The rise and fall of LIBOR (and rise of SOFR)

andysinclairLeave a comment
City of London skyline with skyscrapers

Many years ago, while working at an investment bank in the City of London, I spent a lot of time learning all about the inner workings of the global finance industry. Attending various courses and eventually sitting a tricky exam led to me qualifying for the ACI Dealing Certificate, a rite of passage for many working in foreign exchange or money markets at the time.

One concept above all others dominated this education, it was the “price of money” and the gold standard for this measure was LIBOR, the London Interbank Offered Rate.

LIBOR served as the benchmark interest rate at which major global banks lent to one another in the international interbank market for short-term loans.

It was everywhere and included in many of the formulas that I had to learn as part of this education. It had been around “forever” and at its peak over $300 trillion in financial contracts globally were structured around this measure.

Fast forward 20 years (!) and today LIBOR is no more.

Why did LIBOR disappear?

LIBOR was based on trust and that trust evaporated.

Banks were asked, on a daily basis, at what rate they could borrow funds. They were trusted to provide a truthful answer, and these answers provided the LIBOR rate for the day.

In 2012 news broke of the LIBOR rigging scandal, and the rest is history. Traders had colluded to rig the rate to generate trading profits over a 7-year period.

The fallout took many years to play out until eventually LIBOR disappeared completely in 2024.

What replaced LIBOR?

LIBOR was replaced globally by national risk-free-rates based on actual transaction data in each country’s respective currency overnight market.

SOFR (Secured Overnight Financing Rate) is the USD replacement, €STR (Euro Short-Term Rate) is the EUR replacement and SONIA (Sterling Overnight Index Average) is the GBP replacement. There are equivalents in all other major world currencies.

Accessing SOFR rates in Excel

If you are building financial models for corporate debt, bond pricing etc. in Excel then having easy access to current and historical SOFR rates is very important.

Excel Price Feed makes this very easy via several Excel formulas which leverage Federal Reserve Economic Data (FRED) for the SOFR rates.

For example, to retrieve the latest SOFR rate in your spreadsheet, this simple Excel formula can be used:

=EPF.FRED.Last("SOFR")

Each time you refresh your spreadsheet the latest rate is retrieved so your spreadsheet is always upto date.

You can also easily download a timeseries of historical rates using this formula, which retrieves the last 30 days rates:

=EPF.FRED.HistoricLookback("SOFR",30,"DESC",0)

And here is a simple Excel chart showing these rates over time:

SOFR historical rates chart in Excel

You can download our sample SOFR spreadsheet from our website.

And for more details on getting started with Excel Price Feed, head over to our website for your free 10-day trial: https://www.excelpricefeed.com/userguide

And finally…

Bonus point if you can answer this LIBOR related question, which I dug out from my study notes back in the late 90’s, but no points for remembering what DEM stood for!:

DEM FRA LIBOR question

“Money never sleeps” – 24 Hour trading is here to stay

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24 hours sign

Nasdaq recently announced, starting December 6, new trading hours from 9:00 pm to 4:00 am, effectively increasing the trading day to 23 hours (with one hour available for settlement operations).

This reinforces the trend which has seen investors demand longer trading hours outside the traditional exchange daytime hours, with many markets now available 24 hours a day.

The 24-hour trading periods

The 24 hour trading day however is not one continuous trading period: for example the US stock market operates across four primary trading periods each weekday, spanning the full 24-hour cycle across major exchanges, like NYSE and Nasdaq, and Alternative Trading Systems (ATS).

Each period has its own characteristics and mechanics which investors need to be aware of:

Trading PeriodTime (US Eastern Time)Key Characteristics & Mechanics
Pre-Market4:00 AM – 9:30 AMVolatility is often high as traders react to overnight news, European market activity, and pre-bell corporate earnings reports.
Regular Trading Hours (RTH)9:30 AM – 4:00 PMThe core session offered directly by primary exchanges. Peak liquidity, tightest bid-ask spreads and highest execution volume occur during this window.
After-Hours (Post-Market)4:00 PM – 8:00 PMCommences right after the closing bell. Most US earnings announcements release immediately after 4:00 PM, driving significant price movement.
Overnight8:00 PM – 4:00 AMOperated via dark pools and specialized ATS (e.g., Blue Ocean ATS). Trades execute Sunday through Thursday nights, primarily using limit orders for select liquid equities and ETFs.

The new Excel formulas

To cater for this shift towards 24 hour trading we have recently added some new Excel formulas which enable you to retrieve prices for each of these periods, as well as a new general formula which will return the “24 hour” price.

(All of these formulas have corresponding change and change % formulas):

Trading PeriodExcel Price Feed Formula
Pre-MarketEPF.Yahoo.PreMarketPrice
Regular Trading Hours (RTH)EPF.Yahoo.Price
After-Hours (Post-Market)EPF.Yahoo.PostMarketPrice
OvernightEPF.Yahoo.OvernightMarketPrice
24 hour (automatically switches between periods)EPF.Yahoo.Price24h

EPF.Yahoo.OvernightMarketPrice

This new formula returns the overnight market price, in this case from Blue Ocean ATS via Yahoo Finance.

EPF.Yahoo.Price24h

This new formula returns a price regardless of the time of day and currently active trading session. This is really useful if you want your spreadsheet to be easily updated any time of the day with just one formula for the price.

See our User Guide for full details of the Excel Formulas.

The formulas in action

We have also added these formulas to our sample spreadsheet

Here is Dell stock during the pre-market session: you can see that the pre market price (571.70) and 24 hour price (571.70) are available. The regular market price (578.96) is the close price of the previous days regular market session:

Dell stock 24 hour price

We hope you find these new formulas useful.

How to Get the Last Trading Day of Each Month in Excel

Katerina AntonopoulouLeave a comment

The problem with month-end dates

If you want to create a table of historical month-end prices in Excel, there is a small problem you need to deal with: the last day of a month isn’t always a trading day.

For example, 31 May 2025 was a Saturday, so there was no closing price for the S&P 500 on that date. Similarly, month-end dates can fall on Sundays or exchange holidays.

Let’s say we want to create a table showing the month-end levels for three major indices:

  • S&P 500 (^GSPC)
  • NASDAQ Composite (^IXIC)
  • FTSE 100 (^FTSE)

We could use the EPF.Yahoo.Historic.Close formula to retrieve the closing price:

=EPF.Yahoo.Historic.Close("^GSPC",A3)

This works when the date in A3 is a trading day. However, if the date is a Saturday, Sunday or exchange holiday, there is no closing price for that date and the formula returns an error:

Formula =EPF.Yahoo.Historic.Close("^GSPC",A3) showing an error for a month-end date that falls on a non-trading day

In this article, we’ll show you how to automatically find the last available trading day’s closing price for each month, without having to manually enter the actual last trading date of each month.

Using historical data to find the last trading day

One option would be to use Excel’s WORKDAY function to move backwards from the month-end date.

The problem is that WORKDAY knows about weekends, but it doesn’t automatically know about every exchange-specific holiday.

A better approach is to ask Excel Price Feed for a small range of daily historical data ending on the month-end date, and then simply take the final available trading day.

For example for May 2025, we can do this using:

=EPF.Yahoo.HistoricDatePeriod("^GSPC","Daily",A7-14,A7,"ASC",0)

This retrieves the daily historical data from 14 calendar days before the month-end through to the month-end.

The result contains several columns of historical data:

The HistoricDatePeriod formula entered in Excel, with the resulting Date, Open, High, Low, Close and Volume data spilling into the worksheet

Because we have requested the data in ascending order, the final row will contain the most recent trading day in our date range, in this case the 30th May 2025.

That is exactly what we need.

Why use a 14-day range?

You might wonder why we’re using:

A3-14

rather than simply looking at the previous few days.

The reason is that we’re working with calendar days, not trading days. A month-end can fall immediately after a weekend or a holiday period, so giving the formula a reasonable buffer makes sure there is a trading day available in the requested range.

Fourteen calendar days is normally plenty for ordinary weekends and holiday combinations. If you’re working with a market that has an unusually long closure, you can increase the buffer.

The important part is that the end date remains the month-end date, so the final row returned by HistoricDatePeriod is the last available trading day on or before that date.

Extracting the closing price

We don’t need all of the historical data in our final table. We only want the Close value from the final trading day.

Excel’s INDEX function can be used to extract the fifth column, which is the Close column:

=INDEX(data,,5)

We can then use Excel’s TAKE function to return the final value from that column:

=TAKE(closes,-1)

Rather than putting these into separate formulas, we can combine them using Excel’s LET function.

The final formula

Assuming:

  • The ticker is in row 2
  • The month-end date is in column A
  • The first ticker is in B3
  • The first month-end date is in A3

the formula is:

=LET(
    data,EPF.Yahoo.HistoricDatePeriod(B$2,"Daily",$A3-14,$A3,"ASC",0),
    closes,INDEX(data,,5),
    TAKE(closes,-1)
)

One of the advantages of this formula is that you don’t need to change it for every index or every month.

The ticker reference is:

B$2

and the date reference is:

$A3

This means we can simply copy the formula across the columns and down the rows. The finished spreadsheet will look something like this:

The final formula entered in B3, with the resulting closing price displayed

This formula does three things:

  1. Retrieves daily historical data for the ticker in B2, covering the 14 calendar days leading up to the date in A3.
  2. Extracts the Close column from the historical data.
  3. Returns the final close in the data set — which is the last available trading day on or before the month-end.

Notice that the dates in column A are still the calendar month-end dates. The formula automatically finds the last trading day when the month-end itself isn’t a trading day. For example, if the month ends on a Saturday, the formula will return Friday’s closing price.

This approach avoids maintaining a list of exchange holidays and means your spreadsheet continues to work automatically when you add more months or more indices.

Bonus Tip: Automatically generating the month-end dates

You don’t have to type all the month-end dates manually either.

If A3 contains:

31/01/2025

you can use:

=EOMONTH(A3,1)

in A4 and copy the formula down.

This will generate the subsequent month-end dates automatically:

Column A showing the EOMONTH formula being copied down to generate all 12 month-end dates

We hope you find this useful!

New Date/Time Excel Formulas

andysinclairLeave a comment

We have just released a new version of Excel Price Feed, and this release includes a bunch of new Excel formulas to help with date/time manipulation in Excel.

New “Now” Formulas

The first set of new formulas are replacements for the built-in Excel “volatile” formulas NOW and TODAY.

We’ve talked about volatile Excel formulas on this blog before, the key takeaway being to avoid them at all costs. Unfortunately this is easier said than done as there is no built-in Excel alternative, until now…

Introducing EPF.Dates.Now.Local, a non volatile Excel formula which returns the local date/time on your PC.

In addition, there is now EPF.Dates.Now.UTC which returns the current UTC (Coordinated Universal Time) date/time.

We’ve also created formulas to return the current date/time in a bunch of different time zones:

  • EPF.Dates.Now.EST for US Eastern Standard Time, the time zone for New York.
  • EPF.Dates.Now.GMT for GMT Standard Time, the time zone for London.
  • EPF.Dates.Now.CET for Central Europe Standard Time, the time zone for Paris and Frankfurt.
  • EPF.Dates.Now.JST for Japan Standard Time, the time zone for Tokyo.
  • EPF.Dates.Now.AEST for Australian Eastern Standard Time, the time zone for Sydney.
Excel Now formulas for different time zones including UTC, EST and GMT

There is also an additional formula, EPF.Dates.Now.TimeZone, in order to convert a UTC date/time into any other time zone from this list: https://www.excelpricefeed.com/userguide/date-time-formulas#timezones

New Date/Time Conversion Formulas

Converting dates and times between time zones in Excel is not easy. There are no built in conversion formulas in Excel and many of the workarounds you see online are either very complicated string manipulation formulas, or simpler formulas but don’t take into account daylight savings time etc.

We have therefore released a bunch of simple-to-use Excel formulas that convert between time zones taking into account daylight savings time. Like the new Now formulas they cover major time zones:

  • EPF.Dates.UTC.To.Local
  • EPF.Dates.UTC.To.EST
  • EPF.Dates.UTC.To.GMT
  • EPF.Dates.UTC.To.CET
  • EPF.Dates.UTC.To.JST
  • EPF.Dates.UTC.To.AEST
  • EPF.Dates.UTC.To.TimeZone

Here we can see them in action on our sample spreadsheet:

Excel date/time time zone conversion formulas

We hope you find these new formulas useful and let us know if there are other date/time related formulas that you would like us to add to the Add-in.

How to analyze stock split information in Excel

andysinclairLeave a comment
Stock split

If you’ve ever seen a headline such as “Nvidia stock rises after 10-for-1 stock split” and wondered whether that’s actually a big deal, you’re not alone. Stock splits sound technical but the idea behind them is surprisingly simple and they can matter more to investors than they first appear.

What Is a Stock Split?

A stock split happens when a company changes the number of shares outstanding by either dividing or multiplying its existing shares, without changing the overall value of the company.

Think of it like breaking a $100 bill into two $50 bills. You still have $100; it’s just divided into smaller pieces!

Here’s an example:

  • Before the split: You own 1 share priced at $200
  • After a 2-for-1 split: You own 2 shares, each priced at $100
  • Your total investment value stays the same: $200 before, $200 after

Nothing magical happened to the company’s fundamentals. revenue, profits, and market capitalization don’t change just because of a split.

Why Do Companies Split Their Stock?

To Make Shares More Affordable

A high stock price can be intimidating to everyday investors. While fractional shares exist many investors still prefer whole shares. By lowering the price per share, a company:

  • Attracts more retail investors
  • Increases accessibility
  • Makes trading feel more approachable

To Improve Liquidity

Lower share prices often lead to:

  • More trading activity
  • Tighter bid-ask spreads
  • Easier entry and exit for investors

As a Signal of Confidence

Companies usually split their stock after strong price appreciation. Management doesn’t do this randomly; it often reflects confidence in continued growth. While a split itself doesn’t create value, it can reinforce the idea that:

  • The company is doing well
  • Leadership expects the business to keep performing

Why Stock Splits Matter to Investors

From a purely financial perspective nothing changes. But in the real-world lower prices feel “cheaper”, more investors get involved and therefore demand can increase Markets are driven by people, not just spreadsheets!

Some indexes and funds weigh stocks by price or have practical constraints. A lower share price can make inclusion easier and therefore increase exposure to the stock through ETFs and mutual funds. That can mean more automatic buying over time and potentially an appreciating stock price.

Using Excel to Analyze Stock Splits

The Excel Price Feed Add-in includes 3 new Excel formulas for retrieving stock split data:

EPF.Yahoo.Splits.DatePeriod

This Excel formula retrieves a time series of stock splits for the specified ticker and date period.

The example spreadsheet and formula below shows Apple stock (AAPL) splits since 2000:

Stock split time series Excel formula

EPF.Yahoo.Splits.LastDate

This Excel formula retrieves the last date there was a stock split event for the specified ticker.

EPF.Yahoo.Splits.LastRatio

This Excel formula retrieves the last stock split ratio event for the specified ticker.

The example spreadsheet below shows a bunch of stocks and their last split date and ratio using these formulas:

Excel stock split examples

We hope you find these new Excel formulas useful.

Excel visualisation tips for stock portfolio and watchlist spreadsheets

andysinclairLeave a comment

We were recently involved in helping a customer build an stock watchlist Excel spreadsheet based around the Large Cap watchlist on the Yahoo Finance website.

They wanted it to “look good” so here are some techniques we used to improve formatting and visualisations:

Custom number format colours

One useful Excel feature for financial spreadsheets is the ability to change the colour of a number depending on whether the number is positive or negative. Usually this is used to show negative numbers as red and positive as black, like this:

Excel custom number formatting

You can see that the negative colour, red, is specified in [] brackets; the semi-colon separates the positive and negative formatting (black is the default colour).

What if we want to show a positive change in green, such as an increase in a stock price? Well, Excel has 8 built in colours:

  • [Black]
  • [Green]
  • [White]
  • [Blue]
  • [Magenta]
  • [Yellow]
  • [Cyan]
  • [Red]

Let’s try green, with this formatting: [Green]0.00 ;[Red]-0.00

Excel number format green and red

Ugh, it’s a horrible luminous green!

Fortunately there are 56 colours that we can choose from, although these are not well documented by Microsoft and require a colour code rather than a name:

Excel custom number format colors

Let’s try Colour10 instead, and we’ll also add a + symbol to signify a positive change: [Color10]+0.00 ;[Red]-0.00

Excel positive negative number format color

That looks much better!

Data Bars

Data bars are a very simple but effective visualisation technique in Excel to easily show comparisons between numbers.

Here we are showing the 52 week percentage change in a stock price for a bunch of stocks:

52 week percentage change stock prices

We would like to add a Data Bar so that a quick visual comparison can be made.

First, we highlight the cells, a small icon appears at the bottom right of the selection, we can then see the various visualisation options:

Excel Data Bars selection dialog

Select “Data Bars”, and the result is horizontal bars which provide a great way to quickly compare values:

Excel stocks 52 week change with a Data Bar visualisation

There are other visualations, known in Excel as “Conditional Formatting” such as Color Scales and Icon Sets which can be used to create similar visualisations.

We hope you find these tips useful.

You can download the Large Cap spreadsheet here: https://coderun.blob.core.windows.net/epf/samples/YahooLargeCapStocks.xlsx

It includes Excel Price Feed formulas to retrieve live stock data, so each time you refresh the spreadsheet the values are updated:

Excel Price Feed large cap stocks spreadsheet

Excel Price Feed Add-in Release (v1.140)

andysinclairLeave a comment

Today we released a new version of Excel Price Feed. To update your Add-in, please follow the instructions in the User Guide.

This release includes the following changes:

Yahoo Finance: EPF.Yahoo.HistoricDatePeriod formula

We’ve made several improvements to this formula.

We have fixed an issue which affected certain stock/date combinations which returned additional data points outside the requested date range.

We have also added an additional optional parameter includePrePost which if set will include pre and post market data in the returned time series (for periods less than daily).

We have also made 3 of the parameters optional so you just need to specify a ticker, period and start/end date.

For example, this formula will return hourly data for Apple from 1 to 4 October; it will return headers, date in descending date order and not include pre or post market data:

=EPF.Yahoo.HistoricDatePeriod("APPL","Hourly","2025-10-01","2025-10-04")

The other parameters: order, includeHeaders and includePrePost are optional.

For more details please see the Excel Formula Reference: Historical Array Formulas section in the User Guide.

Yahoo Finance: fix EPF.Yahoo.PEGRatio formula

This formula has been fixed:

PEG Ratio formula in Excel

Chart Crime and Bubbles

andysinclairLeave a comment

There are lies, damned lies and statistics. There are also charts that are published to mislead or to simply reinforce a point of view that’s flimsy at best or just plain wrong.

These charts are known as “chart crimes” and one appeared all over social media last month. Usually I would just make a comment and move on but this one received over 2 million views and deserves further investigation.

It was a chart comparing the growth of the Nasdaq over two periods: the dot com bubble and the current AI “bubble”. The conclusion being that we are on the same upward trajectory and all things being equal are due a major crash anytime soon.

Here is the chart and tweet in question:

AI Boom vs. Dot Com Bubble.

Aside from the obvious lack of timescale on the x axis and disparity in y axis scaling, does this chart bear any resemblance to reality?

Let’s build our own using Excel Price Feed to retrieve historical market data and produce an Excel chart based on the actual data.

For the Dot com bubble period we will use 1996 to 2002 and for present day we will look at data from Q4 2022 (when ChatGPT was released) to now.

To retrieve the data we will use the Excel Price Feed HistoricDatePeriod formula. Here is an example of how to retrieve monthly data for the NASDAQ Composite Index:

=EPF.Yahoo.HistoricDatePeriod("^IXIC","MONTHLY","1 Sep 2022","1 Oct 2025","ASC",1)

We will base each time series to 1 so we are comparing like-for-like. To do this we simply divide each point by the initial starting point.

We can now plot this data in Excel; the blue line is the dot com bubble, and the orange line is the past 3 years:

Compare Nasdaq dotcom bubble vs AI bubble

Not nearly as dramatic, the trajectory is similar but we are barely halfway towards the dot-com crash equivalent peak. So if the past is an indicator of the future then we should expect the market to double again from here and crash in about a year. But as they say, the past is not always a predictor of the future…

What about individual stocks?

Let’s look at one from the dot com bubble: Cisco (light blue) and one from now: Nvidia (green).

Nvidia has climbed at a much steeper rate than Cisco. Again, similar trajectory and timescales:

Compare CSCO dot com bubble with NVDA stock now

If you want to build financial charts like this yourself check out Excel Price Feed today and try it free for 10 days: https://www.excelpricefeed.com/

How to use Excel to find the highest high and lowest low for a stock time series (including the date)

andysinclair2 Comments
AAPL high low chart in Excel

We were recently contacted by a user who was trying to calculate the market high and low over an particular date period and more importantly the date that the high or low was reached.

Neither Excel Price Feed nor Excel have a single formula to calculate this, but we can use several Excel functions to achieve it.

For this example we will look at daily data, although the procedure and formulas used can be applied to any timeframe.

We start by using the Excel Price Feed “Historic Date Period” formula to retrieve the daily high/low/open/close over a specified date period for a specified resolution:

=EPF.Yahoo.HistoricDatePeriod(B1,"Daily",B2,B3,"DESC",1)

B1 is the stock ticker, B2 is the start date and B3 is the end date.

This formula outputs a table as shown below, the formula is in cell D1:

apple excel daily ohlcv

Finding the highest high over the period is easy, we simply use the MAX formula to find the maximum value of all the daily highs (column F):

=MAX(F:F)

To find the lowest low we use the MIN formula with column G:

=MIN(G:G)

The hard part is finding the date at which the highest high and lowest low was reached. We can achieve this by using a combination of Excel functions.

We will now walk through how to find the date of the highest high, which is in cell B5:

  1. Using the MATCH function we can find the row where the highest high was achieved. The MATCH function searches a range, in this case the column (G:G) and finds the row where the highest high is, in this case the value in cell B5 (260.10).
  2. We then take this row and use the ADDRESS function to combine it with the column where the date is located, column E (or the 5th column as this function requires a numeric column reference).
  3. We now have an address for the location of the date, via a column and row number. To return the actual value at this address we must use the INDIRECT function, this will then provide the date value of “26 Dec 2024”

The full formula looks like this:

=INDIRECT(ADDRESS(MATCH(B5,G:G,0),5))

Below we can see the full formula in the formula bar at the top and the result is “26 Dec 2024”:

excel highest high

To find the date of the lowest low we just replace column G with column H and the low which is in cell B5.

We hope you find this useful and if you would like to try the spreadsheet for yourself you can download it from here.

Excel Price Feed Add-in Release (v1.139)

andysinclairLeave a comment

Today we released a new version of Excel Price Feed. To update your Add-in, please follow the instructions in the User Guide.

In this release, we plugged in any gaps in formulas which were missing the Quarterly and Trailing 12 Months equivalent. The gaps were in the Balance Sheet, Income Statement and Cash Flow groups of formulas.

You can see these formulas in use in our example Yahoo Finance spreadsheet.

Yahoo Finance: Income Statement formulas

We added the following Quarterly formulas, which take as input a stock ticker and reporting quarter:

  • EPF.Yahoo.QuarterlyImpairmentOfCapitalAssets
  • EPF.Yahoo.QuarterlyOtherSpecialIncomeCharges
  • EPF.Yahoo.QuarterlyRestructuringAndMergersAcquisition
  • EPF.Yahoo.QuarterlySpecialIncomeCharges
  • EPF.Yahoo.QuarterlyWriteOff

And the following Trailing 12 Month (TTM) Formulas, which take as input just a stock ticker:

  • EPF.Yahoo.TTMImpairmentOfCapitalAssets
  • EPF.Yahoo.TTMOtherSpecialIncomeCharges
  • EPF.Yahoo.TTMRestructuringAndMergersAcquisition
  • EPF.Yahoo.TTMSpecialIncomeCharges
  • EPF.Yahoo.TTMWriteOff

Here is an example of the new formulas used in a sheet. This dataset is for the NWL ticker.

And here are a couple of examples of formulas we used:

=EPF.Yahoo.QuarterlyImpairmentOfCapitalAssets("NWL",0)/1000
=EPF.Yahoo.TTMImpairmentOfCapitalAssets("NWL")/1000

Please bear in mind when using these formulas that not every company reports the same type of information so sometimes the formulas might return #NUM!

For more details please see the Excel Formula Reference: Income Statement section in the User Guide.

Yahoo Finance: Balance Sheet formulas

We also added some additional formulas for retrieving Quarterly figures, which all take as inputs a stock ticker and a quarter. Yahoo doesn’t make available equivalent TTM formulas.

  • EPF.Yahoo.QuarterlyAccountsPayable
  • EPF.Yahoo.QuarterlyAccountsReceivable
  • EPF.Yahoo.QuarterlyAssetsTotalCash
  • EPF.Yahoo.QuarterlyCapitalLeaseObligations
  • EPF.Yahoo.QuarterlyCurrentAssets
  • EPF.Yahoo.QuarterlyCurrentLiabilities
  • EPF.Yahoo.QuarterlyGoodwill
  • EPF.Yahoo.QuarterlyGoodwillAndOtherIntangibleAssets
  • EPF.Yahoo.QuarterlyInventory
  • EPF.Yahoo.QuarterlyInvestedCapital
  • EPF.Yahoo.QuarterlyLongTermDebt
  • EPF.Yahoo.QuarterlyNetDebt
  • EPF.Yahoo.QuarterlyNetPropertyPlantEquipment
  • EPF.Yahoo.QuarterlyRetainedEarnings
  • EPF.Yahoo.QuarterlyStockholdersEquity
  • EPF.Yahoo.QuarterlyTangibleBookValue
  • EPF.Yahoo.QuarterlyTotalAssets
  • EPF.Yahoo.QuarterlyTotalDebt
  • EPF.Yahoo.QuarterlyTotalLiabilities
  • EPF.Yahoo.QuarterlyTotalNonCurrentAssets
  • EPF.Yahoo.QuarterlyTotalNonCurrentLiabilities
  • EPF.Yahoo.QuarterlyWorkingCapital

Here is an example of these new formulas in action:

And here are some examples of the new formulas we used:

=EPF.Yahoo.QuarterlyAccountsPayable("NWL",0)/1000
=EPF.Yahoo.QuarterlyAccountsReceivable("NWL",0)/1000

For more details please see the Excel Formula Reference: Balance Sheet section in the User Guide.

Yahoo Finance: Cash Flow formulas

Lastly, we added quite a few additional Quarterly and TTM formulas for Cash Flow. Along with the formulas for Free Cash flow (added in the previous version) below are all the Cash Flow formulas in the system.

Quarterly formulas:

  • EPF.Yahoo.QuarterlyAccountsPayableChange
  • EPF.Yahoo.QuarterlyAccountsReceivableChange
  • EPF.Yahoo.QuarterlyAcquisitions
  • EPF.Yahoo.QuarterlyBeginningCashPosition
  • EPF.Yahoo.QuarterlyCapitalExpenditures
  • EPF.Yahoo.QuarterlyChangeInCash
  • EPF.Yahoo.QuarterlyChangeInWorkingCapital
  • EPF.Yahoo.QuarterlyCommonStockIssued
  • EPF.Yahoo.QuarterlyCommonStockRepurchased
  • EPF.Yahoo.QuarterlyDebtRepayment
  • EPF.Yahoo.QuarterlyDeferredIncomeTax
  • EPF.Yahoo.QuarterlyDepreciationAndAmortization
  • EPF.Yahoo.QuarterlyDividendsPaid
  • EPF.Yahoo.QuarterlyEndCashPosition
  • EPF.Yahoo.QuarterlyFreeCashFlow
  • EPF.Yahoo.QuarterlyInventoryChange
  • EPF.Yahoo.QuarterlyOtherCashflowsFromInvestingActivities
  • EPF.Yahoo.QuarterlyOtherFinancingActivities
  • EPF.Yahoo.QuarterlyOtherNonCashItems
  • EPF.Yahoo.QuarterlyPurchasesOfInvestments
  • EPF.Yahoo.QuarterlySalesOfInvestments
  • EPF.Yahoo.QuarterlyStockBasedCompensation
  • EPF.Yahoo.QuarterlyTotalCashflowsFromFinancingActivities
  • EPF.Yahoo.QuarterlyTotalCashflowsFromInvestingActivities
  • EPF.Yahoo.QuarterlyTotalCashflowsFromOperatingActivities

Trailing 12 Month (TTM) formulas:

  • EPF.Yahoo.TTMAccountsPayableChange
  • EPF.Yahoo.TTMAccountsReceivableChange
  • EPF.Yahoo.TTMAcquisitions
  • EPF.Yahoo.TTMBeginningCashPosition
  • EPF.Yahoo.TTMCapitalExpenditures
  • EPF.Yahoo.TTMChangeInCash
  • EPF.Yahoo.TTMChangeInWorkingCapital
  • EPF.Yahoo.TTMCommonStockIssued
  • EPF.Yahoo.TTMCommonStockRepurchased
  • EPF.Yahoo.TTMDebtRepayment
  • EPF.Yahoo.TTMDeferredIncomeTax
  • EPF.Yahoo.TTMDepreciationAndAmortization
  • EPF.Yahoo.TTMDividendsPaid
  • EPF.Yahoo.TTMEndCashPosition
  • EPF.Yahoo.TTMFreeCashFlow
  • EPF.Yahoo.TTMInventoryChange
  • EPF.Yahoo.TTMOtherCashflowsFromInvestingActivities
  • EPF.Yahoo.TTMOtherFinancingActivities
  • EPF.Yahoo.TTMOtherNonCashItems
  • EPF.Yahoo.TTMPurchasesOfInvestments
  • EPF.Yahoo.TTMSalesOfInvestments
  • EPF.Yahoo.TTMStockBasedCompensation
  • EPF.Yahoo.TTMTotalCashflowsFromFinancingActivities
  • EPF.Yahoo.TTMTotalCashflowsFromInvestingActivities
  • EPF.Yahoo.TTMTotalCashflowsFromOperatingActivities

Here is an example of the new formulas used in a sheet. This dataset is for the MSFT ticker.

Again the Quarterly formulas take a input a ticker and a reporting quarter and the Trailing 12 Month (TTM) Formulas take as input just a stock ticker. Examples:

=EPF.Yahoo.QuarterlyDividendsPaid("MSFT",0)/1000
=EPF.Yahoo.TTMDividendsPaid("MSFT")/1000

Please download our example Yahoo Finance spreadsheet to find examples of using these formulas.

We hope you find them useful. Let us know if there are any more formulas you would like us to add.