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关键词： asymmetries   bivariate GARCH   oil price   stock market   structural breaks   volatility spillover   AUTOREGRESSIVE TIME-SERIES   SHOCKS   VARIANCE   TRANSMISSION   RETURNS   FUTURES  

摘要： The purpose of this paper is to examine the volatility transmission between oil prices and the seven major stock markets (G7) using symmetric and asymmetric bivariate GARCH models incorporating structural breaks. Since these countries play a crucial role in the international economy, it is important for financial market participants to understand the volatility transmission process for designing optimal portfolio allocations. We examine weekly data over the period 1998-2017 and endogenously detect structural breaks in variance using an iterated algorithm in order to estimate the volatility dynamics with greater accuracy. The models were estimated using the maximum likelihood method, and the BFGS algorithm was employed to obtain the variance-covariance estimation and the corresponding standard errors. Overall, we find volatility spillovers between markets together with the fact that the oil market has a leading role. More importantly, we show that neglecting structural changes in variance and/or asymmetries may lead to biased volatility spillover effects. Furthermore, the results highlight that models ignoring structural breaks are significantly overestimating the effect of their own past volatility on the current volatility. In addition, we find that disregarding asymmetries could also lead to erroneous estimates of these effects. Finally, we compute dynamic risk-minimizing hedge ratios and optimal portfolio weights, however, no significant discrepancies are found among the models considered.

关键词： Chinese stock market   Comovement   Complex network   Engle-Granger test   Weighted LeaderRank algorithm   INFLUENTIAL SPREADERS   FINANCIAL NETWORKS   GRANGER CAUSALITY   SYSTEMIC RISK   CENTRALITY   COINTEGRATION   TOPOLOGY   MODEL   CONNECTEDNESS   INFORMATION  

摘要： How to appropriately characterize the comovement between any pair of individual stocks and describe the market comovement structure is a great challenge and plays a key role in understanding emerging markets. This paper applies the complex network approach to deal with this issue for the Chinese stock market. Firstly, in view of the topological properties, we investigate the time-varying comovement between individual stocks by constructing 14 directed weighted stock networks. Furthermore, the weighted LeaderRank algorithm is employed to describe the comovement structure of the entire market. Most importantly, from the perspective of fundamental factors and industry factors, we reveal the driving factors of the comovement and structural change of the entire market. The empirical results suggest that: (i) Stocks with higher weighted LeaderRank algorithm scores generally have more long-term investment value; and the so-called views, "too big to fail"and "too connected to fail", are further confirmed. (ii) ROE, BMratio and Growth are significantly positively correlated with the comovement between individual stocks, and Mvalue is significantly negatively correlated during normal periods. However, during the crisis, the signs of regression coefficients of above four explanatory variables are reversed. (iii) In normal periods, we only find that the agriculture, forestry, animal husbandry & fishery and composite have significant influence on the comovement structure of the entire market. Besides, public utilities and medias also have a significant impact during the crisis. In addition, a very interesting fact in point is that network density, average clustering coefficient, and global efficiency can provide an "early warning"for possible upcoming crises.

关键词： 审计报告改革   关键审计事项   股票流动性   信息价值   审计质量   审计费用   审计风险  

摘要： 手工收集5806家A股上市公司2017—2018年新式审计报告文本数据,采用事项个数、段落字数和文件长度三种披露水平计量方法,研究发现随着审计报告中关键审计事项披露水平的提高,公司股票流动性增强,在考虑内生性和执行多种稳健性检验后结论仍然成立。进一步分析表明,在内部控制薄弱、大股东持股比例低的样本中两者存在显著正相关关系。研究贡献在于从股票流动性视角证明了关键审计事项披露的信息价值,以源自审计师的信息披露为调查对象,拓展了股票流动性的影响因素研究,表明审计报告改革实现了预期目的,有助于提高证券市场效率。

关键词： 产能建设   不确定性因素   敏感性分析  

摘要： 随着油田效益开发理念的逐步推进,产能建设作为关系到油田经济效益和长期可持续性发展的一项重要的生产活动,由于其具有的高风险、高投入特点,各油气田企业纷纷将效益指标作为产能建设是否予以实施的量化“标尺”,通过缜密的经济评价,形成产能建设可行性论证的重要一部分,实现开发效果与经济效益的有效匹配。由于评价过程中采取的各项指标具有预测性,为了精准评价,做出最佳决策,本文对影响产能建设评价结论的影响因素开展敏感性分析,找出敏感性因素,确定评价指标对该因素的敏感程度和项目对其变化的承受能力,在投资风险评估、投资方案优化及选择上发挥了重要的作用,是项目经济评价过程中不可或缺的环节。

关键词： 金融工具准则   预期信用损失减值模型   货币时间价值  

摘要： 2017年财政部新修订的《企业会计准则第22号——金融工具确认和计量》,要求企业采用“预期信用损失法”对金融工具减值损失进行会计处理时要考虑货币的时间价值。在其具体运用过程中,我国上市公司通过使用预期信用损失模型对货币时间价值进行考量,出现了多种情况。对此,文章结合相关理论与实务案例,对预期信用损失模型中的货币时间价值要素提出思考,并对现行准则提出了改进建议。

关键词： 建设项目   现金流   银行贷款   利率   偿还方式  

摘要： 从现金流量的角度,基于NPV的盈利能力评价,通过有无对比讨论银行贷款对建设项目所带来的净现金流量效果,通过建立数学模型,定量表达贷款所带来的净现值效果,研究贷款利率、还款年限、融资比例和贷款偿还方式对净现值效果的影响。

关键词： 消费者物价指数   风险与收益   经济金融化   投资组合   债券市场   上证50指数   中国证券市场   风险结构  

摘要： 经典金融学理论认为,对于金融市场来说,风险与收益是成正比的。本文尝试对中国证券市场自2005年以来上证50指数、中小板综合指数、20年期国债、3个月期国债以及C P I消费者物价指数的年化收益率数据做定量分析,检验不同投资工具的收益率与其各自的风险是否对称,并希望通过对检验结果的解读,提供政策参考建议。本研究结果发现,中国股票市场和债券市场之间的收益和风险是对称的,但以小公司为主的中小板综合指数与以大公司为主的上证50指数的收益率与风险不对称,同样的情况还出现在20年期国债和3个月期国债两者的收益风险关系上。这种情况的出现,一方面与研究期的时间较短有关;另一方面,还与中国经济正处于转型升级的过程有关。建议继续推进经济金融化进程,并在设计投资组合时,投资者要重视上述因素对投资市场的影响。

关键词： 复杂网络   多元金融上市公司   资管新规   动态拓扑结构  

摘要： 对2009年度和2019年度中国A股多元金融公司的股票基于收益率相关性进行复杂网络建模,研究其网络拓扑结构在这十年中的动态变化,揭示其网络连通程度日益紧密的特征。一方面采用控制变量法来解释变化的原因,一方面通过《关于规范金融机构资产管理业务的指导意见》等金融监管环境的变化、宏观去杠杆等经济政策以及公司自身的经营状况等基本面因素寻求网络结构演进的现实依据。由于重要节点公司反应了该网络的主要信息,因此“指数成分股”动态选择具有理论依据。在2020年资本市场受到新冠肺炎疫情冲击而动荡的背景下,对其进一步研究,发现在系统性危机的冲击下,证券市场板块内部的网络拓扑结构发生改变,网络联通度降低,边缘节点公司增多,节点公司的重要性也会发生变动,据此,为股票市场投资和监管提出相应的政策建议。

关键词： 个体工商业户   电力工业志   广西壮族自治区   沿海地区   宏观经济环境   用电报装  

摘要： 由于受宏观经济环境的影响,工业用电报装增容还不多,户数比1998年增长了2.31%,增容主要分布在柳州、南宁、河池、桂林、玉林等地,北海、钦州、防城等沿海地区增容较少。个体工商业户有所发展增加,户数比上年增长了4.52%。

关键词： SARS-CoV-2 pandemic   Stock indices   Survival analysis models   Risk assessment  

摘要： The aim of the study is to assess the strength of the world stock exchanges reaction to the SARS-CoV-2 coronavirus pandemic at the turn of 2019-2020. We analyze the risk and intensity of the decline in the values of the basic stock indices by means of selected methods of survival analysis. The spreading pandemic within a few months covered all continents and had a significant impact on the socio-economic situation of all countries. We studied the time of the 20% drop in stock market indices. This is a value that is taken as a sign of a crisis. In order to assess the probability of indices' value decrease, we use the Kaplan-Meier's estimator. We determine the risk of decline by means of a logit model and the intensity of the decline by means of an empirical hazard estimator and the Cox proportional hazard model. The intensity and risk of the decline of stock indices varied from continent to continent. The obtained results show that the intensity is highest in the fourth and eighth week after the peak and is the highest on European exchanges and then American and Asian exchanges (including Australia). The risk of falling the stock indices' prices is the highest in America, followed by Europe, Asia and Australia, and lowest in Africa. Half of the analyzed indices record a 20% drop in value after 52 days (median duration). The study is a prelude to further analyses related to the crisis and the normalization of the situation on world stock exchanges. It allows to learn about the impact of the pandemic on the economic situation and to detect the differences between the continents.