Evaluation of a mining project using Discounted Cash Flow analysis, Decision Tree analysis, Monte Carlo Simulation and Real Options using an example

Alan Silko must decide whether to invest in seven statistical-process-control (SPC) stations in order to increase his chances of becoming a “select supplier” for a large computer company. The student must do a discounted-cash-flow/decision-tree analysis of the option. The student is also given the opportunity to construct x-bar and range charts and to do an SPC analysis.

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Economic and Risk Analysis to Deep Water Operations

Journal of Energy Research and Reviews ◽

10.9734/jenrr/2020/v5i230143 ◽

2020 ◽

pp. 11-16

Author(s):

C. E. Ubani ◽

A. O. Oluobaju

Keyword(s):

Sensitivity Analysis ◽

Monte Carlo Simulation ◽

Monte Carlo ◽

Cash Flow ◽

Net Present Value ◽

Oil And Gas ◽

Risk Model ◽

Flow Analysis ◽

Discounted Cash Flow ◽

Exploration And Production

The exploration and production (E&P) operations of oil and gas project in deep waters, is associated with risks. These risks affects return on investment if they are not identified and analyzed to reduce their impact on the project. This study seek to apply Discounted Cash Flow (DCF) analysis, Monte Carlo Simulation and Sensitivity analysis, to an existing field in the Niger Delta region in Nigeria, to ascertain the viability of deepwater project when it is affected by government fiscal terms and technical terms. Economic and risk models were developed to determine profitability indicators and risk associated with the project. Risk simulator software was used to carry out Monte Carlo simulation and the sensitivity analysis. Results obtained showed that the project was economically viable with a Net Present Value (NPV) of $1,621.8 million and Internal Rate of Return (IRR) of 34%. The Monte Carlo Simulation and the sensitivity analysis showed that the Contractor’s NPV and percentage take were most sensitive to tax (under the fiscal terms) with an range of $639.27 million for a variation of by +/- 10% and crude price (under the technical term). The model developed can easily be applied in investment selections and decision makers should make decision based on the outcome of both economic model (cash flow analysis) and the risk model (Monte Carlo Simulation).

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Integrating the Subsurface and the Commercial: A New Look at Monte Carlo and Decision Tree Analysis

10.2118/162883-ms ◽

2012 ◽

Cited By ~ 6

Author(s):

Jan Schulze ◽

Jeremy Walker ◽

Kent Burkholder

Keyword(s):

Monte Carlo ◽

Decision Tree ◽

Decision Tree Analysis ◽

Tree Analysis ◽

New Look

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A Comparison of Monte Carlo Simulation and Discounted Cash Flow Investment Appraisal Techniques Using an Office Building in Akure, Nigeria

Nigerian Journal of Environmental Sciences and Technology - March 2018 ◽

10.36263/nijest.2017.02.0043 ◽

2017 ◽

Vol 1 (2) ◽

pp. 299-308

Author(s):

S. P. Akinbogun ◽

O. P. Binuyo ◽

O. T. Akinbogun

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Cash Flow ◽

Investment Decision ◽

Single Point ◽

Investment Analysis ◽

Point Estimate ◽

Discounted Cash Flow ◽

Expected Return ◽

Level Of Risk

Every rational investor aimed to secure an optimum return from an investment at certain level of risk. However, the factors that affect the realization of the expected return are not known with certainty. Therefore, the reliability of a single point estimate for investment decision is debatable particularly when the likelihood of realizing the expected return is crucial to the investor. This study aimed at examining a better method of analysing the uncertainty in property investment rather than the use of the single point estimate formula. We collected a set of historic data from a multi-tenanted office complex in Akure to carry out the investment analysis using Monte Carlo simulation and Discounted Cash Flow Technique. The results from the study were compared and revealed that the single point estimate accounted for a huge level of risk as probability of realizing the expected return is unknown. The Monte Carlo simulation offers a more robust opportunity for a measured investment decisions by providing a probability of realizing different level of the expected returns. The study concludes that it is difficult to make a smart investment decision on a single point estimate. It therefore recommends the use of Monte Carlo simulation for property investment analysis for a more realistic return.

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Optimizing Investment Decisions Using DCF, Decision Tree Analysis, and Real Options Analysis

Handbook of Research on Holistic Optimization Techniques in the Hospitality, Tourism, and Travel Industry - Advances in Hospitality, Tourism, and the Services Industry ◽

10.4018/978-1-5225-1054-3.ch004 ◽

2017 ◽

pp. 98-114

Author(s):

Ramya Rajajagadeesan Aroul

Keyword(s):

Decision Tree ◽

Real Options ◽

Large Scale ◽

Investment Decisions ◽

Call Option ◽

Decision Tree Analysis ◽

Discounted Cash Flow ◽

Tree Analysis ◽

Real Options Analysis ◽

Distinct Approach

Large scale infrastructure expansions in hotels are exposed to uncertainty. Since the costs involved in these expansion projects are high and often irreversible, hotels would benefit from analyses that incorporate uncertainty along with traditional valuation techniques like the discounted cash flow (DCF) method. Decision tree analysis (DTA) and real options analysis (ROA) have been in use for the past couple of decades to handle uncertainties and optimize investment decisions. DTA provides a distinct approach to strategic investments that quantitatively takes into account the uncertainties involved in the investments. Under uncertainty, the decision about whether to expand is analogous to the decision about whether to exercise an American call option. By using ROA to the hotel expansion scenario, managers can incorporate and quantify, flexibility and timing in their analysis. The objective of this chapter is to detail the DCF, DTA and ROA methodologies and their applications specific to hotel expansion investments.

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Using Monte Carlo Simulation to Improve Ceramic R&D Investment Decisions

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.105-106.798 ◽

2010 ◽

Vol 105-106 ◽

pp. 798-801

Author(s):

Bao Cheng He ◽

Hong Tao Jiang ◽

Shu Zhi Yao ◽

Bao Yuan He

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Real Options ◽

Cash Flow ◽

Investment Decisions ◽

Discounted Cash Flow ◽

Valuation Model ◽

Managerial Flexibility ◽

D Investment

The success of ceramic companies is highly dependent on research and development (R&D). Thus, a pivotal aim of management is to allocate resources to the best scientific and financial R&D projects. But the valuation of ceramic R&D is a difficult task for managers. The conventional discounted cash flow (DCF) methods fail to consider the value of managerial flexibility provided by R&D projects. Real options Analysis (ROA) offers a superior way of capturing the value of flexibility. It enables decision-maker to value projects more accurately by incorporating managerial flexibilities into the valuation model. However, ROA can’t effectively deal with the volatility of parameters in itself under high uncertain circumstance. In view of the limitation of ROA, this paper uses Monte Carlo simulation to solve the parameters volatility problems. In the end, the case study proves that Monte Carlo simulation can improve R&D investment decisions, especially for highly unpredictable ceramic R&D projects.

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Synergies between an Observed Port and a Logistic Company: Application of the Discounted Cash–Flow Model and the Monte Carlo Simulation

Logistics & sustainable transport ◽

10.1515/jlst-2017-0001 ◽

2017 ◽

Vol 8 (1) ◽

pp. 1-18 ◽

Cited By ~ 2

Author(s):

Dejan Dragan ◽

Bojan Rosi ◽

Toni Avžner

Keyword(s):

Monte Carlo Simulation ◽

Monte Carlo ◽

Cash Flow ◽

Flow Model ◽

Strategic Partnership ◽

Discounted Cash Flow ◽

Strategic Cooperation ◽

Simulation Based ◽

Main Motive ◽

Dcf Model

AbstractThe paper addresses an analysis of potential synergies in collaboration between an observed Port in the Mediterranean Sea and Central-European logistic railway-services based company. Both companies have established a strategic partnership. The main motive was cooperation in rail transport, with a particular emphasis on potential synergies that would a rail traffic have brought to a port’s business. For the purpose of synergies valuation under uncertain conditions, a Monte Carlo simulation-based framework with integrated discounted cash flow (DCF) model is applied. The possible values of future synergies are calculated via the DCF model by simultaneously changing values of different uncertain financial parameters at each repetition of a Monte Carlo scenario-playing mechanism. In this process, predicted forecasts of future synergetic throughputs are also used for various types of observed cargo. As it turned out, the generated synergies’ values follow the approximate normal distribution. Based on statistical inference and analysis of probability intervals it was discovered that there might indeed exist certain important synergies in the collaboration between both companies. This fact has convinced us into a belief in the correctness of companies′ decision to enter into such kind of strategic cooperation.

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