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.

Sustainability of Bridges:Risk Mitigation for Natural Hazards

Bridges serve as essential parts of transportation infrastructure,facilitating the movement of people and goods across rivers,valleys,and other obstacles.However,they are also susceptible to a wide range of natural hazards,including floods,earthquakes,and landslides,which can damage or even collapse these structures,leading to severe economic and human losses.A risk index has been developed to address this issue,which quantifies the likelihood and severity of natural hazards occurring in a specific location.The application of risk indices for natural hazards in bridge management involves a data collection process and mathematical modelling.The data collection process gathers information on bridges’location,condition,and vulnerability,while mathematical modelling uses the data to assess the risk of natural hazards.Overall,risk indices provide a quantitative measure of the vulnerability of bridges to natural hazards and help to prioritize maintenance and repair activities.Mitigation measures are then evaluated and implemented based on the risk assessment results.By using this tool,the UBMS research group has developed an algorithm for risk assessment which will be essential in the decision-making process,specifically focused on enhancing Fund Optimization,Deterioration Modelling,and Risk Analysis.These developments effectively fulfill the primary objectives associated with addressing and mitigating hazards.This development also helps bridge managers understand the potential threats posed by natural hazards and allocate resources more efficiently to ensure the safety and longevity of critical transportation infrastructure.

Systemic Risk of Conventional and Islamic Banks: Comparison with Graphical Network Models

The main aim of this paper is to compare the stability, in terms of systemic risk, of conventional and Islamic banking systems. To this aim, we propose correlation network models for stock market returns based on graphical Gaussian distributions, which allows us to capture the contagion effects that move along countries. We also consider Bayesian graphical models, to account for model uncertainty in the measurement of financial systems interconnectedness. Our proposed model is applied to the Middle East and North Africa (MENA) region banking sector, characterized by the presence of both conventional and Islamic banks, for the period from 2007 to the beginning of 2014. Our empirical findings show that there are differences in the systemic risk and stability of the two banking systems during crisis times. In addition, the differences are subject to country specific effects that are amplified during crisis period.

PRICING CATASTROPHE OPTIONS WITH COUNTERPARTY CREDIT RISK IN A REDUCED FORM MODEL

In this paper, we study the price of catastrophe Options with counterparty credit risk in a reduced form model. We assume that the loss process is generated by a doubly stochastic Poisson process, the share price process is modeled through a jump-diffusion process which is correlated to the loss process, the interest rate process and the default intensity process are modeled through the Vasicek model： We derive the closed form formulae for pricing catastrophe options in a reduced form model. Furthermore, we make some numerical analysis on the explicit formulae.

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.

基于相关系数-熵-二维云模型的装配式建筑施工风险测度

装配式建筑施工过程要在多维空间中进行,叠加风险高,事故发生率高于传统现浇建筑施工,因此科学、准确地测度装配式建筑施工风险具有重要的现实意义。根据装配式建筑施工的特点,从人员、机械、环境、技术、管理5个维度建立了装配式建筑施工风险测度指标体系,并构建了相关系数-熵-二维云风险测度模型。实例应用结果表明:该测度模型较全面、客观、准确地反映了装配式建筑施工风险要素,能够有效实现装配式建筑施工过程风险的定量化测度,可为装配式建筑施工安全管理提供有力参考和依据。

基于扭曲风险度量的鲁棒投资策略

投资组合策略在很大程度上取决于损失的基本分布.因此当损失的分布信息只能通过有限的数据样本来观察时,投资组合策略模型的稳健性是至关重要的.假设损失的基本分布具有已知的均值和方差且位于一个以经验分布为中心,以Wasserstein距离为半径的球内,本文建立了一个基于扭曲风险度量的稳健投资组合策略模型,并将其转化为更简便的等价形式.此外,本文运用模拟和实证研究证明了该模型的有效性.

情绪对矿工安全行为能力影响研究

为减少煤矿生产中安全事故的发生,从情绪控制角度,基于效价-唤醒度(V-A)情绪模型,并结合情绪唤醒方法和生理测量技术,开展矿工安全行为能力认知试验;然后通过测量不同情绪唤醒下的注意力和决策时间,采用回归分析法,探究不同情绪效价下唤醒度对矿工安全行为能力的影响。结果表明:低唤醒度正性情绪中,唤醒度的降低会使矿工注意力减弱、决策时更厌恶风险;在正性情绪的高唤醒度区间,随着唤醒度的提高,矿工注意力和决策厌恶风险程度先增加后减少,直到低于中性情绪;低唤醒度负性情绪中,唤醒度降低会使矿工注意力和风险厌恶程度都降低,在负性情绪的高唤醒度区间,唤醒度的提高同样使注意力和决策的风险厌恶程度先增加后减少,甚至直到低于中性情绪;相较之下,在情绪的高唤醒度区间,正性情绪唤醒度的提高更容易使矿工安全行为能力降低到中性情绪水平以下。

基于蒙特卡罗法的高校易燃易爆实验室不安全因素风险评估

为了减少高校实验室火灾爆炸事故,参考“2-4”模型理论,以实验开展流程对2001年来发生的46起火灾爆炸事故进行分析,基于蒙特卡罗法构建了不安全因素风险评估模型。对实验前准备、实验操作过程、实验后整理、实验材料、仪器设备5个环节的不安全因素风险后果值进行累计概率分布,通过敏感度分析得出各不安全因素对风险值的影响。结果表明,实验材料、实验操作过程2个环节的风险值最高;“未熟知实验危险有害因素”“废弃物处理不当”“实验试剂材料违规购买、存放或使用”“危险实验未防护”及“试剂材料选取方式不符合规定或更改设备操作顺序”5个不安全因素的敏感度值大于30%,对风险值的影响较大。在此基础上对各环节及重点不安全因素的提出事故预防措施。

历史文化名镇游客感知价值测量模型及实证检验——以邯郸市永年区永年广府城为例

以邯郸市永年区永年广府城为研究对象,综合考虑风险感知与文化价值特性,针对历史文化名镇开发符合古镇特征的游客感知价值测量表,探寻古镇类型景区游客感知价值的影响因素。结果表明,历史文化名镇游客感知价值测量表由人居环境价值、服务价值、情感价值、文化认知价值、文化观赏价值、文化产品价值、风险感知和成本感知8个维度27个测量指标构成;文化认知价值、文化产品价值和文化观赏价值是历史文化名镇有别于其他景区共性维度以外的特殊维度;游客在发生公共危机事件时形成的风险感知对历史文化名镇游客感知价值具有显著影响。

铁路安全风险控制措施有效性评估方法研究

铁路安全风险控制备受关注,对控制措施开展有效性量化评估是确保安全风险切实受控的重要保障。结合铁路实际和双重预防机制建设,采用现状调研分析、分类赋值、多维度矩阵量化、相互独立参量的线性叠加、应用验证等方法,研究提出铁路安全风险控制措施有效性评估方法。研究发现,铁路在安全风险控制措施制定、控制措施分类、风险等级划分等方面有了明确的指导要求;控制措施有效性影响因素主要包括措施类型、措施实用性、措施可用性和措施独立性等4个方面;措施有效性评估模型需要综合考虑有效性量化的多种维度。结果表明,在Bow-tie分析基础上,安全风险控制措施有效性评估方法能够应用于实际案例分析,初步验证了评估方法的可操作性、正确性。

主动脉夹层患者术后呼吸机相关肺炎的危险因素分析

目的分析主动脉夹层(aortic dissection,AD)患者术后呼吸机相关肺炎(ventilator associated pneumonia,VAP)发生的危险因素,并探究预防措施。方法回顾性分析2021年3月—2022年3月南华大学附属第二医院收治的296例AD患者的临床资料。通过医院电子病例数据库检索诊断为AD且顺利完成手术的患者,根据术后是否发生VAP分为VAP组和N-VAP组。采用单因素分析筛选出差异有统计学意义的肺炎相关危险因素作为自变量,以患者术后是否发生VAP为因变量进行多因素logistic回归分析,筛选危险因素。结果本研究共纳入296例AD患者,其中术后发生VAP的患者43例,VAP发病率为14.53%;VAP组与N-VAP组是否急诊、通气时间、手术时间、是否多次气管插管、发病至手术时间比较,差异有统计学意义(P<0.05)。以AD患者术后是否出现VAP为因变量,单因素分析有差异的是否急诊、通气时间、手术时间、是否多次气管插管、发病至手术时间为自变量进行多因素logistic回归分析,结果显示,通气时间延长、手术时间≥5 h、有多次气管插管是AD患者术后出现VAP的危险因素(P<0.05)。结论本研究对AD患者术后VAP发生的影响因素进行初步评估,其中通气时间较长、多次气管插管及手术时间≥5 h是AD患者术后VAP发生的危险因素。

基于Bow-Tie模型和未确知测度理论的煤矿透水风险分析

为了克服煤矿井下透水事故安全性评价相关因子的不确定性,以及权重指标赋值模糊的问题,采用Bow-Tie模型分析法通过对煤矿井下的人、物、环境、管理4个方面的分析研究,建立出煤矿透水事故的Bow-Tie评价模型,把得到的12项透水事故的影响因子作为煤矿透水事故风险评估的评价指标。通过层次分析法对指标进行权重的赋值,最后由未确知测度法确定煤矿透水事故风险评价等级。通过对小回沟煤矿进行实例评估分析,评价结果与该煤矿实际相符合,可见该法的合理性和适用性,可以为煤矿透水事故的风险评价提出一些指导。

工业软件供应链安全风险分析及应对措施

随着信息化和工业化的深入融合,工业软件供应链的安全问题逐渐凸显。文章深入剖析了工业软件供应链存在的问题、威胁和风险,并详细描述了软件供应链攻击的类型、特点以及可能带来的影响。为了解决这些问题,文章提出了一套基于信息化运维的工业软件供应链安全防护模型,并设计了相应的防护措施。同时,通过整合人工智能、区块链和云计算等先进技术,有效提高了供应链防护的效率和效果。

基于商业银行贷款风险度量的Credit Risk+模型

文章运用Credit Risk+模型对我国商业银行贷款风险度量进行实证分析.原Credit Risk+模型在计算违约损失率时使用历史平均值的方法有很大的缺陷,现运用清算LGD方法计算贷款的违约损失率.同时,采用更有效的CVaR方法度量风险,提高违约损失的计算精度.

Claim reserving for insurance contracts in line with the International Financial Reporting Standards 17:a new paid‑incurred chain approach to risk adjustments

This study considers the risk management of insurance policies in line with the implementation of the new International Financial Reporting Standards 17.It applies the paid-incurred chain method to model the future unpaid losses by combining the information channels of both the incurred claims and paid losses.We propose the recovery of the empirical distribution of the outstanding claims liabilities associated with a group of contracts via moment-based density approximation.We determine the risk measures and adjustments that are compliant with the new standard using the Monte–Carlo simulation method and approximated distributions.The historical data on the aggregate Ontario automobile insurance claims over a 15-year period are analyzed to examine the appropriateness and accuracy of our approach.

Indifference Pricing in the Single Period Binomial with Complete Market Model

Binomial no-arbitrage price have a method is the traditional approach for derivative pricing,which is,the complete model,which makes possible the perfect replication in the market.Risk neutral pricing is an appropriate method of asset pricing in a complete market.We have discussed an incomplete market,a non-transaction asset that produces incompleteness of the market.An effective method of asset pricing in incomplete markets is the undifferentiated pricing method.This technique was firstly introduced by Bernoulli in(1738)the sense of gambling,lottery and their expected return.It is used to command investors'preferences and better returns the results they expect.In addition,we also discuss the utility function,which is the core element of the undifferentiated pricing.We also studied some important behavior preferences of agents,and injected exponential effect of risk aversion in the model,so that the model was nonlinear in the process of claim settlement.

维持性血液透析患者肌少症发生风险预测模型的构建

目的探讨血液透析患者肌少症发生的危险因素的风险预测模型的构建。方法纳入2020年1月至2020年12月于本院进行维持性血液透析治疗的246例患者为研究对象,根据患者是否发生肌少症分为肌少症组(n=58)和非肌少症组(n=188),比较分析两组患者临床资料差异,使用多因素Logistic回归方程分析血液透析患者肌少症发生的危险因素,建立Logistic回归预测模型,并通过绘制风险Nomogram图进行可视化。结果血液透析患者肌少症发生率为23.58%;Logistic回归分析显示,高年龄、较长透析龄、营养状况差是血液透析患者肌少症发生的危险因素(均P<0.05),高四肢骨骼肌量、高肌肉力量是血液透析患者肌少症发生的保护因素(均P<0.05)。风险Nomogram图分析显示,基于血液透析患者肌少症发生的危险因素预测血液透析患者肌少症发生的C-index为0.919;ROC曲线分析显示曲线下面积为0.924,敏感性为91.30%,特异度为77.38%,尤登指数为0.687。结论年龄、透析龄、营养状况及四肢骨骼肌量、肌肉力量是血液透析患者肌少症发生的影响因素,可用于预测血液透析患者肌少症发生。

双传染渠道下银行系统性风险的测度研究

运用改进后的双传染渠道模型,依据2014—2022年42家银行的年报数据,从传染损失、倒闭机构数、银行系统损失和溢出至经济系统损失四个维度测度我国银行系统性风险。结果显示,从传染损失或倒闭机构数量单个维度测量系统性风险并分析其生成机制过于片面。综合银行系统损失和溢出至经济系统损失维度能更全面、准确地测度银行系统性风险。降价抛售、债务违约分别是权益损失、银行破产的主要渠道。杠杆高且银行间贷款占比高的银行更脆弱,溢出风险更大。