A Stochastic Cost Volume Profit Analysis

Kim, Chaiho

doi:10.1111/j.1540-5915.1973.tb00559.x

Cited by 18 publications

(5 citation statements)

References 6 publications

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“…Kim [28] presents two modified CVP models intended to help financial analysts avoid the problem of the difference of ex post and ex ante costs and prices in sensitivity analysis; some unexpected statistical and financial properties are displayed in this study.…”

Section: Literature Reviewmentioning

confidence: 99%

A Generalized Stochastic Cost–Volume–Profit Model

Liang

Guiffrida

Liu³

et al. 2021

Systems

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Cost–volume–profit (CVP) analysis is a widely used decision tool across many business disciplines. The current literature on stochastic applications of the CVP model is limited in that the model is studied under the restrictive forms of the Gaussian and Lognormal distributions. In this paper we introduce the Mellin Transform as a methodology to generalize stochastic modeling of the CVP problem. We demonstrate the versatility of using the Mellin transform to model the CVP problem, and present a generalization of the CVP model when the contribution margin and sales volume are both defined by continuous random distributions.

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Section: Literature Reviewmentioning

confidence: 99%

A Generalized Stochastic Cost–Volume–Profit Model

Liang

Guiffrida

Liu³

et al. 2021

Systems

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“…Therefore, understanding the amount of risk the firm is willing to accept is crucial to selecting the best alternative. Studies introducing risk or uncertainty into C-V-P analysis have assumed normal distributions of profits Jaedicke [3]; Jarrett [12]; Kim [13]; Johnson [14]; Hilliard [2]. These studies made assumptions that demand and output were equal or unequal.…”

Section: Cost-volume-profit Analysis Under Uncertaintymentioning

confidence: 99%

Integration of Cost Volume Profit Analysis under Uncertainty in Profit Planning: A Current Application

Beykaei¹,

Abekah²,

Rahim

2020

SIAM

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Use of cost-volume-profit analysis for actual planning is often limited by an inability to properly incorporate uncertainty in the analysis when assumptions about known price and costs do not hold. We use currently available analysis software (MAPLE) in this study to demonstrate that uncertainty can be incorporated in Cost-Volume-Profit analysis and planning in practice. We show in our examples that expected selling price and variable cost changes have greater influence on expected breakeven sales levels than the impact of the standard deviations of selling price and variable cost. In particular, decreases in the expected selling price are shown to lead to significantly sharp declines in the expected breakeven quantity. By contrast, when the standard deviations of selling price or variable costs increase, only proportionate increases in the breakeven quantity are observed.

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“…Several attempts have been made in order to incorporate a stochastic be-havior of profits into the analysis (see e.g. [5][6][7][8][9][10]), in which fluctuations are assumed to be normally distributed.…”

mentioning

confidence: 99%

“…Clearly, the question arises of how to estimate in a more realistic fashion profit fluctuations, and therefore attempting to improve the accuracy of earnings predictions, the latter being closely related to the issue of profitability or break-even point [4]. Several (a) E-mail: eduardo.roman@mib.infn.it attempts have been made in order to incorporate a stochastic behavior of profits into the analysis (see, e.g., [5][6][7][8][9][10]), in which fluctuations are assumed to be normally distributed.…”

mentioning

confidence: 99%

“…It is remarkable that η = 0.5, the latter would indicate a standard behavior of fluctuations. The fact that η > 1/2 tells us that fluctuations are stronger than one would expect if ∆π were normally distributed (see, e.g., [6]). To find out the actual shape of the probability distribution function, G( ), for ≡ ∆π/ |∆π| (in the case η = 0.6), we have plotted it in fig.…”

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confidence: 99%

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Fluctuations of company yearly profits vs. scaled revenue: Fat-tail distribution of Lévy type

et al. 2008

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Abstract. -We analyze annual revenues and earnings data for the 500 largest-revenue U.S. companies during the period 1954-2007. We find that mean year profits are proportional to mean year revenues, exception made for few anomalous years, from which we postulate a linear relation between company expected mean profit and revenue. Mean annual revenues are used to scale both company profits and revenues. Annual profit fluctuations are obtained as difference between actual annual profit and its expected mean value, scaled by a power of the revenue to get a stationary behavior as a function of revenue. We find that profit fluctuations are broadly distributed having approximate power-law tails with a Lévy-type exponent α ≃ 1.7, from which we derive the associated break-even probability distribution. The predictions are compared with empirical data.

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A Stochastic Cost Volume Profit Analysis

Cited by 18 publications

References 6 publications

A Generalized Stochastic Cost–Volume–Profit Model

A Generalized Stochastic Cost–Volume–Profit Model

Integration of Cost Volume Profit Analysis under Uncertainty in Profit Planning: A Current Application

Fluctuations of company yearly profits vs. scaled revenue: Fat-tail distribution of Lévy type

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