企业风险传导及其载体研究

本文在概述风险与企业风险的基础上定义了何为企业风险传导,并对企业风险的传导路径作了归纳和分析;阐述了在企业风险的传导链和传导网络中,载体是风险传导过程中风险各要素相互联系的桥梁,也是各要素相互作用实现的有效形式;还揭示了在整个风险传导过程中,载体具有承载风险和传导风险的作用,同时,风险源、驱动力以及风险载体之间相互作用形成的耦合效应也使载体在企业风险传导链中具有“放大镜”的效应;并从企业风险传导的角度探讨了如何防范和控制企业风险。     

企业理财系统风险传导构成要素研究

本文界定了企业理财系统风险传导的概念,揭示了企业理财系统风险传导机理,分析了企业理财系统风险传导的风险源、风险传导路径和风险传导载体,为防范和控制企业理财系统风险奠定了理论基础,亦具有实践指导意义。     

企业理财系统风险传导构成要素研究

本文界定了企业理财系统风险传导的概念,揭示了企业理财系统风险传导机理,分析了企业理财系统风险传导的风险源、风险传导路径和风险传导载体,为防范和控制企业理财系统风险奠定了理论基础,亦具有实践指导意义。     

基于正向链式传导模式的供应链风险管理研究

正向链式传导模式的供应链风险是供应链风险中一种比较常见的供应链风险传导模式,它具有单向性、隐蔽性、成长性三个特征。本文首先分析了正向链式传导模式的供应链风险传导机理,然后分析了它的来源,并以发生概率和影响性对它们进行了预测和分类,最后提出了相应的风险控制对策。     

企业财务风险传导路径及传导效应

企业财务风险具有动态传导性,一个企业的财务风险会传导至财务关系网络中的其他关联企业。本文研究了企业财务风险传导的路径类型,分析了财务风险传导的蝴蝶效应、多米诺骨牌效应、耦合效应以及破窗效应。     

基于系统动力学的嵌入型食品供应链风险传导问题研究-以河北省保定市蔬菜供应链为例

通过对河北省保定市的蔬菜供应链进行分析调查,采用解释结构模型和系统动力学的方法结合嵌入型理论分析研究保定市蔬菜供应链的风险传导问题,将蔬菜供应链风险传导系统分为风险识别子系统、风险传导子系统和风险控制子系统,最后将这三个系统合并为蔬菜供应链风险传导系统,得出结论：要控制风险沿供应链传导,供应链上的核心企业起着主导的作用;超市在应对供应链风险的过程中应充分利用信息、合理控制库存和采购、严格对蔬菜进行质量检验。     

基于系统动力学的嵌入型食品供应链风险传导问题研究——以河北省保定市蔬菜供应链为例

通过对河北省保定市的蔬菜供应链进行分析调查,采用解释结构模型和系统动力学的方法结合嵌入型理论分析研究保定市蔬菜供应链的风险传导问题,将蔬菜供应链风险传导系统分为风险识别子系统、风险传导子系统和风险控制子系统,最后将这三个系统合并为蔬菜供应链风险传导系统,得出结论:要控制风险沿供应链传导,供应链上的核心企业起着主导的作用;超市在应对供应链风险的过程中应充分利用信息、合理控制库存和采购、严格对蔬菜进行质量检验。     

基于不同时期的企业风险传导分类研究

企业风险既存在资金风险、技术风险、人才风险,也存在环境风险、市场、政策等多种形态的风险。本文在区分可传导风险与非传导风险的基础上,依照风险传导在发生时间上的不同,提出了连续性风险传导、间歇性风险传导、时滞性风险传导、周期性风险传导、突发性风险传导的概念,分析了其各自的特征,进而引入了连续性和离散性概率分布类型,为企业风险传导的度量提供了一个良好的基础平台,有利于提高对风险传导一般规律的认识。     

企业财务风险生成和传导机理分析

文章主要分析了企业财务风险与会计要素及其结构、外部客观环境、企业内部主观管理决策的不确定性之间的关系,在此基础上构建了企业财务风险生成与传导的分析框架。该分析框架有助于研究各种因素引起的企业财务风险的机理和过程,从而有针对性地防范和控制企业财务风险的发生。     

从风险后果角度探讨供应链风险传导机理

供应链系统存在多种风险因素,这些风险因素具有传导性,并且在传导中给节点企业带来经济损失,对节点企业和供应链系统造成危害。作者从风险后果的角度出发,讨论了当风险来临时,风险因素对节点企业和整个供应链的影响,并结合供应链系统统计的相关数据,得出风险要素之间的传导概率,提出了风险因素的传导损失计算模型,利用此模型和风险因素带来的损失,可计算出传导损失,并将此损失与节点企业和供应链可承受的损失做比较,得出风险控制的相关结论。     

Oil structural shocks,bank-level characteristics,and systemic risk: Evidence from dual banking systems

By performing a structural VAR analysis on oil price shocks, we provide an evidence on how the origins of oil price shocks impact the risk level of banks in oil-exporting countries and whether bank-level characteristics can influence the sensitivity of risk to oil shocks. When conducting panel regression analysis, we document the following findings. First, not all shocks have the same effect on bank risk. Due to oil supply shocks, the increase in oil price raises bank risk, whereas the similar increase in price due to economic expansion or oil-market specific demand reduces that risk. Second, the business model (whether the bank is Islamic or conventional), size, income diversification, profitability, and financial leverage influence the bank risk exposure to oil shocks differently. Third, the two major recent crises (global financial crises and COVID-19 pandemic) magnified bank risk exposure to oil supply shocks and speculative oil demand shocks. Overall, the structural oil shocks explain a large fraction of the variation in financial stability in GCC countries.     

建设工程项目进度的动态风险分析研究

基于PERT网络模型,以网络活动为基础,对所有活动进行风险因素识别,并考虑其风险因素的时空变化性及其施工性质,对风险因素进行概率分布量化及活动影响权重量化;然后,依据量化结果,进行网络时间参数计算、Monte Carlo Simulation(MCS)模拟分析,得到项目完工工期的概率分布;最后,依据项目影响性计算原则,对各风险因素进行动态风险分析,得出各风险因素的影响指数曲线,达到进度动态风险分析的目的。     

Impact of investor’s varying risk aversion on the dynamics of asset price fluctuations

While investors’ responses to price changes and their price forecast have been identified as one of the major factors contributing to large price fluctuations in financial markets, our study shows that investors’ heterogeneous and dynamic risk aversion (DRA) preferences may play a more critical role in understanding the dynamics of asset price fluctuations. We allow an agent specific and time-dependent risk aversion index in a popular power utility function with constant relative risk aversion to construct our DRA model in which we made two key contributions. We developed an approximated closed-form price setting equation, providing a necessary framework for exploring the impact of various agents’ behaviors on the price dynamics. The dynamics of each agent’s risk aversion index is modeled by a bounded random walk with a constant variance, and such dynamics is incorporated in the price formula to form our DRA model. We show numerically that our model reproduces most of the “stylized” facts observed in the real data, suggesting that dynamic risk aversion is an important mechanism for understanding the dynamics of the financial market and the resultant financial time series.     

基于BP神经网络的企业应急物流风险管理

在客观分析企业应急物流风险的前提上,基于MATLAB工具箱--BP神经网络提出有效的评价方法,从应急物流的角度来评价突发事件的风险大小;同时建立了风险预警模型,最后提出对应的风险控制策略,为企业顺利应对突发事件提供行之有效的参考依据。     

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.     

House price risk and the hedging benefits of home ownership

Using a repeat-sales methodology, this paper finds that estimates of house price risk based on aggregate house price indices substantially underestimate the true size of house price risk. This is the result of the fact that aggregate house price indices average away the idiosyncratic volatility in house prices. Additional results show that the idiosyncratic risk exceeds the hedging benefits of home ownership. These results imply that for many home owners, owning a house may well add more price risk than it hedges away. These findings are based on a detailed dataset of individual housing transactions in the Netherlands.     

Pricing vulnerable options with stochastic liquidity risk

In this paper, we consider vulnerable options with stochastic liquidity risk. We employ liquidity-adjusted pricing models to describe the underlying stock price and option issuer’s assets. In addition, the correlation between these assets is stochastic, depending on the market liquidity measures. In the proposed framework, we derive closed forms of vulnerable European options with stochastic liquidity risk and then use them to illustrate the effects of stochastic liquidity risk on vulnerable option prices. Numerical results show that the effects of liquidity risk on the prices of out-of-the-money options or the options with a short maturity are not negligible.     

加油站网点拓展和经营中法律风险分析及防控对策

在加油站网点拓展和业务发展过程中,伴随着市场占有率提高和利润增加,法律风险也如影随形。为维护企业合法权益,我们采取对策力图减少并尽可能防止纠纷,也有了不少成功案例,但纠纷还多有发生。笔者以为,之所以如此,关键在于防控思维重总结,轻落实",谁来抓落实,如何抓落实,落实不到位怎么办"的风险防范责任难执行。我们应转换思维,落实责任,通过完善制度体系来保障风险防控落到实处,切实降低法律风险。     

Modelling the iron ore price index: A new perspective from a hybrid data reconstructed EEMD-GORU model

As iron ore is the fundamental steel production resource, predicting its price is strategically important for risk management at related enterprises and projects. Based on a signal decomposition technology and an artificial neural network, this paper proposes a hybrid EEMD-GORU model and a novel data reconstruction method to explore the price risk and fluctuation correlations between China’s iron ore futures and spot markets, and to forecast the price index series of China’s and international iron ore spot markets from the futures market. The analysis found that the iron ore futures market in China better reflected the price fluctuations and risk factors in the imported and international iron ore spot markets. However, the forward price in China’s iron ore futures market was unable to adequately reflect the changes in the domestic iron ore market, and was therefore unable to fully disseminate domestic iron ore market information. The proposed model was found to provide better market risk perceptions and predictions through its combinations of the different volatility information in futures and spot markets. The results are valuable references for the early-warning and management of the related enterprise project risks.     

Trade credit financing and stock price crash risk

This study investigates the association between trade credit financing and stock price crash risk within China's context. We find that firms using more trade credit financing have significantly lower future stock price crash risk. This negative association is more pronounced for firms with greater information asymmetry and for firms located in less developed financial markets. This finding is robust to the endogeneity concern, alternative measures of stock price crash risk, and the inclusion of other factors identified in prior studies that might affect stock price crash risk. Further evidence suggests that both the monitoring mechanism and the disclosure mechanism drive the documented relation. Our study suggests that access to trade credit can significantly reduce the likelihood of crash risk in a country like China with less developed formal bank financing. Our study also suggests that investors can effectively avoid stock price crash risk by using the trade credit information disclosed in financial statements.