Decision Making Under Uncertainty in Pipeline Projects Using Monte Carlo Simulation

Author(s):  
Claudio de Brito Garcia ◽  
Leandro Bastos Machado

Uncertainty about a situation can often indicate risk, which is the possibility of loss, damage, or any other undesirable event. Most people and organization desire low or minimized risk, which would translate to stand to a scenario of high probability of success, profit, or some form of gain. This work shows the importance of risk analysis when it comes to compare two capital investment projects in the natural gas transmission business. A transmission company needs to choose between two alternatives for capacity expansion of a pipeline, with a maximum value for the transmission tariff previously agreed to the shipper. At first, the transmission tariff is calculated by the conventional method that comprises iterative calculation from an arbitrary value, until the project Net Present Value (NPV) reaches zero. Once calculated, the lower of the transmission tariffs associated to the two expansion projects indicates the best choice. That’s the way the majority of companies perform their economical analysis of the proposed problem. Monte Carlo Simulation risk analysis technique is a powerful tool to asses the risk associated to a capital investment project, which can be summarized as the probability of undesired results. The risk calculation is based on the uncertainties associated to the input data used to build the project free cash flow, and the simulation produces a frequency distribution, or histogram, for, the NPV of a project. As will be seen in the work, the investment with the largest expected NPV may not always be the best investment alternative.

Author(s):  
محمد الأمين ◽  
بن حامد عبد الغني ◽  
مراس محمد

Our research aims to try to present the modeling mechanisms in the field of simulation and quantitative methods. The research is a presentation of the role of quantitative methods in making investment project evaluation decisions, more than that and is the use of the Monte Carlo simulation model in evaluation and multi-period analysis of investment projects under conditions Risk and uncertainty. And highlighting the theoretical, scientific and practical importance of the Monte Carlo simulation method in particular, and the importance of using quantitative methods in helping to make decisions in general


Author(s):  
Liana Chechenova ◽  
Natalya Volykhina ◽  
Yuriy Egorov

Objective: When assessing the risks of an investment project, it is necessary to take into account the uniqueness of each project, which requires the search for completely new solutions, the application and combination of various tools and assessment methods for the effective implementation of the project. The objective is to develop and test an algorithm for express risk assessment of an investment project using an integral risk factor. In order to achieve this the following issues are considered: the development of the risk theory and the main stages of its development, the modern concept of risk and risk classification in the context of investment projects, modern methods for assessing the risks of investment projects and their problems. Next, the concept of an integral risk factor is introduced and an express assessment of risks of a local investment project is carried out using an integral risk factor. Methods: The classical methods of identifying and assessing project risks (the method of expert estimates, the Monte-Carlo simulation method), the comparative method, analysis, and synthesis are used in the study. Results: The basic characteristics of the concept of “risk” inherent in the modern understanding were formulated. A new concept of the integral risk factor and the method of its calculation were proposed. Alternative scenarios for the implementation of the investment project using the integral risk factor were developed. An algorithm for complex risk express assessment of an investment project on a multi-brand dealer auto center construction was developed by means of an integral risk factor and Monte-Carlo simulation method. Practical importance: The developed algorithm can be used by managers to identify and evaluate or carry out an express assessment of complex risks of investment projects in the process of operating real projects, as well as to provide background for developing new and more advanced methods of project risks assessment.


2015 ◽  
Vol 16 (5) ◽  
pp. 877-900 ◽  
Author(s):  
Wenqing Zhang ◽  
Prasad Padmanabhan ◽  
Chia-Hsing Huang

Uncertainty influences a decision maker's choices when making sequential capital investment decisions. With the possibility of extremely negative cash inflows, firms may need to curtail operations significantly. Traditional Net Present Value analysis does not allow for efficient management of these problems. In addition, firm managers may behave irrationally by accepting negative Net Present Value projects in the short term. This paper presents a Monte Carlo simulation based model to provide policy insights on how to incorporate extreme cash flows and manager irrationality scenarios into the capital budgeting process. This paper presents evidence that firms with irrational managers and experiencing extremely negative cash flows may, under certain conditions, reap long term rewards associated with the acceptance of negative Net Present Value projects in the short term. These benefits are largest if cost ratios (discount rates) are small, or investment horizons are high. We argue that acceptance of short term negative Net Present Value projects implies the purchase of a long term real option which can generate positive long term cash flows under certain conditions.


2007 ◽  
Vol 15 (2) ◽  
pp. 32-43
Author(s):  
Jiří Fotr ◽  
Lenka Švecová ◽  
Ivan Souček ◽  
Lubomír Pešák

2021 ◽  
Vol 43 ◽  
pp. e50965
Author(s):  
Flávio Fraga Vilela ◽  
João Victor Soares do Amaral ◽  
Gustavo dos Santos Leal ◽  
Gabriel Fernandes de Oliveira ◽  
José Arnaldo Barra Montevechi ◽  
...  

The cost of electricity in hospitals represents a significant portion in its context of operating expenses. Therefore, it is important to constantly think about ways to reduce this cost without losing the quality and reliability required for hospital care activity. It is well known, that reducing electricity consumption has a direct impact on the effective management of hospital cash flow, so it is imperative to rationalize this resource. In this context, the objective of this paper focuses on analyzing the economic feasibility of purchasing and using a diesel generator to find the peak hour demand and verifying financial uncertainty by applying a Monte Carlo simulation approach to risk analysis. The target hospital of this research is located in southeastern of Brazil and it is part of a foundation that covers educational and assistance activities, serving the local population and thousands of patients during the year. Finally, the economic risk analysis applied through the Monte Carlo simulation found that the acquisition of the aforementioned diesel generator has a very high probability of viability. Therefore, it is verified that the investment is viable and attractive from the hospital's economic and operational point of view, while the Net Present Value remains positive, with the expected value of R$ 868,358.84, considering the risk and uncertainty analysis having an attractive internal returning rate of 78.76% per year.


2020 ◽  
Vol 22 (1) ◽  
pp. 119-124
Author(s):  
Volodymyr Kharchenko ◽  
◽  
Hanna Kharchenko ◽  

Introduction. The article deals with the modeling features in the implementation of investment projects using the Monte Carlo method. The purpose of the article is to substantiate the feasibility of using economic and mathematical models to identify the risks of investment projects in agricultural production, taking into account the randomness of factors. Results. The expediency of using this method during the analysis of projects in agriculture is determined. This type of modeling is a universal method of research and evaluation of the effectiveness of open systems, the behavior of which depends on the influence of random factors. Particular attention is paid in such cases to decisions on the implementation of investment projects. The expediency of using this method in the analysis of projects in agriculture is determined. The main characteristics of the investment project are considered: investments involve significant financial costs; investment return can be obtained in a few years; there are elements of risk and uncertainty in forecasting the results of the investment project. The algorithm of the analysis of investment projects consisting of various stages is offered. The importance of investigating the risks of investment projects in agricultural production is substantiated. It is investigated that the basis of the Monte Carlo method is a random number generator, which consists of two stages: generation of a normalized random number (uniformly distributed from 0 to 1) and conversion of a random number into an arbitrary distribution law. The task of choosing an investment project for a pig farm is proposed. The calculations revealed that the amount of the expected NPV is UAH 63,158.80 with a standard deviation of UAH 43,777.90. The coefficient of variation was 0.69, so the risk of this project is generally lower than the average risk of the investment portfolio of the farm. Conclusions. The results of the analysis obtained using the method of Monte Carlo simulation are quite simple to interpret and reflect the change of factors over a significant interval, taking into account the probabilistic nature of economic factors. Thus, this method allows the implementation of the investment project to assess the impact of uncertainty on the final result of the project.


Author(s):  
Fernando Rodrigues de Amorim ◽  
Pedro Henrique Camargo de Abreu ◽  
Marco Tulio Ospina Patino ◽  
Leonardo Augusto Amaral Terra

Globalization is a phenomenon that is present in modern society and, with its expansion, it is essential that companies can meet the constant demands of the market, but for this, it is necessary to make the best decisions and deal with various adversities related to the economy, competition, management, among others. The success of investment projects is determined by a set of techniques that must be applied so as not to compromise the viability of the project. When this viability is surrounded by uncertainties, a useful alternative to knowing the risks is the use of the Monte Carlo method. The present work aims to address the risk factors in a company of the furniture sector, using the Monte Carlo simulation to analyze the viability of this project. The methodology adopted was developed from a case study, through an exploratory research. The results showed that the investment project is viable, estimating a return between the 4th and 5th year of the project, in addition, the balance after the 10 years of investment would be around R$ 4,128,211.63, a value that represents 161.25% of the initial investment.


2021 ◽  
Author(s):  
Agostino Bruzzone ◽  
Kirill Sinelshchikov ◽  
Federico Tarone ◽  
Federica Grosso

2015 ◽  
Vol 11 (4) ◽  
pp. 63-78 ◽  
Author(s):  
Seyed Mojtaba Hosseini Bamakan ◽  
Mohammad Dehghanimohammadabadi

In recent decades, information has become a critical asset to various organizations, hence identifying and preventing the loss of information are becoming competitive advantages for firms. Many international standards have been developed to help organizations to maintain their competitiveness by applying risk assessment and information security management system and keep risk level as low as possible. This study aims to propose a new quantitative risk analysis and assessment methodology which is based on AHP and Monte Carlo simulation. In this method, AHP is used to create favorable weights for Confidentiality, Integrity and Availability (CIA) as security characteristic of any information asset. To deal with the uncertain nature of vulnerabilities and threats, Monte Carlo simulation is utilized to handle the stochastic nature of risk assessment by taking into account multiple judges' opinions. The proposed methodology is suitable for organizations that require risk analysis to implement ISO/IEC 27001 standard.


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