2016
DOI: 10.3390/f7070130
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Quantitative Analysis of Uncertainty in Financial Risk Assessment of Road Transportation of Wood in Uruguay

Abstract: Abstract:The uncertainty in road transportation of wood is inherent to its operational costs, to the amount of transported wood, to the traveled distance, to its revenue, and more. Although it is not possible to measure this uncertainty fully, it can be quantified by the investment risk, which is the probability and degree of financial loss. The objective of this study is to quantify the financial risk of the investment in wood transportation through Monte Carlo simulation, which uses realistic situations to e… Show more

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Cited by 14 publications
(11 citation statements)
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“…The deterministic variables were bole biomass (dry ton/ha), deployment costs (USD/ha), cultural treatment costs for 1st year (USD/ha), cultural treatment costs for 2nd year (USD/ha), administration costs (USD/ha), and land remuneration (USD/ha). Due to lack of information for these variables, we assumed the distribution followed a symmetrical triangular distribution [45][46][47][48]. The probability distribution is the building block for risk models that calculates the probability distribution of output random variables based on the probability distribution of input random variables [49].…”
Section: Risk Analysismentioning
confidence: 99%
“…The deterministic variables were bole biomass (dry ton/ha), deployment costs (USD/ha), cultural treatment costs for 1st year (USD/ha), cultural treatment costs for 2nd year (USD/ha), administration costs (USD/ha), and land remuneration (USD/ha). Due to lack of information for these variables, we assumed the distribution followed a symmetrical triangular distribution [45][46][47][48]. The probability distribution is the building block for risk models that calculates the probability distribution of output random variables based on the probability distribution of input random variables [49].…”
Section: Risk Analysismentioning
confidence: 99%
“…The software uses a stochastic Monte Carlo simulation procedure for conducting sensitivity and risk analyses where input variables vary simultaneously to produce the output variables. We simulated the developed model 1000 times and used a triangular probability distribution function for input variables (Simoes et al, 2016).…”
Section: Financial Risk and Sensitivity Analysesmentioning
confidence: 99%
“…The simulations were done using the @RISK 7.5 software (Palisade, 2017) and the input variables followed a symmetrical triangular distribution, with central peak (mode) and endpoints (minimum and maximum). The triangular distribution is easy to understand and commonly used in uncertainty analysis when there is no credible information about the probability distribution of the weighted variables in the stochastic model (Simões et al, 2016).…”
Section: Capital Budgeting Calculationmentioning
confidence: 99%