Revenue Per Dollar Common Equity (Historical) Formula in Excel
Understanding Revenue Per Dollar Common Equity (Historical)
The Revenue Per Dollar Common Equity (Historical) formula in Excel, provided by MarketXLS, helps you quickly evaluate a company's efficiency by showing how much revenue is generated per dollar of common equity. This is a key metric for analysts and investors looking to understand how effectively a company uses equity funding to generate sales.
- Purpose: Offers insight into how productively shareholder equity is deployed.
- Key Benefits:
- Enables comparison across companies and sectors.
- Provides a historical perspective to track performance over time.
- Helps in spotting trends in revenue generation versus equity.
- When to Use:
- Evaluating historical financial performance.
- Performing fundamental analysis for investment decisions.
- Assessing a company's efficient use of equity in different time periods.
Syntax and Parameters
Use the formula as follows in Excel:
=hf_Revenue_per_Dollar_Common_Equity(Symbol, year, [quarter], [TTM])
Parameter | Description | Required | Example |
---|---|---|---|
Symbol |
The stock symbol or instrument identifier. Can be regular equities, indices, options, or cryptos. | Yes | "MSFT", "^SPX", "@MSFT 110122C00020000", "BTCUSD:DEFAULT" |
year |
The reporting year. You can also use special inputs like "lq" for last quarter, "ly" for last year, etc. | Yes | "2022", "lq", "lq-1", "ly-1", "lt", "lt-1" |
quarter |
The calendar quarter (1 to 4). If omitted, defaults to "1". Accepts "TTM" parameter if needed. | No | 1, 2, 3, or 4 |
TTM |
Set to "TTM" to fetch trailing twelve-month data from the specified quarter/year. Leave blank if not used. |
No | "TTM" |
?? Note: This function returns numeric values if data is available. Otherwise, it returns
"NA"
.
Return Value:
• Returns a numeric value indicating revenue per dollar of common equity.
• Returns "NA"
if the symbol is invalid, data is not available, or license validation fails.
Examples and Usage
Below are some common usage scenarios in Excel:
-
Basic Example for a Specific Year:
=hf_Revenue_per_Dollar_Common_Equity("MSFT", 2022)
Retrieves the revenue per dollar of common equity for Microsoft in 2022.
-
Year and Quarter:
=hf_Revenue_per_Dollar_Common_Equity("MSFT", 2022, 2)
Fetches the metric for calendar quarter 2 of 2022.
-
Trailing Twelve Months:
=hf_Revenue_per_Dollar_Common_Equity("MSFT", 2022, 3, "TTM")
Returns the trailing twelve-month figure from quarter 3 of 2022.
-
Last Quarter or Last Year:
=hf_Revenue_per_Dollar_Common_Equity("MSFT", "lq") =hf_Revenue_per_Dollar_Common_Equity("MSFT", "ly-1")
• "lq" retrieves data from the last reported quarter.
• "ly-1" retrieves data from last year minus one additional year.
? Pro Tip: You can reference a cell for the
Symbol
oryear
parameter (e.g., =hf_Revenue_per_Dollar_Common_Equity(A1, A2)) or use textual dates like =hf_Revenue_per_Dollar_Common_Equity("MSFT", TEXT(A1,"yyyy")) for custom date inputs.
Common Questions
-
Why am I getting "NA"?
- This may occur if the symbol is invalid, the data source is incomplete, or your MarketXLS license is not valid.
-
Can I apply this to different asset classes?
- Yes, you can use regular stock symbols, indices (e.g., "^SPX"), options (e.g., "@MSFT 110122C00020000"), and cryptocurrencies (e.g., "BTCUSD:DEFAULT").
-
Are there performance considerations?
- Large Excel sheets calling many MarketXLS formulas can slow down. Consider using fewer calls or caching data.
-
What other historical fundamental formulas are available?
- • Revenue (Historical): Returns total revenue for the chosen period.
• Cost Of Revenue (Historical): Retrieves total cost of revenue.
• Gross Profit (Historical): Indicates the gross profit for the specified period.
• R & D Expenses (Historical): Shows research and development expenses.
• Selling General and Administrative Expense (Historical): Tracks SG&A expenses over a period.
- • Revenue (Historical): Returns total revenue for the chosen period.
Use this function as part of a broader fundamental analysis to assess the company’s operational efficiency and compare it with peers across different historical periods.