Return On Average Assets (ROA - Historical) Formula in Excel

Return On Average Assets (ROA - Historical) is a powerful Excel formula available with MarketXLS that helps you understand how efficiently a company uses its assets over time. By comparing a company's net income to its average assets, ROA provides valuable insights into operational performance and resource management.

Understanding Return On Average Assets (ROA - Historical)

  • Purpose and Use Cases
    The Return On Average Assets (ROA - Historical) formula gives a clear measurement of how well a company utilizes its assets to generate profits. This makes it useful when comparing peers in the same industry.

  • Key Benefits

    • Helps determine management efficiency.
    • Provides a basis for industry comparisons.
    • Complements other financial metrics like Return on Equity (ROE).
  • When to Use
    Use this function when you want to conduct historical trend analysis, evaluate investment opportunities, or benchmark against industry peers.

Syntax and Parameters

Below is the standard syntax structure for using this function in Excel with MarketXLS:

=hf_Return_on_Average_Assets(Symbol, Year, [Quarter], [TTM])
Parameter Description Required Example
Symbol The stock or asset symbol. Can include indices (^SPX), options (@MSFT 110122C00020000), or crypto (BTCUSD:DEFAULT). Yes "MSFT", "^SPX", "@MSFT 110122C00020000", "BTCUSD:DEFAULT"
Year Specifies the target year. Can also handle special keywords like "lq", "ly", etc. Yes 2022, "lq", "ly-1", "lt-1"
Quarter The calendar quarter (1 to 4). If omitted, defaults to 1 (or 2 internally to align data). No 2
TTM Used to specify trailing twelve months. If set, calculates the TTM value for the given period. No "TTM"

Return Value
The function returns a numeric value representing the Return On Average Assets for the specified symbol and period. If an invalid symbol or parameter is detected, it returns "NA".

?? Note: This feature requires a Historical Fundamentals data subscription in MarketXLS.

Examples and Usage

Here are some practical ways to use the Return On Average Assets (ROA - Historical) formula:

  1. Basic Yearly Lookup

    =hf_Return_on_Average_Assets("MSFT", 2022)

    Retrieves the ROA for Microsoft in 2022.

  2. Quarter-Specific Lookup

    =hf_Return_on_Average_Assets("MSFT", 2022, 2)

    Returns Microsoft’s ROA in the second calendar quarter of 2022.

  3. Trailing Twelve Months

    =hf_Return_on_Average_Assets("MSFT", 2022, 3, "TTM")

    Calculates Microsoft’s ROA for the trailing twelve months in the third calendar quarter of 2022.

  4. Last Quarter or Year

    =hf_Return_on_Average_Assets("MSFT", "lq")
    =hf_Return_on_Average_Assets("MSFT", "ly")

    Returns Microsoft’s ROA for the last quarter or the last year, respectively.

  5. Formatting Date Inputs

    • Cell References:
      =hf_Return_on_Average_Assets(A1, 2022)
    • Direct Dates:
      =hf_Return_on_Average_Assets("MSFT", "2024-03-15")
    • Excel Date Functions:
      =hf_Return_on_Average_Assets("MSFT", TEXT(A1,"yyyy-mm-dd"))

? Pro Tip: Combine this formula with other MarketXLS historical metrics such as Revenue (Historical) and Gross Profit (Historical) to get a comprehensive view of a company’s performance.

Common Questions

  1. What if the symbol is invalid or not supported?
    The function will return "NA" to indicate an unavailable value.

  2. Does this formula work with indices, options, and crypto symbols?
    Yes. MarketXLS supports notation like "^SPX" for indices, "@MSFT 110122C00020000" for options, and "BTCUSD:DEFAULT" for crypto.

  3. Why am I getting an NA error even though my symbol is correct?
    Ensure you’re subscribed to Historical Fundamentals data. Also check spelling and argument formats.

  4. How often is the data updated?
    MarketXLS updates its fundamental data regularly. The function references the most recent data available in the MarketXLS backend.

  5. How can I improve performance with multiple ROA calculations?
    Use Excel’s built-in calculation settings to manage large datasets efficiently. You can also consider caching or referencing results from fewer cells if needed.