Risk measurement of international oil and gas projects based on the Value at Risk method

International oil and gas projects feature high capital-intensity, high risks and contract diversity. Therefore, in order to help decision makers make more reasonable decisions under uncertainty, it is necessary to measure the risks of international oil and gas projects. For this purpose, this paper constructs a probabilistic model that is based on the traditional economic evaluation model, and introduces value at risk(VaR) which is a valuable risk measure tool in finance, and applies Va R to measure the risks of royalty contracts, production share contracts and service contracts of an international oil and gas project. Besides, this paper compares the influences of different risk factors on the net present value(NPV) of the project by using the simulation results. The results indicate:(1) risks have great impacts on the project's NPV, therefore, if risks are overlooked, the decision may be wrong.(2) A simulation method is applied to simulate the stochastic distribution of risk factors in the probabilistic model. Therefore, the probability is related to the project's NPV, overcoming the inherent limitation of the traditional economic evaluation method.(3) VaR is a straightforward risk measure tool, and can be applied to evaluate the risks of international oil and gas projects. It is helpful for decision making.

Global and Regional Trends and Projections of Infective Endocarditis-Associated Disease Burden and Attributable Risk Factors from 1990 to 2030

Objective To forecast the future burden and its attributable risk factors of infective endocarditis(IE).Methods We analyzed the disease burden of IE and its risk factors from 1990 to 2019 using the Global Burden of Disease 2019 database and projected the disease burden from 2020 to 2030 using a Bayesian age-period-cohort model.Results By 2030,the incidence of IE will increase uncontrollably on a global scale,with developed countries having the largest number of cases and developing countries experiencing the fastest growth.The affected population will be predominantly males,but the gender gap will narrow.The elderly in high-income countries will bear the greatest burden,with a gradual shift to middle-income countries.The incidence of IE in countries with middle/high-middle social-demographic indicators(SDI) will surpass that of high SDI countries.In China,the incidence rate and the number of IE will reach 18.07 per 100,000 and 451,596 in 2030,respectively.IEassociated deaths and heart failure will continue to impose a significant burden on society,the burden on women will increase and surpass that on men,and the elderly in high-SDI countries will bear the heaviest burden.High systolic blood pressure has become the primary risk factor for IE-related death.Conclusions This study provides comprehensive analyses of the disease burden and risk factors of IE worldwide over the next decade.The IE-associated incidence will increase in the future and the death and heart failure burden will not be appropriately controlled.Gender,age,regional,and country heterogeneity should be taken seriously to facilitate in making effective strategies for lowering the IE disease burden.

Risk Management： A New Project Management Perspective

Risk management in Botswana has been very ineffective at assisting projects to be on time, on budget, and meeting client＇s/buyer＇s expectations. Traditional risk management attempts to manage, control, and direct a project through various phases, from planning and design, through procurement, and to construction. However, the risk management in Botswana seems to be either not implemented or not successful. The project performance in Botswana has a poor performance record. The researchers are attempting to identify why the traditional project/risk management is not working. In analyzing the problem in Botswana, the researchers discovered that the traditional risk management model was theoretically unsound, and designed a new project and risk model, with an entirely different approach to risk. The new model is an outgrowth of the highly successful Performance Information Procurement System （PIPS） and the Information Measurement Theory （IMT）/Kashiwagi Solution Model （KSM） concepts. The approach has been presented to some Botswana clients and academics and has received a favorable response. The development of the new risk model will lead to a huge change in the paradigm for delivering projects in Botswana. The theoretical development of the new risk model is ongoing at the University of Botswana as a part of a doctoral dissertation.

Geostatistical Modeling of Uncertainty for the Risk Analysis of a Contaminated Site

This work is a study of multivariate simulations of pollutants to assess the sampling uncertainty for the risk analysis of a contaminated site. The study started from data collected for a remediation project of a steel- works in northern Italy. The soil samples were taken from boreholes excavated a few years ago and analyzed by a chemical laboratory. The data set comprises concentrations of several pollutants, from which a subset of ten organic and inorganic compounds were selected. The first part of study is a univariate and bivariate sta- tistical analysis of the data. All data were spatially analyzed and transformed to the Gaussian space so as to reduce the effects of extreme high values due to contaminant hot spots and the requirements of Gaussian simulation procedures. The variography analysis quantified spatial correlation and cross-correlations, which led to a hypothesized linear model of coregionalization for all variables. Geostatistical simulation methods were applied to assess the uncertainty. Two types of simulations were performed: correlation correction of univariate sequential Gaussian simulations (SGS), and sequential Gaussian co-simulations (SGCOS). The outputs from the correlation correction simulations and SGCOS were analyzed and grade-tonnage curves were produced to assess basic environmental risk.

Research on SAP Business One Implementation Risk Factors with Interpretive Structural Model

The possible risk factors during SAP Business One implementation were studied with depth interview. The results are then adjusted by experts. 20 categories of risk factors that are totally 49 factors were found. Based on the risk factors during the SAP Business One implementation, questionnaire was used to study the key risk factors of SAP Business One implementation. Results illustrate ten key risk factors, these are risk of senior managers leadership, risk of project management, risk of process improvement, risk of implementation team organization, risk of process analysis, risk of based data, risk of personnel coordination, risk of change management, risk of secondary development, and risk of data import. Focus on the key risks of SAP Business One implementation, the interpretative structural modeling approach is used to study the relationship between these factors and establish a seven-level hierarchical structure. The study illustrates that the structure is olive-like, in which the risk of data import is on the top, and the risk of senior managers is on the bottom. They are the most important risk factors.

HOW BIG DATA MAKES CONSTRUCTION PROJECT RISK INTACT

Construction project is not a standalone engineering maneuver.It is closely linked to the well-being of local communities in concern.The city renovation in Beijing down center for Olympic 2008 transformed many antique architecture and regional landscape.It gave a world-recognized achievement in China s modem development and manifested a major milestone in China's economic development.In the course of metro construction projects,there are substantial interwoven municipal structures influencing the success of the projects,which including,but the least,all underground cables and ducts,sewage system,the power consumption of construction works,traffic diversion,air pollution,expatriate business activities and social security.There are many US and UK project insurance companies moving into Asia Pacific.They are doing re-insurance business on major construction guarantee,such as machinery damage,project on-time,power consumption,claims from contractors and communities.Environmental information,such as water quality,indoor and outdoor air quality,people inflow and lift waiting time play deterministic roles in construction's fit-touse.Big Data is a contemporary buzzword since 2013,and the key competence is to provide real time response to heuristic syndrome in order to make short-term prediction.This paper attempts to develop a conceptual model in big data for construction

RISK MODEL FOR ENERGY PERFORMANCE CONTRACTING IN CORRECTIONAL FACILITIES

Energy performance contracting provides guaranteed minimum energy savings to building owners,enabling them to finance project costs using utility savings over the duration of the project.This has been an attractive project delivery method for organizations with reduced budgets for capital projects,particularly among correctional facilities which frequently have lengthy periods of deferred maintenance and ongoing building operations and maintenance concerns.This research builds on a previously developed project factors risk framework for energy service companies undertaking building retrofits.This paper proposes a risk analysis and evaluation model that includes quantitative,expert-based,and probabilistically derived information.Expected cost was used to evaluate risks over lengthy project life cycles and a new metric was developed for use in the model-expected life cycle value.Model results reveal that the most critical risk factors relate to the reduced availability of“low-hanging fruit”energy conservation measures,work scopes based on traditional design-bid-build procurement,unavailable or inaccurate facility information,facility age and current code requirements,and conducting the investment grade audit too quickly.The life cycle cost-based risk model employed in this paper is proposed as an advancement over traditional risk management methods,and it is expected to be applicable,with modification,across other municipal and state government subdomains,especially high security projects.

Impacts of Chinese Translators’Risk Management Ability on Translation Project Outcomes:A Study Based on Structural Equation Model

Translation project outcomes are affected by many factors.Hence,this study explored the impact of risk management ability of translators on translation project outcomes in China.In the study,we took risk management ability of translators in translation projects as the research objective and collected research data through an online questionnaire to establish a structural equation model.Based on these data in the model,we analyzed impacts of translators’risk management ability on translation project outcomes.Evidently,risks in project planning during translation as well as proofreading and typesetting after translation affect the delivery and remuneration of translation.The study can help translators correctly recognize and manage the risks in translation practices,increase the success rate of translation projects and further promote the sound development of language services.

Tracking market and non-traditional sources of risks in procyclical and countercyclical hedge fund strategies under extreme scenarios:a nonlinear VAR approach

The subprime crisis was quite damaging for hedge funds.Using the local projection method(Jordà2004,2005,2009),we forecast the dynamic responses of the betas of hedge fund strategies to macroeconomic and financial shocks—especially volatility and illiquidity shocks—over the subprime crisis in order to investigate their market timing activities.In a robustness check,using TVAR(Balke 2000),we simulate the reaction of hedge fund strategies’betas in extreme scenarios allowing moderate and strong adverse shocks.Our results show that the behavior of hedge fund strategies regarding the monitoring of systematic risk is highly nonlinear in extreme scenarios—especially during the subprime crisis.We find that countercyclical strategies have an investment technology which differs from procyclical ones.During crises,the former seek to capture non-traditional risk premia by deliberately increasing their systematic risk while the later focus more on minimizing risk.Our results suggest that the hedge fund strategies’betas respond more to illiquidity uncertainty than to illiquidity risk during crises.We find that illiquidity and VIX shocks are the major drivers of systemic risk in the hedge fund industry.

Common Management Process Model of New TQM Based on the Situation Analysis

In the previous study, we suggested the concept of new TQM based on the consideration of basic concept of Quality Control. Also, in the previous study, we suggested the target domains and entities of product and process based on the TQM Matrix and view point of Three Dimensional Unification Value Models for managing quality of organization systems. Furthermore, in the previous study, we suggest the Common Management Process of organizations. Based on the above suggestion, in this paper, we would like to propose the Common Management Process Model of Total Quality Management based on the consideration of situation analysis and more precise definition of TQM Matrix and Three Dimensional Unification Value Model of “Product and Process”. Improvement of quality and efficiency of organization management can be expected by the integration of conventional different management such as quality assurance, quality improvement, risk management, investment individually from the view point of common management process.

南四湖不同起调水位汛期调水风险传导规律

南水北调东线工程通水以来,有效缓解了山东半岛等地的缺水问题,但水资源供需矛盾依然突出,汛期调水将成为解决该矛盾的方式之一。汛期调水时,湖周河道开闸泄洪,非汛期积累于河道中的污染物随水流下泄入湖,使得流域水环境风险显著增加。为科学支撑东线后续工程汛期调水水环境风险管控和探究湖区内部风险传导机制,以南水北调东线调蓄湖泊南四湖上级湖段为例,构建水环境风险空间传导分析模型,计算相邻子湖区处于不同风险状态组合的概率,定量评价汛期调水时南四湖上级湖流域水环境风险状态,探讨丰、平、枯3种水平年起调水位下水环境风险在南四湖上级湖的传导规律。结果表明:丰水年高水位调水时,南四湖上级湖水环境风险值最小,枯水年最大;高、中水位调水时,呈由低风险传导至中风险、再传导至高风险的逐步传导模式,而低水位调水时,风险由低风险直接传导至高风险;以平水年为例,白马河区至万福河区93%概率为低—中风险增强型传导、7%概率为低—高风险增强型传导。

基于组织-任务网络的项目进度风险分析

针对工程项目外部进度风险的传播与控制,构建项目组织-任务网络模型,依据级联失效理论,从风险荷载、节点容量、荷载重分配与失效判别规则四方面确定项目进度风险的传播机制.仿真结果表明,组织和任务间的相互关系会扩大外部风险对项目进度的影响,且随机组织失效造成的影响大于关键组织.通过增加风险投入、加强预警、提高容错率可在一定范围内增强项目风险抵抗能力,同时需要加强非关键组织的风险预警与管控,有效控制外部风险对项目进度造成的影响.

引汉济渭工程调水区多源风险评估与对策研究

为评估引汉济渭跨流域调水工程本身及运行管理行为中多源风险导致供水不足的可能性,构建了跨流域调水工程水库-泵站-电站的风险评估框架。将工程管理中的行为与经验以随机、模拟、优化三种调度模式进行数学表达,设置了兼顾工程失能与运行管理的单源、多源调度风险模式和方案集;建立并仿真计算了三种调度模型,获得了不同风险方案的动态调度过程及造成的供水风险;制定了跨流域调水工程的调度风险分级基准,采取专家打分法获取事件发生的初始概率区间,采用集值统计法和改进耦合度模型定量估计各方案发生概率,基于供水风险指标定量估算各方案的损失严重度;划分了风险矩阵的等级标准,结合最低合理可行(ALARP)准则明确了风险可接受程度,提出了非工程措施以管控风险,为引汉济渭工程调水区风险评估和防控提供了理论依据。研究发现:(1)三种调度模式中仅优化调度可满足调水15亿m 3、95%供水保证率的供水目标,且相较于随机调度方式,供水能力提升了13%;(2)单源风险方案的供水风险逐渐向长时间缺水过程发展,多源风险方案面临的调度情况更加复杂,供水风险在各个维度均处于危险状态;(3)处于ALARP区域的风险事件占比超过60%,与工程相关的风险多为小概率高危害式风险,应优先解决处于ALARP区域并预防不可接受区域的风险事件;(4)针对发生概率小但危害性高的供水风险,制定了水库下游人员转移等应急方案,以降低潜在的供水损失。研究结果对于跨流域调水工程的风险管理具有积极的推动作用,强化了ALARP准则在调水工程风险评估中的应用价值。

工程项目组合风险扩散模型的级联失效分析

为构建符合工程项目组合特点的风险扩散模型,解决风险扩散问题。本文考虑风险扩散的双关系载体—项目交互关系和风险因素逻辑关系,构建工程项目组合风险扩散的双层相依网络模型,运用级联失效理论提出风险扩散规则,通过数值仿真分析风险扩散特征。仿真结果发现:工程项目组合中,双层网络模型能够反映风险在项目和风险因素双关系载体中的扩散特征;与单层网络风险扩散模型相比,构建的模型展现出差异性的风险扩散效应,风险扩散在工程项目组合中表现出更剧烈的级联失效过程。风险扩散模型作为工程项目组合风险扩散问题的前置性研究,为进一步风险扩散网络稳定性的研究提供新思路和启发。

基于多粒度语言标度DEMATEL的建筑废弃物资源化PPP项目风险因素研究

为提高建筑废弃物资源化PPP项目风险管理水平,对建筑废弃物资源化PPP项目风险因素进行研究。通过文献梳理和案例分析,识别出建筑废弃物资源化PPP项目的25个风险因素;提出了一种多粒度语言标度DEMATEL群组决策的新方法,并计算各风险因素的中心度和原因度辨析出关键风险因素,针对关键风险因素提出了具体的对策和建议。结果表明:运营成本超支、消费者认可度不足、政策不稳定这3个风险因素为建筑废弃物资源化PPP项目的关键风险因素,在项目进行过程中应予以重点关注,研究结论对建筑废弃物资源化PPP项目的风险防控和管理具有重要意义。

引汉济渭工程初期调水风险特征研究

为解决引汉济渭工程运行中调水风险因素与特征规律识别不全面的问题,以工程运行初期为研究对象,采用专家调查法识别工程主要调水风险因素并确定风险组合类型,再建立危险度模型,分析单一风险因素的稳定性和风险组合危险度的特征规律。研究结果表明:变异系数越大则风险因素稳定性越差,其中管理失误风险因素最不稳定,其值高达0.998;水源不足、需水量增加两类风险因素叠加后风险组合的危险度更高;风险组合的危险度与风险因素数量之间没有明显的正向关系。研究成果补充了引汉济渭工程调水风险特征研究的不足,为制定针对性风险减控和管理策略提供技术支撑。

基于改进FAHP的水利工程EPC总承包项目风险管理研究

结合水利工程EPC总承包项目的自身特点,建立改进FAHP的风险评判模型,最后,进行实证分析。结果表明,基于改进FAHP的水利工程EPC总承包项目风险评判模型具有一定的科学性和适用性,同时,研究结果对提高水利工程EPC总承包项目风险管理水平具有一定的参考意义。

基于AHP和云模型的公路BOT项目风险管理研究

为了降低公路BOT项目的管理风险,保证项目的顺利实施,提出了基于层次分析法和云模型的风险评估体系。从公路BOT项目全寿命周期出发,基于故障树法识别了项目各阶段的风险源,利用层次分析法确定了各风险指标的权重。在此基础上引入风险随机性和模糊性概念,利用模糊数学将风险指标模糊化,结合云模型理论和风险矩阵理论,确定了公路BOT项目的风险的等级,并以某实际公路BOT项目为例,成功验证了本文提出的风险评估体系的有效性。研究成果可以为公路BOT项目风险防控提供依据,为保障BOT项目顺利实施提供新视野。

基于失稳概率的单体滑坡灾害风险定量评价及其工程应用

对潜在滑坡灾害实施风险评价至关重要,但在实际工程中单体滑坡灾害风险评价仍然以定性评价方法为主,由危险性和损失通过风险矩阵得到定性风险等级,存在风险标准多重性和不连续性的问题,不便于在实际工程中对风险大小进行比较并实施分类处置,还可能导致风险评价结果出现误差,误导风险处置。为此,运用概率模型定量描述滑坡灾害的稳定性,同时考虑承灾体的损失大小,得到单体滑坡灾害风险定量评价指标,提出了滑坡灾害风险曲面及风险等值线的概念,并开发相应的评估计算软件,形成了滑坡灾害风险定量评价方法,消除了传统滑坡风险矩阵带来的风险标准多重性和不连续性,提高了评估的准确性。通过对重庆市奉节县6个单体滑坡进行风险定量评价,验证了所提方法的正确性和可靠性,为滑坡灾害风险评价提供了新的途径。

Impacts and risks of“realistic”global warming projections for the 21st century

The IPCC AR6 assessment of the impacts and risks associated with projected climate changes for the 21st century is both alarming and ambiguous.According to computer projections,global surface temperature may warm from 1.3℃to 8.0℃by 2100,depending on the global climate model(GCM)and the shared socioeconomic pathway(SSP)scenario used for the simulations.Actual climate-change hazards are estimated to be high and very high if the global surface temperature rises,respectively,more than 2.0℃and 3.0℃above pre-industrial levels.Recent studies,however,showed that a substantial number of CMIP6 GCMs run“too hot”because they appear to be too sensitive to radiative forcing,and that the high/extreme emission scenarios SSP3-7.0 and SSP5-8.5 are to be rejected because judged to be unlikely and highly unlikely,respectively.Yet,the IPCC AR6 mostly focused on such alarmistic scenarios for risk assessments.This paper examines the impacts and risks of“realistic”climate change projections for the 21st century generated by assessing the theoretical models and integrating them with the existing empirical knowledge on global warming and the various natural cycles of climate change that have been recorded by a variety of scientists and historians.This is achieved by combining the SSP2-4.5 scenario(which is the most likely SSP according to the current policies reported by the International Energy Agency)and empirically optimized climate modeling.According to recent research,the GCM macro-ensemble that best hindcast the global surface warming observed from 1980 to 1990 to 2012–2022 should be made up of models that are characterized by a low equilibrium climate sensitivity(ECS)(1.5℃<ECS≤3.0℃),in contrast to the IPCC AR6 likely and very likely ECS ranges at 2.5–4.0℃and 2.0–5.0℃,respectively.I show that the low-ECS macro-GCM with the SSP2-4.5 scenario projects a global surface temperature warming of 1.68–3.09℃by 2080–2100 instead of 1.98–3.82℃obtained with the GCMs with ECS in the 2.5–4.0℃range.However,if the global surface temperature records are affected by significant non-climatic warm biases—as suggested by satellite-based lower troposphere temperature records and current studies on urban heat island effects—the same climate simulations should be scaled down by about 30%,resulting in a warming of about 1.18–2.16℃by 2080–2100.Furthermore,similar moderate warming estimates(1.15–2.52℃)are also projected by alternative empirically derived models that aim to recreate the decadal-to-millennial natural climatic oscillations,which the GCMs do not reproduce.The proposed methodologies aim to simulate hypothetical models supposed to optimally hindcast the actual available data.The obtained climate projections show that the expected global surface warming for the 21st-century will likely be mild,that is,no more than 2.5–3.0℃and,on average,likely below the 2.0℃threshold.This should allow for the mitigation and management of the most dangerous climate-change related hazards through appropriate low-cost adaptation policies.In conclusion,enforcing expensive decarbonization and net-zero emission scenarios,such as SSP1-2.6,is not required because the Paris Agreement temperature target of keeping global warming<2℃throughout the 21st century should be compatible also with moderate and pragmatic shared socioeconomic pathways such as the SSP2-4.5.