Dividend Yield (Historical) Formula in Excel

Excel users and MarketXLS subscribers can leverage the "Dividend Yield (Historical)" formula to retrieve historical dividend yield values for a stock symbol or other asset. This function is particularly useful for investors who want to track how dividend yields have changed over time.

Understanding Dividend Yield (Historical)

• Purpose: The Dividend Yield (Historical) formula helps you analyze the historical dividend yield of a security for a given period.
• Use Cases:
  • Determining long-term dividend trends.
  • Comparing dividend yield changes between consecutive quarters or years.
  • Evaluating performance for investment decisions based on yield history.
• Key Benefits:
  • Quick retrieval of historical yield data.
  • Ability to specify quarter or trailing twelve months (TTM) periods.
  • Seamless integration with Excel for further analysis.

Syntax and Parameters

=hf_Dividend_Yield(symbol, year, [quarter], [TTM])

?? Note: The function returns a numeric value when data is available. If the symbol is invalid, the subscription is not active, or data cannot be retrieved, the function returns "NA".

Return Value

• A numeric value representing the dividend yield percentage for the specified period.
• Returns "NA" if data is unavailable or there is an error.

Error Handling

• Invalid or unsupported symbol: "NA"
• License or data subscription issues: "NA"
• Invalid year, quarter, or TTM inputs: "NA"

? Pro Tip: Use references or formulas to dynamically supply year and quarter parameters. For example, if cell A1 contains a year, you can use:

=hf_Dividend_Yield("MSFT", A1)

Examples and Usage

Below are examples showing various input configurations:

1. Basic annual usage

   =hf_Dividend_Yield("MSFT", 2022)

   Returns the historical dividend yield for Microsoft (MSFT) in the year 2022.

2. Specifying a quarter

   =hf_Dividend_Yield("MSFT", 2022, 2)

   Returns the yield for Q2 of 2022.

3. Trailing twelve months (TTM)

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

   Returns the yield for the trailing twelve months from Q3 2022.

4. Using shortcuts (last quarter, last year, etc.)

   =hf_Dividend_Yield("MSFT", "lq")
   =hf_Dividend_Yield("MSFT", "ly-1")
   =hf_Dividend_Yield("MSFT", "lt")

   • "lq" retrieves the last available quarter.
   • "ly-1" retrieves the year before the previous year.
   • "lt" retrieves the last twelve months.

Date Inputs

You can also employ different ways to pass a date-like string or reference for the year parameter:

• By cell reference:

  =hf_Dividend_Yield("MSFT", A1)

• By direct date string:

  =hf_Dividend_Yield("MSFT", "2024-03-15")

• By Excel date function:

  =hf_Dividend_Yield("MSFT", TEXT(A1, "yyyy-mm-dd"))

?? Note: In many cases, MarketXLS processes the year parameter as a simple string, so using "YYYY" might be the most straightforward approach. Date strings are typically used for advanced references or where supported by MarketXLS.

Common Questions

1. Why am I getting "NA" or an error message?

• Ensure your MarketXLS subscription is active and includes historical fundamentals data.
• Verify that the symbol is correct and supported.
• Double-check your year, quarter, or TTM inputs to ensure valid formats.

2. Does the function support international symbols?

• Yes, when the data is available for that market. Use the relevant symbol format required by MarketXLS.

3. Are there performance considerations?

• When calling multiple historical functions across many symbols, you may experience slower performance due to data fetches. Consider limiting simultaneous requests or using batch data pulls.

4. Can I reference other cells for dynamic inputs?

• Absolutely. Use standard Excel references for symbol, year, quarter, and TTM to maximize flexibility.

? Pro Tip: Combine this function with other historical fundamental formulas like hf_Revenue, hf_Gross_Profit, or hf_RnD_Expense for comprehensive fundamental analysis.

By following these guidelines, Excel users can harness the power of the Dividend Yield (Historical) formula in MarketXLS to make more informed investment decisions.