Abstract This article focuses on the effect of chance variation on revenue and cost estimations for break-even analysis. Break-even analysis consists essentially of examining the relationship between revenues and costs. The regression models use historical data to predict future revenue-volume and cost-volume relationships. The model, suggestively, is good if the environment does not change. The break-even analysis based on estimated revenue and cost functions, therefore, is subject to chance variation. The purposes of this article is twofold: first, to demonstrate the determination of the chance variation in estimated revenue and cost functions, and second, to illustrate how the chance variation associated with revenue and cost estimations affect the results of a break-even analysis. According to the author, regression analysis can be a helpful tool for predictions of future revenue and cost if fundamental assumptions in the model are satisfied. The most important assumption of regression analysis is that the historical relationship between the dependent variable and independent variable will persist. Therefore, one of the problems of using regression analysis is that the future relationships may not coincide with the relationships indicated by mathematical equations derived from historical data.

Abstract Accountants frequently prepare depreciation lapse schedules showing depreciation expense by year for each depreciable asset. Such schedules are used in providing financial data for management planning functions, such as tax planning, cash flow budgets and forecasting financial statements. The traditional method becomes impractical, inconvenient and expensive when a schedule contains a large number of items and years. The purpose of this article is to introduce a practical application of the matrix method for the preparation of depreciation lapse schedules. The depreciation rate is determined by the depreciation policy. The matrix approach also provides an efficient framework for computerizing the calculation process. A depreciation lapse schedule, when prepared on the company's year basis, provides information for tax planning, budgeting and forecasting as well as for financial accounting and reporting. The matrix method when computerized provides a convenient and efficient framework for performing the necessary computations.

Abstract The article presents an accounting model of cost-volume-profit (C-V-P) analysis. The use of stochastic analysis in a C-V-P analysis model is a great step forward in providing more useful information for profit planning. This model has been depicted as a limit analysis, since the assumptions of the independent model parameters and the normalcy of the resulting profit function are not true in all cases. Instead of using single estimates of model parameters in the C-V-P analysis model, sampling C-V-P analysis treats the model parameters as random variables. The objective of model sampling is to calculate one profit value from each set of the random model parameters. Then, by repeating the sampling process a sufficient number of times, certain characteristics of the profit distribution can be derived. The purpose of model sampling is to determine the sample profit points in the profit distribution rather than to identify the distributional form. However, the C-V-P model sampling is not restricted to the problem with independent and normal distribution model parameters only. An example in this article demonstrates the application of model sampling to a C-V-P analysis problem with dependent and non-normal distribution model parameters.