arXiv - QuantFin - Risk Management最新文献_第7页

Stochastic Earned Value Analysis using Monte Carlo Simulation and Statistical Learning Techniques 利用蒙特卡罗模拟和统计学习技术进行随机挣值分析

arXiv - QuantFin - Risk Management Pub Date : 2024-05-31 DOI: arxiv-2406.02589

Fernando Acebes, M Pereda, David Poza, Javier Pajares, Jose M Galan

引用次数: 0

Beyond probability-impact matrices in project risk management: A quantitative methodology for risk prioritisation 超越项目风险管理中的概率-影响矩阵：风险优先排序的量化方法

arXiv - QuantFin - Risk Management Pub Date : 2024-05-31 DOI: arxiv-2405.20679

Fernando Acebes, José Manuel González-Varona, Adolfo López-Paredes, Javier Pajares

{"title":"Beyond probability-impact matrices in project risk management: A quantitative methodology for risk prioritisation","authors":"Fernando Acebes, José Manuel González-Varona, Adolfo López-Paredes, Javier Pajares","doi":"arxiv-2405.20679","DOIUrl":"https://doi.org/arxiv-2405.20679","url":null,"abstract":"The project managers who deal with risk management are often faced with the\u0000difficult task of determining the relative importance of the various sources of\u0000risk that affect the project. This prioritisation is crucial to direct\u0000management efforts to ensure higher project profitability. Risk matrices are\u0000widely recognised tools by academics and practitioners in various sectors to\u0000assess and rank risks according to their likelihood of occurrence and impact on\u0000project objectives. However, the existing literature highlights several\u0000limitations to use the risk matrix. In response to the weaknesses of its use,\u0000this paper proposes a novel approach for prioritising project risks. Monte\u0000Carlo Simulation (MCS) is used to perform a quantitative prioritisation of\u0000risks with the simulation software MCSimulRisk. Together with the definition of\u0000project activities, the simulation includes the identified risks by modelling\u0000their probability and impact on cost and duration. With this novel methodology,\u0000a quantitative assessment of the impact of each risk is provided, as measured\u0000by the effect that it would have on project duration and its total cost. This\u0000allows the differentiation of critical risks according to their impact on\u0000project duration, which may differ if cost is taken as a priority objective.\u0000This proposal is interesting for project managers because they will, on the one\u0000hand, know the absolute impact of each risk on their project duration and cost\u0000objectives and, on the other hand, be able to discriminate the impacts of each\u0000risk independently on the duration objective and the cost objective.","PeriodicalId":501128,"journal":{"name":"arXiv - QuantFin - Risk Management","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141254974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Worst-cases of distortion riskmetrics and weighted entropy with partial information 部分信息失真风险度量和加权熵的最坏情况

arXiv - QuantFin - Risk Management Pub Date : 2024-05-29 DOI: arxiv-2405.19075

Baishuai Zuo, Chuancun Yin

引用次数: 0

An Asymptotic CVaR Measure of Risk for Markov Chains 马尔可夫链风险的渐近 CVaR 度量

arXiv - QuantFin - Risk Management Pub Date : 2024-05-22 DOI: arxiv-2405.13513

Shivam Patel, Vivek Borkar

引用次数: 0

Resilience Analysis of Multi-modal Logistics Service Network Through Robust Optimization with Budget-of-Uncertainty 通过不确定性预算进行稳健优化的多模式物流服务网络弹性分析

arXiv - QuantFin - Risk Management Pub Date : 2024-05-21 DOI: arxiv-2405.12565

Yaxin PangCGS i3, Shenle PanCGS i3, Eric BallotCGS i3

引用次数: 0

Risk, utility and sensitivity to large losses 风险、效用和对巨额损失的敏感性

arXiv - QuantFin - Risk Management Pub Date : 2024-05-20 DOI: arxiv-2405.12154

Martin Herdegen, Nazem Khan, Cosimo Munari

{"title":"Risk, utility and sensitivity to large losses","authors":"Martin Herdegen, Nazem Khan, Cosimo Munari","doi":"arxiv-2405.12154","DOIUrl":"https://doi.org/arxiv-2405.12154","url":null,"abstract":"Risk and utility functionals are fundamental building blocks in economics and\u0000finance. In this paper we investigate under which conditions a risk or utility\u0000functional is sensitive to the accumulation of losses in the sense that any\u0000sufficiently large multiple of a position that exposes an agent to future\u0000losses has positive risk or negative utility. We call this property sensitivity\u0000to large losses and provide necessary and sufficient conditions thereof that\u0000are easy to check for a very large class of risk and utility functionals. In\u0000particular, our results do not rely on convexity and can therefore also be\u0000applied to most examples discussed in the recent literature, including\u0000(non-convex) star-shaped risk measures or S-shaped utility functions\u0000encountered in prospect theory. As expected, Value at Risk generally fails to\u0000be sensitive to large losses. More surprisingly, this is also true of Expected\u0000Shortfall. By contrast, expected utility functionals as well as (optimized)\u0000certainty equivalents are proved to be sensitive to large losses for many\u0000standard choices of concave and nonconcave utility functions, including\u0000$S$-shaped utility functions. We also show that Value at Risk and Expected\u0000Shortfall become sensitive to large losses if they are either properly adjusted\u0000or if the property is suitably localized.","PeriodicalId":501128,"journal":{"name":"arXiv - QuantFin - Risk Management","volume":"2013 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141147627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Risk-neutral valuation of options under arithmetic Brownian motions 算术布朗运动下期权的风险中性估值

arXiv - QuantFin - Risk Management Pub Date : 2024-05-18 DOI: arxiv-2405.11329

Qiang Liu, Yuhan Jiao, Shuxin Guo

引用次数: 0

Is the annualized compounded return of Medallion over 35%? Medallion 的年复合回报率是否超过 35%？

arXiv - QuantFin - Risk Management Pub Date : 2024-05-17 DOI: arxiv-2405.10917

Shuxin Guo, Qiang Liu

引用次数: 0

Data-generating process and time-series asset pricing 数据生成过程和时间序列资产定价

arXiv - QuantFin - Risk Management Pub Date : 2024-05-17 DOI: arxiv-2405.10920

Shuxin Guo, Qiang Liu

引用次数: 0

Research on Credit Risk Early Warning Model of Commercial Banks Based on Neural Network Algorithm 基于神经网络算法的商业银行信用风险预警模型研究

arXiv - QuantFin - Risk Management Pub Date : 2024-05-17 DOI: arxiv-2405.10762

Yu Cheng, Qin Yang, Liyang Wang, Ao Xiang, Jingyu Zhang

{"title":"Research on Credit Risk Early Warning Model of Commercial Banks Based on Neural Network Algorithm","authors":"Yu Cheng, Qin Yang, Liyang Wang, Ao Xiang, Jingyu Zhang","doi":"arxiv-2405.10762","DOIUrl":"https://doi.org/arxiv-2405.10762","url":null,"abstract":"In the realm of globalized financial markets, commercial banks are confronted\u0000with an escalating magnitude of credit risk, thereby imposing heightened\u0000requisites upon the security of bank assets and financial stability. This study\u0000harnesses advanced neural network techniques, notably the Backpropagation (BP)\u0000neural network, to pioneer a novel model for preempting credit risk in\u0000commercial banks. The discourse initially scrutinizes conventional financial\u0000risk preemptive models, such as ARMA, ARCH, and Logistic regression models,\u0000critically analyzing their real-world applications. Subsequently, the\u0000exposition elaborates on the construction process of the BP neural network\u0000model, encompassing network architecture design, activation function selection,\u0000parameter initialization, and objective function construction. Through\u0000comparative analysis, the superiority of neural network models in preempting\u0000credit risk in commercial banks is elucidated. The experimental segment selects\u0000specific bank data, validating the model's predictive accuracy and\u0000practicality. Research findings evince that this model efficaciously enhances\u0000the foresight and precision of credit risk management.","PeriodicalId":501128,"journal":{"name":"arXiv - QuantFin - Risk Management","volume":"68 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141147623","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0