorities to conduct macro-prudential management, control systemic risks, and maintain the stability of financial market.     

智力资本要素对企业价值影响之实证研究

本文以台湾信息电子产业为研究对象,先从理论及实证两方面文献选取智力资本之财务及非财务量化指标,再以2000至2007年共8年之数据利用线性回归方式检验相关指标对台湾信息电子业企业价值之贡献程度,尝试找出智力资本各构面之重要项目,以供企业做为未来提升自身智力资本项目之改进参考方向。实证结果显示员工年龄、员工教育程度、人力资本运用效率、前一年度研发密集度、以及主要顾客数皆对企业价值造成显著之影响。     

欧债危机冲击我国股票与债券市场的风险传染研究？

欧债危机对金融市场产生了显著的冲击,引发了巨大的风险。本文通过构建二元GARCH-BEKK模型,实证检验了欧债危机背景下欧洲股票市场、我国股票市场、国债市场与企业债市场之间的波动溢出效应,揭示了欧债危机冲击我国股票市场、国债市场与企业债市场的风险传染路径。实证表明,欧债危机冲击我国股票市场与债券市场的风险传导路径为：欧债危机引发的风险通过欧洲股票市场传导到我国股票市场,然后传导到企业债市场,最后传导到国债市场。     

Institutional quality, governance, and financial development

Using banking sector and stock market development indicators, we examine the effect of institutional quality on financial development in developed and developing countries. Empirical results are based on dynamic system generalized method of moments estimations and demonstrate that a high-quality institutional environment is important in explaining financial development, specifically for the banking sector. However, the stock market development-institution relationship is contingent one, characterized by a non-monotonic pattern. The results are robust to two measurements of institutions and governance indicators, as well as estimation methods.     

基于GARCH模型的股票市场价格波动分析

在经济和金融研究中,波动性一直是一个非常重要的方面,中国股票市场建立至今,股市大起大落成为一种常态。本文建立了上证综合指数波动的GARCH模型,从实证角度说明了上证综合指数波动存在着波动集簇性,而GARCH模型可以很好的拟合股指波动情况,同时对股指收益率也能进行较好的预测,最后根据结论提出了一些对策建议。     

中国内地、香港与美国股票市场的长期协整关系研究

随着中国经济不断地融入国际经济环境中,中国内地证券市场的国际化进程也逐渐加快,表现为与世界主要资本市场的联动效应明显增强。本文通过运用协整检验对中国内地、香港以及美国股票市场联动效应的研究发现,金融危机改变了三地股市间的长期均衡关系。     

金融中心成熟度评价体系实证研究

对金融中心成熟度的客观评价有助于金融城市科学合理地定位,制定发展战略。金融中心成熟度评价体系包含金融环境、金融规模、金融聚集度、金融服务和金融人才五个方面,这5个准则层用14个指标加以细化。同时选取亚洲的8个金融城市进行实证分析,为今后上海建设金融中心提出两点建议。     

A Reduced Rank Regression Approach to Tests of Asset Pricing

Both the Arbitrage Pricing Theory (APT) and the Capital Asset Pricing Model (CAPM) place restrictions of the cross-sectional variation of conditional expectations of asset returns and of macro indicators. We show that these restrictions imposed on the reference statistical models lead to special cases of the reduced rank regression model. The maximum likelihood problem is solved by canonical correlation analysis. Likelihood ratio tests about the number of factors underlying stock returns are straightforward to calculate, thus allowing discrimination between competing financial theories. Moreover LR tests on the relevance of each macroeconomic indicator within a chosen model can be implemented. Some of the tests are illustrated by an application to Italian stock market data.     

Impulse response function analysis of the impacts of land value-added tax policy on government performance

In this study, an epsilon-based network data envelopment analysis is employed to construct assessment mechanisms for government performance. Moreover, performance indicators of two dimensions of tax collection efficiency and financial effectiveness are measured. We propose a vector autoregression model in which all economic variables are regarded as dependent variables to address the disadvantages of traditional regression model. The conclusions are as follows: (a) measures of tax collection efficiency deteriorated, whereas those of financial effectiveness improved. (b) In an impulse response analysis of the model, an increase in government-published land values produced significantly increased tax collection efficiency.