Prepaid Expenses (Historical) Formula in Excel

Get insights into a company's future financial commitments by analyzing the prepaid expenses, which are payments made in advance for goods or services. With MarketXLS, you can easily pull historical data and streamline your investment research. This documentation shows you how to use the Prepaid Expenses (Historical) formula in Excel for data-driven decision-making.

Understanding Prepaid Expenses (Historical)

• Purpose: This formula retrieves the historical amount of prepaid expenses for a specified security and time period.
• Key Benefits:
  • Helps estimate a company's future payment obligations.
  • Aids in monitoring changes in working capital.
  • Useful for evaluating company liquidity and budgeting.
• When to Use:
  • To analyze a company's balance sheet for historical commitments.
  • During quarterly or yearly financial statement reviews.

Syntax and Parameters

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

Return Value:
• Returns a numeric value indicating the amount of prepaid expenses for the specified period.
• If the symbol is invalid, data is unavailable, or the license is not valid, the function returns "NA".

?? Note: This function relies on external data from MarketXLS servers; slight delays or occasional unavailability may occur.

Date and Symbol Input Formats

Use any of the following methods to reference symbols or date-related inputs, where applicable:

1. Cell references:

   =hf_Prepaid_Expenses(A1, "2022")

2. Direct strings or dates in quotes (if the function is extended to accept date-based strings):

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

3. Using Excel date functions (again, if extended for date interpretation):

   =hf_Prepaid_Expenses(TEXT(A1,"yyyy-mm-dd"))

? Pro Tip: Use references like "ly", "lq", or "lt" for data relative to the last year, last quarter, or last 12 months, respectively.

Examples and Usage

Below are practical examples of using Prepaid Expenses (Historical) in Excel:

1. Basic usage with year:

   =hf_Prepaid_Expenses("MSFT", "2022")

   Retrieves prepaid expenses for Microsoft (MSFT) in the year 2022.

2. Specifying a quarter:

   =hf_Prepaid_Expenses("MSFT", "2022", 2)

   Retrieves prepaid expenses for the second calendar quarter of 2022.

3. Using TTM (trailing twelve months):

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

   Retrieves prepaid expenses for Q3 2022 on a trailing-twelve-month basis.

4. Last Quarter (lq) references:

   =hf_Prepaid_Expenses("MSFT", "lq")

   Retrieves data for the most recent quarter.

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

   Retrieves data for one quarter prior to the last quarter.

5. Last Year (ly) references:

   =hf_Prepaid_Expenses("MSFT", "ly")

   Retrieves data for the latest full year.

   =hf_Prepaid_Expenses("MSFT", "ly-1")

   Retrieves data for one year prior to the last year.

6. Last 12 months (lt):

   =hf_Prepaid_Expenses("MSFT", "lt")

   Retrieves data for the last 12 months from the most recent quarter.

   =hf_Prepaid_Expenses("MSFT", "lt-1")

   Retrieves data for the previous last 12 months period.

?? Note: The function returns "NA" if data is not available or if your MarketXLS license type does not support the requested feature.

Common Questions

1. Why am I getting "NA"?

   • Invalid symbol input, license issue, or data not found for the specified period.

2. How often is the data updated?

   • MarketXLS updates fundamentals typically on a daily basis, but frequency can vary based on data availability.

3. Can I use this for all global stocks and indices?

   • Major US and international symbols are supported. Some specialized or over-the-counter assets may not have data.

4. Is there a limit to how many calls I can make?

   • This depends on your MarketXLS plan. Refer to your subscription details for usage limits.

5. Does using TTM slow down performance?

   • TTM calculations request multiple data points, which can slightly impact performance compared to single-quarter or single-year queries.

? Pro Tip: Combine hf_Prepaid_Expenses with other MarketXLS historical fundamentals (such as hf_Revenue, hf_CostOfRevenue) to get a comprehensive picture of a company's financial health.