Value-at-Risk Model Analysis of Taiwanese High-Tech Facility Construction

Chen, Po‐Han; Peng, Tsu-Te

doi:10.1061/(asce)me.1943-5479.0000585

Cited by 4 publications

(2 citation statements)

References 10 publications

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“…A frequently employed metric for assessing risk in finance is the Value at Risk (VaR) (Caron, 2013;Caron et al 2007). In financial terms, it is traditional to choose a P95 percentile as risk appetite (Chen and Peng, 2018;Joukar and Nahmens, 2016;Gatti et al 2007;Kuester et al 2006;Giot and Laurent, 2003). However in project management, the P80 percentile is sometimes chosen as the most appropriate percentile to measure risk appetite (Kwon and Kang, 2019;Traynor and Mahmoodian, 2019;Lorance and Wendling, 2001).…”

Section: Tot Dur I Tot Costmentioning

confidence: 99%

Beyond probability-impact matrices in project risk management: A quantitative methodology for risk prioritisation

Acebes,

González-Varona,

López-Paredes

et al. 2024

Humanit Soc Sci Commun

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The project managers who deal with risk management are often faced with the difficult task of determining the relative importance of the various sources of risk that affect the project. This prioritisation is crucial to direct management efforts to ensure higher project profitability. Risk matrices are widely recognised tools by academics and practitioners in various sectors to assess and rank risks according to their likelihood of occurrence and impact on project objectives. However, the existing literature highlights several limitations to use the risk matrix. In response to the weaknesses of its use, this paper proposes a novel approach for prioritising project risks. Monte Carlo Simulation (MCS) is used to perform a quantitative prioritisation of risks with the simulation software MCSimulRisk. Together with the definition of project activities, the simulation includes the identified risks by modelling their probability and impact on cost and duration. With this novel methodology, a quantitative assessment of the impact of each risk is provided, as measured by the effect that it would have on project duration and its total cost. This allows the differentiation of critical risks according to their impact on project duration, which may differ if cost is taken as a priority objective. This proposal is interesting for project managers because they will, on the one hand, know the absolute impact of each risk on their project duration and cost objectives and, on the other hand, be able to discriminate the impacts of each risk independently on the duration objective and the cost objective.

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Section: Tot Dur I Tot Costmentioning

confidence: 99%

Beyond probability-impact matrices in project risk management: A quantitative methodology for risk prioritisation

Acebes,

González-Varona,

López-Paredes

et al. 2024

Humanit Soc Sci Commun

View full text Add to dashboard Cite

show abstract

“…Subsequently, the Water Criteria are considered undetermined parameters and thus, are given in the form of probability distributions as shown in Table IV. In this way, uncertain parameters have been selected to conduct a stochastic analysis using a Monte 864 ECAM 26,5 Carlo simulation as in previous studies (Berk and Podhraski, 2018;Buyukyoran and Gundes, 2017;Chen and Peng, 2018;Dong et al, 2011;Feng et al, 2017;Liu et al, 2017;Kumar et al, 2018).…”

Section: Project's Overviewmentioning

confidence: 99%

Investment valuation model for sustainable infrastructure systems

González-Ruiz

Arboleda

Botero

et al. 2019

ECAM

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Purpose The purpose of this paper is to develop an investment valuation model using the mezzanine debt mechanism based on blue bonds that explicitly allude to public–private partnerships (P3s) and project finance (PF). Additionally, this study proposes the financial captured value (FCV) theory for measuring how much financial value lenders may capture by becoming sponsors through financing of sustainable infrastructure systems (SIS). Design/methodology/approach The investment valuation model was validated through the Aguas Claras wastewater treatment plant as a case study. Findings The empirical results show that lenders may capture financial value by converting outstanding debt into equity shares throughout the operation and maintenance stage. Furthermore, case study results provide new insights into the implications of the debt–equity conversion ratio on the relationship between the sponsors’ internal rate of return and the FCV. Research limitations/implications The most significant limitation is the lack of primary and secondary information on blue bonds. Thus, robust statistical analyses to contrast results were not possible. Practical implications Researchers and practising professionals can improve their understanding of how mezzanine debt, P3s and PF into an investment valuation model allows financing SIS using a non-conventional financial mechanism. The recommendations will benefit both the academia as well infrastructure industry in bridging the gap between design theory and practice. Originality/value Sustainability components have not been addressed explicitly or combined in the financing’s structuring. Therefore, the investment valuation model could be considered a novel methodology for decision making related to financing and investment of SIS.

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Project Risk Costs: Estimation Overruns Caused When Using Only Expected Value for Contingency Calculations

López-Manzanares

2022

J. Manage. Eng.

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Value-at-Risk Model Analysis of Taiwanese High-Tech Facility Construction

Cited by 4 publications

References 10 publications

Beyond probability-impact matrices in project risk management: A quantitative methodology for risk prioritisation

Beyond probability-impact matrices in project risk management: A quantitative methodology for risk prioritisation

Investment valuation model for sustainable infrastructure systems

Project Risk Costs: Estimation Overruns Caused When Using Only Expected Value for Contingency Calculations

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