Impacts of LIFO and FIFO Inventory Methods on Selected Financial Ratios

FINANCIAL STATEMENT/RATIOFIFOLIFO
Net Income and Profit MarginsUsually higher in a rising price environment.Usually lower in a rising price environment.
Pre-tax Cash FlowSame.Same.
After-tax Cash FlowUsually lower in a rising price environment because a company is reporting higher net income due to lower COGS.Usually higher in a rising price environment because a company is reporting lower net income due to higher COGS.
Current Ratio = Current Assets/Current LiabilitiesUsually higher in a rising price environment because reported inventories are more valuable and COGS is lower.Usually lower in a rising price environment because reported inventories are based on lower cost purchases and higher COGS.
Inventory Turnover = COGS/Avg. InventoryUsually lower in a rising price environment because the average cost of inventory will be higher.Usually higher in a rising price environment because the average cost of inventory will be lower.
Debt-to-Equity Ratio = Total Interest Bearing Debt/Total Shareholders' EquityUsually lower in a rising price environment.Usually higher in a rising price environment.
Return on Assets =Net Income/ Avg. Total Assets Return on Equity = Net Income / Avg. Total EquityUsually higher in a rising price environment because net income is higher.Usually lower in a rising price environment because net income is lower.

Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

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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.