Level Of Systemic Risk Research Articles

A dynamic community gas risk-prediction method based on temporal knowledge graphs

This paper presents a community gas-safety risk-prediction method for solving the complex and continuous community gas-safety factors based on the temporal knowledge graphs. First, a community gas-safety risk-assessment index system is constructed based on the risk sources and factors influencing gas accidents. Entity and relationship features are extracted from the index system to construct a temporal knowledge graph of the community gas system. The community gas-safety risk-assessment index system is constructed based on the risk sources and risk-influencing factors of gas accidents. Furthermore, entity and relationship features are extracted in the index system to construct temporal knowledge graphs for a community gas system. Then, a gas-system risk-prediction method based on the temporal knowledge graphs is proposed, which predicts the risk level of the gas system in a certain period in the future. Finally, by applying the method in a specific community, the accuracy of the proposed prediction method is 74.87%, and the mean reciprocal rank is 87.44. The proposed gas-safety risk-prediction method based on a temporal knowledge graph network can assist managers in effectively managing community gas and has a positive auxiliary effect on sensing and controlling gas-safety situations.

Low carbon urban rail transit station city integration based on building information modeling and sensor fusion

In order to better play the role of information technology in the construction management of rail transit projects, we analyze the application of geographic information system (GIS) + building information modeling (BIM) technology in the construction management of rail transit projects by combining the characteristics of GIS+BIM technology and aiming at the overall improvement of project management efficiency and technical management methods. This study is mainly conducted with the support of BIM technology and sensing technology. In the design stage, carbon emissions are classified according to the source activities of building carbon emissions, and the carbon emissions in the building life cycle are quickly calculated by using BIM technology, and the design is optimized according to the analysis of the budget results. The experimental results prove that the low-carbon building evaluation standard cloud model of all-electronic computer interlocking system for urban rail transit established in this study, combined with the comprehensive weighting results, calculates the low-carbon index cloud model and comprehensive cloud model, and derives the operational safety risk level of the all-electronic computer interlocking system, and the model optimization effect is good. Practice shows that GIS+BIM technology can realize the refinement and informatization of construction management, and has a broad development space in the field of urban rail transit and urban underground space construction.

Shear Performance of Large-Thickness Precast Shear Walls with Cast-in-Place Belts and Grouting Sleeves

Building industrialization has great significance for improving the efficiency of construction production, achieving the goal of energy saving and emission reduction, and promoting sustainable development. On the other hand, numerous thick wall structures with bulky dimensions and complex connection constructions have been applied into special engineering such as islands, tunnels, and deep sea projects. The precast structure is an open and complex system with a certain level of systematic risk for the whole life cycle. Moreover, structural mechanics and reliability, construction uncertainty, and resilience of precast thick wall structures still need to be revealed. For promoting the application of building industrialization to thick wall structures, nonlinear finite-element analyses on two types of large-thickness precast shear walls have been carried out based on original structural design specifications. The reinforcement connection configurations and the shear performance in terms of the load–displacement curve, lateral stiffness, ductility, energy dissipation capacity of shear walls with cast-in-place (CIP) belts, or grouting sleeves have been analyzed in detail. Numerical results show that the shear performance of two large-thickness precast shear walls is comparable to that of CIP walls. The relative error of the peak load is less than 10% for three specimens in flexural failure mode. The yield load of shear walls is relatively large and the stage between yield and failure is satisfactory. The shear performance of shear walls decreases slowly after reaching its peak value. Meanwhile, we have conducted the qualitative analysis of structural reliability for large-thickness precast shear walls in component production, quality inspection, wet work, and shear performance.

Coal Mine Fire Emergency Rescue Capability Assessment and Emergency Disposal Research

Nowadays, underground coal mine accidents occur frequently, causing huge casualties and economic losses, most of which are gas explosion accidents caused by fires. In order to improve the emergency rescue capability of coal mine fires and reduce the losses caused by coal mine fires, this article is dedicated to the assessment of coal mine fire rescue capability. Taking the fire emergency rescue system of Lugou mine as an example, based on the introduction of gray system theory and gray evaluation method, an evaluation model was established to assess the risk of the fire emergency rescue index system of Lugou mine. Four primary and 19 secondary indicators were delineated, and a hierarchical structure model of the fire emergency rescue capability of the Lugou mine was established by combining expert opinions, and the weights of indicators at all levels were calculated by using hierarchical analysis. We then used the gray system evaluation method and expert scoring to judge the safety level of various indicator factors in the index system. The evaluation results show that the risk level of the emergency rescue system of the Lugou mine fire is higher than the fourth level. The main risk indicator factors are firefighting equipment, decision-making command, emergency education and training, and fire accident alarm. In response to this evaluation result, corresponding control measures were formulated in four aspects: rescue organization guarantee, personnel guarantee, material guarantee, and information guarantee, which optimally improved the emergency rescue capability of the Lugou mine fire and reduced the loss caused by fire.

Assessment of Hg pollution in stream waters and human health risk in areas impacted by mining activities in the Ecuadorian Amazon.

Illegal gold mining activities have contributed to the release and mobilization of Hg and environmental degradation in many parts of the world. This study aims to determine the concentration of Hg in five provinces of the Amazon Region of Ecuador, in addition to assessing the risk to human health of exposed populations, applying deterministic and probabilistic methods. For this purpose, 147 water samples were collected in rivers and streams crossing and/or located near mining areas. As a result, 100% of the samples analyzed exceeded the maximum permissible limit (MPL) according to the water quality criteria for the preservation of aquatic life of the Ecuadorian regulations, while 7% of the samples exceeded the MPL for drinking water. On the other hand, considering the European Environmental Quality Standard (EQS) for surface water bodies, in our study, 100% of the samples exceed the maximum permissible limit (0.07µg/L), and with respect to the Canadian water quality guidelines, 35% of the samples exceed the permissible limit (0.001mg/l) for drinking water, and 100% of the samples exceed the limit for life in water bodies (0.0001mg/l). The risk assessment revealed that the probability of developing adverse health effects from exposure to Hg is below the recommended limits according to the probabilistic assessment; this is in relation to the criterion of residential and recreational use of water resources. However, it was identified that the child population doubles the acceptable systemic risk level according to the results of the deterministic assessment in the residential scenario. This information can be used by decision-makers to implement strategies to reduce Hg contamination and exposure of the population in Ecuadorian Amazonian rivers.

Composite power system risk evaluation considering the accurate model of renewable power output

The fluctuation of renewable energy will threaten the reliable operation of the composite transmission and generation power system, so the risk level of the composite system with renewable energy attached must be studied. However, the accuracy of the renewable energy model has typically been overlooked in current risk assessment approaches. Therefore, this study provides an accurate hybrid wind/solar power output model that takes the wind farm’s seasonal and spatial characteristics, as well as the correlation between wind and solar PV power into account. For the first, build the seasonal Weibull model of the wind speed and correct the speed captured by each wind turbine considering different spatial characteristics of the wind farm. Secondly, build the probability distribution function of the solar power based on the kernel density estimation method. In the next, construct the joint probability distribution function considering the correlation between wind and solar PV power based on copula theory. Then, using the suggested accurate renewable energy model, the sequential Cross-entropy (SCE) technique is utilized to evaluate the risk indices of the composite system with renewable energy. To validate the models and technique, the modified IEEE-RTS79 is studied. The findings indicate that the accuracy of the renewable energy model influences the risk assessment outcomes.

Topological properties of reconstructed credit networks and banking systemic risk

Financial bipartite networks provide channels for contagion risks and their topological properties determine financial stability. We enrich the bipartite network reconstruction methods proposed by Ramadiah et al. (2020) and extend them to the Chinese banking system. By comparing the reproducibility of the real credit market and the corresponding systemic risk, the impact of topological properties for different reconstructed bipartite networks on financial stability is analyzed. The empirical evidence shows that network reconstruction methods based on maximum entropy ensembles capture more properties in the real credit network. It also highlights that the different systemic risk level is mainly contributed by the topological properties based on common exposures. These analyses for topological properties provide regulatory insights for systemic risk prevention. It shows that reducing credit similarity across banks while increasing credit diversification in different sectors helps to control systemic risk. The results imply the possibility of increasing financial stability through the macro-regulation of the credit market structure.

The Intersectoral Systemic Risk Shock of Emergency Crisis Events in China’s Financial Market: Nonparametric Methods and Panel Event Study Analyses

By employing two systemic risk methods, the marginal expected shortfall (MES) and the component expected shortfall (CES), this paper measures the systemic risk level of all sectors in China’s financial market from 2014 to 2022; thereby, it researches the total effect of sectoral systemic risk using a panel event study model during the three main emergency crisis events. Moreover, two nonparametric methods are utilized, the Wilcoxon signed rank sum test and the bootstrap Kolmogorov–Smirnov test, in order to investigate the changes in individual effects and the dominant ranks of sectoral systemic risk. The empirical results show that (1) the mean values and volatilities of CES and MES of all sectors have a higher level of magnitude in the extreme risk status than those in the normal risk status; (2) by comparing the total effects of three crisis events, we find that different from the continuous shock effect caused by two other events, sectoral systemic risk has a hysteresis effect on the entire market after the outbreak of COVID-19; (3) the long-term and short-term individual effects of sectoral systemic risk in all sectors are different from each other during three events; and (4) the dominance tests of MES are more sensitive and thus better demonstrate the changes in the rankings of sectoral systemic risk than the dominant tests of CES during the emergency crisis events.

Financial Risk Measurement and Spatial Spillover Effects Based on an Imported Financial Risk Network: Evidence from Countries along the Belt and Road

Using the financial market data of 35 countries along the Belt and Road (B&R), this paper constructs an imported financial risk network based on the conditional expected shortfall (CoES) to measure the systemic financial risk of the countries along the B&R. Furthermore, complex network theory is combined with spatial econometrics to construct a spatial, financial network panel model to measure the spatial spillover effects of imported financial risks and further explore the macroeconomic influences on systemic financial risks. The results show that among the countries along the B&R, the level of systemic financial risk in the European region is higher than that in the Asian region from the imported risk perspective. The spatial spillover effect of financial risk and the spatial spillover effect from the imported risk perspective have time-varying characteristics, with the spatial spillover effect increasing significantly during crisis periods. In addition, indicators of the three dimensions of economic openness, the institutional environment, and the external policy environment all have significant effects on systemic financial risk, but the effects differ across regions and periods.

Financial crisis probability measurement model

Methods. The research used the method of analysis and synthesis – to clarify the nature of modern financial crises, the method of grouping – to determine the types of financial crises, general and specific – to differentiate between different types of financial crises, econometric methods – to quantify the level of systemic risk in the financial sector that leads to the financial crisis. Results. Excessive credit growth, the main cause of financial crises, is reflected in the insufficient capitalization of the financial sector. The paper briefly reviews the theoretical and empirical studies on the developments in these markets around the financial crisis. Market-based measures of systemic risk, such as SRISK, which stands for systemic risk, allow monitoring of how such vulnerabilities emerge and progress in real time. Novelty. This paper presents a quantitative assessment of the level of systemic risk in the financial sector that leads to a financial crisis. The model builds on the theory that deleveraging will have a price impact and the greater the magnitude of the deleveraging, the more dangerous the adjustment. In its most extreme case, the real economy has restricted access to credit as the financial sector experiences a fire sale, thus endogenously generating a financial crisis. Practical value. In an econometric framework, the relationship between SRISK and severity of financial crisis for different developed countries is given. The paper focuses on financial crises characterized by disruptions in credit supply, the lower tail of which may be related to various factors. A report on the probability of a financial crisis is provided in real-time from an indication of excessive credit growth. The study shows the important role of the cross-border external effect of financial noncapitalization.

Safety Evaluation Modelling of Hydrogen Energy Industrial Chain for Transportation-energy Integration System in China

This paper divided the safety evaluation indexes of hydrogen energy industrial chain for transportation-energy integration in China into four target tiers, such as hydrogen production safety, storage & transmission safety, supply safety and hydrogen utilization safety. Then the influential factors of security risks under different target tiers were analyzed, and the evaluation index system of security risks were established. Furthermore, according to the characteristics of different target tiers of hydrogen energy industrial chain, the safety evaluation model was constructed by combining analytic hierarchy process with risk assessment matrix. This safety evaluation model can assess the safety status of hydrogen energy chain quantitatively and qualitatively, including calculating the weight of each index and analyzing the risk level of whole system. Moreover, such modeling method could provide a core assessment framework for enterprises and industries related to hydrogen energy to realize real-time security monitoring and alarm.

Reconciling crop production and ecological conservation under uncertainty: A fuzzy credibility-based multi-objective simulation-optimization model

To cope with the problems of agricultural water conflicts and secondary soil salinization in arid regions, a fuzzy credibility-based multi-objective simulation-optimization model is proposed for optimizing irrigation water allocation and crop area planning under uncertainty. This model combines simulation module of enabling to quantify daily physical process of water-salt movement among soil water, crop root zone and groundwater aquifers, optimization module of managing water resources and fuzzy credibility-constrained programming into a general framework. It's applied to a case study in the Jiefangzha Irrigation Subarea in Hetao Irrigation District, Northwest China. Three objectives encompassing maximizing net economic benefits, maximizing nutritional water productivity and minimizing carbon emissions from agricultural system are interconnected through decision variables. Four credibility scenarios of fuzzy constrains including β = 0.6 to 0.9 are presented for obtaining decision-making solutions. Through NSGA-III, such a high-dimensional multi-objective problem is solved. This study uses the multi-objective constraint-handling strategy to handle constraints, which exploits the effective information within infeasible solutions. Moreover, it emphasizes the importance of soil water-salt movement processes in determining optimal solutions and helps decision makers weigh the system outputs and risk level of violating constraints. Results illustrate that when β increases from 0.6 to 0.9, net economic benefit decreases from 1.742 × 109 Yuan to 1.706 × 109 Yuan, nutritional water productivity decreases from 9136.0 kcal/m3 to 8819.6 kcal/m3, and carbon emissions increase from 439.6 × 106 kg. C to 441.6 × 106 kg.C, which shows that an increasing credibility level leads to lower system benefits and conservative system outputs. The results can provide valuable information for managing irrigation water resources and controlling salinity accumulation. Furthermore, dynamic decisions related to water-salt movement processes can be readily generated. These findings show that the developed approach is globally applicable for managing irrigation water in arid and semiarid regions that face similar problems.

The impact of load-PV profile resolution on distribution system risk assessment

Risk assessment is utilized to evaluate the risk level of the system and guide further operation and planning of utilities. However, to lower the cost of communication and storing, only a coarse resolution profile of load and PV can be collected and used to evaluate the risk level of the system, which may lead to inaccurate assessment. To this end, this paper investigates the impact of load-PV profile resolution on distribution system risk assessment. A super-resolution Generative Adversarial Network with pre- and post-processing processes is proposed to restore the high-frequency component of the load-PV profile. Then, with the generated high-resolution profile, a risk assessment model based on the exterior point method is proposed to evaluate the risk level of the distribution system. Case studies in a modified 33-bus system showed that the proposed super-resolution method could achieve the best performance to restore the peak values and high-frequency component of the load-PV profile compared to the other four methods. In addition, compared to super-resolution Generative Adversarial Networks without the post-processing process, the accuracy of risk assessment can be significantly improved using the proposed super-resolution method, which proves that the post-processing process is necessary.

The impact of the COVID-19 pandemic on the equity market risk measured by the beta coefficient

The beta coefficient () is one of the most popular measures of the risk associated with investing in stocks. In the case of the simple linear regression model, the coefficient shows what change in the rate of return on a companys shares will occur when the market rate of return on shares increases by one percentage point. The aim of the study presented in the article is to compare the value of the coefficient of the shares in the largest companies listed on the Warsaw Stock Exchange (WSE) during the COVID-19 pandemic (20202021) and in the period directly preceding its outbreak (20182019). The considered hypothesis is that the spread of the COVID-19 pandemic had an impact on the value of the coefficient of the shares of selected companies listed on the WSE. In order to verify the hypothesis, the ordinary least squares (OLS) method was used to estimate the coefficient of WSE companies for the indicated research periods. Four different time intervals of returns were used to estimate the coefficient: daily, weekly, biweekly and monthly. The differences between the values of the shares of the issuers qualified for the study proved statistically significant (when verified with the t-test for dependent groups) for all of the indicated time intervals of returns. The research results show a significant change in the value of the coefficient of the shares of the largest WSE issuers during the COVID-19 pandemic in comparison to the previous years, which indicates a higher level of systematic risk for these companies, previously considered as safe. These results are consistent with the research conducted on global capital markets.

Struktur Kapital dan Diskresi Manajerial terhadap Pengungkapan Corporate Social Responsibilty (CSR)

The more companies in one area or region will have an impact and contribution to the community and the surrounding environment. Corporate social responsibility (CSR) is able to bring a better oriented company, and by taking into account the social principles of society, stakeholders, environmental principles, and also no less important, namely the discretionary actions of management. Management discretionary actions such as actions to manage excess costs contained in management. CSR practices reduce the level of asymmetric information and agency costs, such as an irregular CSR-related information, not all of which are available and agency costs are also limited, but the level of systematic risk and the cost of capital, which ultimately increases the possibility of increasing equity while reducing dependence on external financing and debt. CSR is realized by the company's management with the aim, as a strategy to protect itself, which allows personal gain to be obtained by investing shares in the company. This study aims to determine the contribution of a company's capital structure and managerial discretion to the CSR defense strategy of companies in Indonesia. This research is a quantitative research. Sources of research data were obtained from 348 companies listed on the Indonesia Stock Exchange and published financial reports and annual reports from 2017-2021. The Fixed Model Effect research model, the results of this study indicate that there is no significant relationship between capital structure and managerial discretion on CSR.

The income bond puzzle

The income bond puzzle

Artificial Market Timing in Mutual Funds

AbstractWe document statistically significant relations between mutual fund betas and past market returns driven by fund feedback trading. Against this backdrop, evidence of “artificial” market timing emerges when standard market timing regressions are estimated across periods that span time variation in fund systematic risk levels, as is typical. Artificial timing significantly explains the inverse relation between timing model estimates of market timing and stock selectivity. A fund’s feedback trading relates to its past performance and remains significant after accounting for trading on momentum. Fund flows suggest that investors value feedback trading, which helps hedge downside risk during bear markets.

Research on Safety Risk Management of a Steel Bracing System Based on Catastrophe Theory

The stability of a steel bracing system is one of the most important indicators by which to measure the stability of the foundation pit. Although a steel bracing system can be monitored using the axial force data, it is subject to the risk of sudden changes due to certain factors and has the characteristics of dynamic discontinuity. Therefore, safety risk management should be applied to the mutability of steel bracing systems to ensure stability. We used the steel bracing system of a foundation pit in Ningbo City, China, as the research object. First, through fault tree analysis (FTA) of the characteristics of the steel bracing system, a safety risk identification of the catastrophe risk was carried out. Second, the safety risk was standardized, and a safety risk evaluation index system was established; the validity and stability of the index system were then verified. Next, a catastrophe theory-based evaluation model was established to determine the safety risk level of the steel bracing system. Finally, a steel bracing risk management process was designed, and a safety risk response was proposed based on the results of the evaluation model. The result was that the membership function value belongs to the general risk area, which accords with the actual state of steel bracing in engineering, and subsequent safety risk response measures can be applied. The proposed method performs well in identifying the risk of sudden changes in steel bracing systems; it also rates the risk and offers response measures to ensure the stability of the steel bracing system. Additionally, this method is of significance due to its applicability in various projects.

Early Warning of Systemic Financial Risk of Local Government Implicit Debt Based on BP Neural Network Model

In recent years, local governments have boosted their local economies by raising large amounts of debt. Even though the state further strictly controls local government debt, the hidden debt formed by the local government borrowing in disguised form can infect systemic financial risks, creating an urgent need to carry out risk warning based on local government hidden debt. The paper uses the macro indicators of local government implicit debt risk at the prefecture-level city level, and introduces the micro indicators of PPP projects, financing platform bank debt, and urban investment debt to establish a BP neural network model. We not only study the contagion effect of local government hidden debt on systemic financial risks, but also predict the systemic financial risks in 2019 and construct an early warning risk system based on the prefecture-level city data from 2015 to 2018. In addition, the early warning effect of local government implicit debt on systemic financial risk under different stress scenarios is investigated. The study found that the implicit debt risk of local governments, the scale of financing platform bank debt, the scale of PPP, and the scale of urban investment bonds have a significant impact on systemic financial risks. The neural network model constructed by introducing these four variables at the same time can better predict the level of systemic financial risk. The model can also accurately predict the changes in systemic financial risks under the stress test of the increase in hidden debt of different local governments, and has a good early warning effect.

Risk dynamics for marine systems: towards a bio-inspired framework for dynamic risk assessment

AbstractThe development of innovative, complex marine systems, such as autonomous ship concepts, has led to risk-based approaches in design and operation that provide safety level quantification and continuous risk assessment. The existing approaches to dynamic risk assessment mainly aim at updating accident probabilities for specific risk scenarios, based on knowledge of system operation and failure, as well as on past accident and failure information. However, for innovative marine systems that include complex interactions, our ability to identify anything that might go wrong is very limited, which may lead to unidentified risks, and failure data may not be available. This paper presents the foundations of a framework for dynamic risk assessment, which is equally applicable to manned and autonomous ships and mainly relies on information about the safe operational envelope and real-time information regarding deviations from safety. Inspiration is drawn from how the biological immune system identifies the risk of infection in a dynamic environment. The objective is to show the feasibility and benefits of our approach for quantifying the operational risk of marine systems. This paper provides the conceptual basis for developing ship specific applications and describes a process for dynamic risk assessment that is methodologically based on artificial immune systems. To demonstrate the implementation of our framework, we described, an illustrative example that involves a ship in a grounding scenario. The results show that the bio-inspired assessment process and risk description can reflect the changes of the risk level of a marine system.