Revenue Per Dollar Cash (Historical) Formula in Excel

Use the Revenue Per Dollar Cash (Historical) formula in Excel with MarketXLS to quickly analyze how much revenue a company generates per dollar of cash over a specified historical period. This function helps investors and analysts make informed decisions by examining the efficiency of a company’s cash usage.

Understanding Revenue Per Dollar Cash (Historical)

• Purpose: To retrieve the revenue-per-dollar-of-cash historical value for a given symbol (stock, index, option, or crypto).
• Use Cases:
  • Determining how effectively a company utilizes its cash reserves.
  • Comparing cash-related performance across multiple stocks or time periods.
  • Assessing the company’s financial efficiency and potential growth opportunities.
• Key Benefits:
  • Quick access to historical fundamentals without manual data gathering.
  • Streamlines fundamental analysis within Excel.
  • Provides insights for both short- and long-term decision-making.

Syntax and Parameters

=hf_Revenue_per_Dollar_Cash(Symbol, Year, [Quarter], [TTM])

?? Note: If an invalid symbol is entered or if your license is not valid, the function returns "NA".

Return Value

• Returns a numeric value representing the revenue-per-dollar-of-cash for the specified symbol and period.
• If the symbol or parameters are invalid, the function returns "NA".

Special Cases and Limitations

• When using advanced references (e.g., “lq-1,” “ly-2,” etc.), be aware of data availability.
• TTM data may not be available for all symbols or for certain time frames.
• Some international stocks and certain sectors may not have complete fundamental data in MarketXLS.

Performance Considerations

• This function retrieves data from MarketXLS cloud services. The performance primarily depends on the speed of your internet connection and the MarketXLS API.
• Repeated calls for the same symbol and period may be cached, improving performance in Excel.

Examples and Usage

Below are practical examples demonstrating how to use hf_Revenue_per_Dollar_Cash in common scenarios:

1. Basic Yearly Data:

   =hf_Revenue_per_Dollar_Cash("MSFT", 2022)

   Retrieves the revenue-per-dollar-of-cash for Microsoft in the year 2022.

2. Specifying Quarter:

   =hf_Revenue_per_Dollar_Cash("MSFT", 2022, 2)

   Retrieves the value for Microsoft in Q2 of 2022.

3. Using TTM (Trailing Twelve Months):

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

   Retrieves the trailing twelve months ending in Q3 of 2022.

4. Using Relative Period Markers:
   • Last Quarter (lq)

   =hf_Revenue_per_Dollar_Cash("MSFT", "lq")

   • Last Quarter minus 1 (lq-1)

   =hf_Revenue_per_Dollar_Cash("MSFT", "lq-1")

   • Last Year (ly)

   =hf_Revenue_per_Dollar_Cash("MSFT", "ly")

   • Last 12 Months (lt)

   =hf_Revenue_per_Dollar_Cash("MSFT", "lt")

? Pro Tip: You can reference cells or construct date/period strings dynamically. For example:

1. =hf_Revenue_per_Dollar_Cash(A1, B1)
2. =hf_Revenue_per_Dollar_Cash("MSFT", TEXT(C1,"yyyy"))

Common Questions

1. Why do I get “NA” as a result?

   • This usually indicates an invalid symbol, year, or license permissions. Double-check your inputs and ensure your MarketXLS subscription is active.

2. How do I apply this formula to multiple years?

   • Create a list of years or period markers in separate cells, and reference them. For example:

     =hf_Revenue_per_Dollar_Cash($A2, B$1)

     Then drag the formula down or across.

3. What is the best practice for annual vs. quarterly data?

   • For an overview, use the yearly parameter. For deeper insights or short-term trends, specify the quarter or TTM.

4. Can I combine this with other MarketXLS historical functions?

   • Absolutely. You can cross-reference other fundamental or price-based metrics for more comprehensive analysis.

?? Note: Use consistent periods (year/quarter) across various functions to maintain data accuracy and relevance.

For more detailed fundamental insights, you may find these related MarketXLS historical formulas helpful:

• Revenue (Historical)
• Cost Of Revenue (Historical)
• Gross Profit (Historical)
• R & D Expenses (Historical)
• Selling General and Administrative Expense (Historical)