Probabilistic DCF Analysis and Capital Budgeting and Investment—a Survey

Carmichael, David G.; Balatbat, Maria C. A.

doi:10.1080/00137910701864809

Cited by 36 publications

(25 citation statements)

References 54 publications

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“…This probabilistic form permits a trade-off between the magnitude of an outcome and the probability of the outcome (Carmichael and Balatbat 2008;Carmichael 2011). Tung (1992), Wagle (1967) and others argue that the probabilistic approach fully utilizes the available information about an uncertain project and facilitates its correct transformation into an evaluation of its true economic merit.…”

Section: Irrmentioning

confidence: 98%

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The financial additionality and viability of CDM projects allowing for uncertainty

Carmichael

Lea

Balatbat

2015

Environ Dev Sustain

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Financial additionality and viability for Clean Development Mechanism (CDM) projects is commonly demonstrated through deterministic internal rate of return (IRR) benchmark analysis, supplemented with a sensitivity analysis. This method is vulnerable to assumptions on cash flows (including that from carbon credits) and is unable to differentiate grades of separation from the benchmark. This paper examines the financial additionality test and viability in the presence of cash flow uncertainty, where IRR becomes a random variable. A case example project involving wind power is exampled. It is seen that the boundaries between acceptance and rejection as a CDM project based on financial additionality and viability tests become blurred, leading to possible alternative conclusions. Comment is given on false positives and false negatives, in terms of acceptance and rejection of projects.

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Section: Irrmentioning

confidence: 98%

“…This yields a distribution for the present worth (PW), which in turn yields the distribution for IRR (Hillier 1963;Carmichael and Balatbat 2008). Following Hillier (1963), the probability that IRR is less than an assumed rate r is the same as the probability that PW is negative,…”

Section: Irrmentioning

confidence: 98%

The financial additionality and viability of CDM projects allowing for uncertainty

Carmichael

Lea

Balatbat

2015

Environ Dev Sustain

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“…This reduces the NPV of projects with higher risks and thus makes them less desirable. Therefore, the compounding effect of the risk premium in the traditional approach penalizes investments with longer life and thus leads to favoring investment projects with short life spans (Carmichael & Balatbat, 2008). Moreover, when there are multiple risk factors with different degrees of uncertainty involved in affecting the NPV, it is not obvious which risk factors are reflected in the assigned cost of capital.…”

Section: Case Study With Monte Carlo Simulationmentioning

confidence: 99%

A Probabilistic Capital Budgeting Model for New Product Development under Stage-Gate Process

Sharifzadeh

Sharif²

2015

AFR

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Stage-gate model for new product development (NPD) and for any research and development (R&D) project consists of a series of stages and gates; each stage is a set of research activities and gates are milestones at which decisions are made based on predetermined criteria. In this paper we developed a capital budgeting model for a typical 5-stage, 5-gate process to be used for appraising commercial viability of the NPD at Stage 2 which will serve as one of the decision making criterion at Gate 3. Because in an NPD project, completion costs (capital investments), completion times, and future cash flows are uncertain, we developed the Pert-Beta probability distribution to encounter for the randomness of these variables. Furthermore, we suggested the model can be applied to real case NPD projects with the Monte Carlo Simulation approach. We then verified the workability of the model by applying it to a notional NPD project and demonstrated that all decision variables reach steady state in the Monte Carlo Simulation calculations.

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“…This probability permits determining the feasibility of an investment as defined by Carmichael and Balatbat (2008). Hillier's methodology is still regarded as pioneering till the present as Sarper et al (2012) recognize.…”

Section: The Literaturementioning

confidence: 99%

“…They study the case of cash flows described by multivariate normal distributions and are able to approximate the distribution of the IRR when variances of period costs and returns are small. A useful review of the literature on probabilistic cash flow analysis is carried out by Carmichael and Balatbat (2008) who find that the research directly related to the subject of the probabilistic IRR is scant. However, more recently Sarper et al (2010) report closed-form probability distributions for the IRR for one-period and two-period capital budgets for which the cash flows are characterized by either uniform or exponential distributions.…”

Section: The Literaturementioning

confidence: 99%

A Probabilistic Internal Rate of Return: Theory and Illustration

Azar¹,

Noueihed²

2014

IJBM

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The purpose of this paper is to provide a theoretical background on the internal rate of return (IRR), on the probabilistic IRR, and to present an illustration based upon both a Taylor series expansion and a Monte Carlo simulation. It is shown that Monte Carlo simulation results in a more precise outcome as compared to the theoretical expectations from a Taylor series expansion. This precision is more than twice in terms of the standard deviations of the IRR, and around six times more in terms of the standard errors of the IRR. Second, the distributions of the internal rate of return follow approximately a normal distribution, and this allows a sound basis for project appraisal and risk management. Third, the grand means of the internal rates of returns for all four cases considered are statistically insignificantly different from each other, as expected, and they are statistically insignificantly different from the average internal rate of return, obtained by discounting the mean amounts of the cash flows. Fifth, the standard deviations and the standard errors of the IRR are directly proportional to the assumed standard deviations of the cash flows.

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Probabilistic DCF Analysis and Capital Budgeting and Investment—a Survey

Cited by 36 publications

References 54 publications

The financial additionality and viability of CDM projects allowing for uncertainty

The financial additionality and viability of CDM projects allowing for uncertainty

A Probabilistic Capital Budgeting Model for New Product Development under Stage-Gate Process

A Probabilistic Internal Rate of Return: Theory and Illustration

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