Revenue Recognition - Barter Transactions

A barter transaction occurs when two firms exchange goods or services with each other without and cash payments. One service is provided and another service is received. For example, buying and selling advertising space of equal value on their respective websites.

IFRS and GAAP provide the following treatment for these transactions.

US GAAP: Recognize revenue at fair value. Face value is determined using past/historical experience in selling such goods or services. Alternatively, recognise revenue based on the carrying value of assets provided in exchange.

IFRS: recognize revenue based on the fair value of similar nonbarter transactions.

Gross and Net Reporting of Revenue

The revenue can be reported as gross or net revenue.

Under gross revenue reporting, the sales and cost of goods sold are shown separately. Under net reporting, the company reports only net revenue which is calculated by subtracting cost of goods sold from sales. Net revenue reporting applies when the company has only earned a commission or fee on the project.

A company uses gross revenue method, when it is the primary party in a contract. The firm bears the risks and benefits associated with revenue-generated activities by: (1) acting as a principal in the transaction; (2) establishing prices; (3) being responsible for fulfilment of the order; (4) taking the risk of loss for collection, delivery and returns; and (5) marketing the products, among other things.

Implications for Financial Analysis

We learned that under different circumstances a company can recognize revenues before delivery, at the time of delivery or after delivery. While performing financial analysis an analyst must pay attention to the revenue recognition methods used. He should understand whether the company is aggressive or conservative in recognizing revenue and how much it relies on estimates for recognizing revenues.

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Data Science in Finance: 9-Book Bundle

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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

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