Mutually Exclusive Projects, Project Sequencing, and Capital Rationing

The cash flow analysis for making capital decisions can become more complex because of the interaction between different projects. The finance manager will have to work with these complexities while evaluating and selecting projects

Independent Vs. Mutually Exclusive Projects

The projects being analyzed by a company may be completely independent of each other or mutually exclusive. When two projects are independent, it means that there cash flows are independent of each other, and so is their profitability. A company may decide to undertake both the projects if they are both profitable.

When two projects are mutually exclusive, it means that the firm wants to undertake only one of these two projects, not both. For example, while deciding between two delivery trucks that have different costs and output, the firm will have to choose one truck between the two.

Project Sequencing

Sometimes projects can only be executed in a sequence. For example, if three projects A, B and C can be executed in a sequence, then project B can be executed only after project A has been executed. Once the project A has been executed, it creates the opportunity for project B to be executed. The firm will also see if project A has been profitable before going ahead with project B.

Unlimited Funds Vs. Capital Rationing

The company may have unlimited access to capital in which case it can execute all profitable projects simultaneously. However, in reality firms will have constraints on how much funds they have to invest. If there are more capital projects then the funds available, the firm will have to exercise capital rationing and prioritize the projects and first execute those that have the highest impact on shareholder’s value.

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Capital Budgeting

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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.