Thursday, April 12, 2012

Energy Sector: Integrated Oil & Gas - Quality of Earnings, Research & Development

The basic premise of this factor compares R&D expenditures with that of the industry.  Relative decreases may indicate that the company will have trouble competing in the future.

There are differences in how R&D expenditures are treated under U.S. Gaap and under IFRS.  Since Canada has adopted IFRS and there is a lot of cross border investment, I'm going to give a brief overview of both.

Under U.S. Gaap, R&D expenditures are expensed as incurred (there is an exception (of course) but we don't need to worry about it right now).  Under IFRS, Canada expenses research costs and capitalizes development costs.  If we were doing an analysis on securities that report in Canada, we would look at changes in intangibles which is found on the balance sheet and R&D expenses found on the income statement.  Since this analysis deals with securities that report in the States, we only need the Research and Development expenses and we need them for Y and Y-1.

Verdasis, the fundamental analysis software, doesn't at this stage have ready made information on industry averages.  However, you can easily manufacture them yourself with a high degree of confidence.  Higher, perhaps, than numbers that you might find elsewhere because you know how they've been calculated.  That being said, lets get into the calculations needed for this factor.

  1. To get the industry average, use the AVERAGE function for each of R&D Y and R&D Y-1,
  2. Find the growth (or decline) in the industry from Y-1 to Y by doing a simple return calculation: 
    • [(Industry R&D Y) - (Industry R&D Y-1)] / (Industry R&D Y-1)
  3. Do the same return calculation for each security to determine the change in R&D
    •  [(Security i R&D Y) - (Security i R&D Y-1)] / (Security i R&D Y-1)
  4. Subtract the industry figure calculate in 2 from each security figure found in 3.
If the company's R&D expenditures are greater than the industry average, then this is positive and the company gets a "1" rating.  If the expenditures are less than the industry average then the company gets a "-1" rating.

You can see the spreadsheet here:

Sunday, April 8, 2012

Energy Sector: Integrated Oil & Gas - Quality of Earnings, Accounts Receivable

For the next quality of earnings indicator in our investment analysis, we're going to look at is Accounts Receivable. 

The calculations for Accounts Receivable are identical to Inventory.  To begin, we collect the three most recent years of revenue and the three most recent years of accounts receivable.

I should probably discuss where each of the line items I use is found.  Accounts receivables and inventory are balance sheet figures, found near the top under current assets.  Revenue or sales is the top line on the income statement.

We need to pull:
  • Total revenue, Y, Y-1, and Y-2
  • Accounts Receivable - Trade, Net, Y, Y-1, Y-2.
And from this information we need to make five calculations:
  • Expected Sales,
  • Expected A/R,
  • % change in Sales,
  • % change in A/R,
  • % change in Sales - % change in A/R.
We proxy expected sales and expected A/R with an average of Y-1 and Y-2.  % change in sales and A/R is:
(Sales Y - Expected Sales)/Expected Sales.

If the percentage change in sales minus the percentage change in a/r is negative, that is an unfavorable signal.

Let's understand the logic.

If our actual sales is greater than our expected sales, we have a positive number.  The same reasoning applies to a/r.  When we take the difference between the % change in Sales and the % change in A/R, if accounts receivable has grown more than sales we get a negative number and a negative signal.

Lev & Thiagarajan discuss how disproportionate a/r increase can indicate sales difficulties (triggering credit extensions) as well as future bad debt write-offs.

I think of it like this - accounts receivable is a component of sales, but they're only on paper.  A sale on paper is not as good as a sale realized in cash.  The reasons are noted above and it's also because it can be indicative of aggressive policies that make the likelihood of actually collecting even more remote (cash is always king). So when I see the less desirable accounts receivable component growing as a percentage of all sales, it's a red flag.

I use the same rating system: 1 is a positive outcome, -1 is negative and 0 is a null or neutral result.  I use an "if, then" formula, rather than plugging the numbers in for each stock.  Verdasis was designed with normalized data - meaning that when it pulls new financial statement information, each Y, Y-1, Y-2 etc is automatically updated - this means that your data doesn't go stale and your ratings can change.

You can see the spreadsheet here:

The next factor we're going to look at is research and development.  These calculations are different from the inventory and accounts receivable ones.

Thank you for reading and I'll be back to you by the end of the week.

Monday, April 2, 2012

Energy Sector: Integrated Oil & Gas, US Stocks - Quality of Earnings, Overview and Inventory

I'm going to start our financial analysis by looking at the quality of earnings calculations but before I go any further, I need to give credit where credit is due.  I am indebted to Baruch Lev and S. Ramu Thiagarajan.  I extracted these indicators from their article "Fundamental Information Analysis", JSTOR, Journal of Accounting Research, Vol. 31, No. 2.  Thank you Dr. Lev and Dr. Thiagarajan.

The five indicators I look at are:
  • Inventory,
  •  Accounts Receivable,
  • Research & Development, 
  • Capital Expenditures,
  • Gross Margin,
  • Selling & Administration Expense.
As I mentioned, I use these six indicators to gauge the trust-worthiness of the financial statement themselves.   Although the importance is probably self-evident, I'll provide an example.

Let's say an investor finds a security that for some reason looks appealing - the earnings are growing at an impressive pace.  It is important to keep in mind that net income is an abstract concept.  There are a number of judgement calls made before arriving at that figure.  Some are benign, an honest reflection of the business or industry in which the company operates.  Some are not, some are manipulative.

For example, many frauds and subsequent company implosions have occurred around receivables.   Receivables can be aggressively recorded and used to artificially inflate earnings.

The one I'm going to discuss today is inventory.  Changes in inventory relative to other financial statement factors can tell a story.  Here are some examples:
  • Inventory increases that are greater than cost of goods sold increases can be negative sign as it can suggest trouble generating sales,
  • Inventory increases can hint at future earnings weakness as prices are cut to move excess inventory,
  • Inventory build-ups may indicate the need to write off obsolete products.
All of this tells us that we don't want to see inventory growing faster than sales. If it is, it's a red-flag.

I'm going to go into detail on the inventory quality of earnings calculation in this post.

When I set up this portfolio in Verdasis, I used the securities in Google's similarly named energy sub-sector, integrated oil & gas.  At the time, there were 23 securities.  If you want the list, you can get it here:

I set up the analysis template (where the user tells the software what financial information they want) to capture sales and and inventory information for the current period plus the last previous two years, or in other words:
  • Total Revenue, Y
  • Total Revenue, Y-1
  • Total Revenue, Y-2
  • Total Inventory, Y
  • Total Inventory, Y-1
  • Total Inventory, Y-2.
Once the data has been sent to a spread sheet, we have to make five calculations:
  • Expected Sales,
  • Expected Inventory,
  • % change in sales,
  • % change in inventory,
  • % change in sales - inventory.
Estimating or guessing on what the future sales might be isn't an exercise I would particularly like to undertake, so it is fortunate that Expected Sales and Expected Inventory can be proxied by taking the average of y-1 and y-2.  The value for expected sales is then compared to this year's sales with a simple return formula:

(Actual Sales in current year - Expected Sales) / Expected Sales

If the actual sales is greater than the expected sales, then the figure is a positive number, if not, it is negative.

Do the same calculations for inventory.

We then want to see how the numbers are moving in relationship to one another.

The best and fastest way to do this is just to subtract:

% change in sales - % change inventory.

If the number is positive, excellent.  If it isn't, red flag.

The final step is to summarize the result and a quick and meaningful way.  I use a 1, 0 and -1 system.  If my indicator is positive, I give a 1 rating.  I use -1 for a unfavorable rating and  0 for a null or neutral result.

You can click the link below to view the finished spreadsheet

The next post will be brief, as it will go through the Accounts Receivable calculation, which is identical to  Inventory.

Thank you so much for reading.  If you have any questions, please do not hesitate to ask!