Tuesday, May 22, 2012

Summary of the Quality of Earnings Measures

The next step is easy and quite satisfying: sum all of the quality of earnings ratings to get a final figure*.  The bigger the number, the higher our confidence in what the financial statements are telling us.

I turned the sums into a chart:

You can see that CVX (5 out of 6) and BP (4 out of 6) look the best, but I would still consider the 3 out of 6's as well, depending how the other factors turn out.

If you were looking for a short candidate the securities with a negative number would be a consideration.

If you want to see the spreadsheet that drives the chart, click here:

Quality of Earnings Summary Spreadsheet

Our next step is to do some value analysis.  I just think it is common sense not to overpay for a stock.  When we over pay, we are letting our emotions get involved - objectivity is definitely a good discipline to develop when investing.  I think I could trace at least 70% of my investing errors to a loss of objectivity.

Besides that, the greater the difference between the price and the value of the security, the greater our risk.   I don't like excessive risk, I like to sleep well at night, which is why I like pessimistic markets, unfashionable sectors, and undervalued securities.

*To sum all of the ratings, I created a new spreadsheet and used the "importrange" feature to collect the rating for each measure.

Friday, May 11, 2012

Investment Analysis: Selling and Administration Expenses

This is the last of the quality of earnings factors that I look at.  Just for complete disclosure, Lev & Thiagarajan have six others.  I'll do a brief post on those to explain them and why I choose not to use them at another time.

This signal is similar to the last one we looked at, "Gross Margin".  Many S&A costs are fixed in the short term and a disproportionate changes relative to sales are rich in information.  We look at the percentage changes and the formula is:

% change in sales - % change in S&A.

If the result is negative, it is a negative signal, if it is positive, it is a positive signal.

In Verdasis, we set up an analysis template that has four elements:
  • Total Revenue, Y
  • Total Revenue, Y-1
  • Selling/General/Admin Expenses, Y
  • Selling/General/Admin Expenses, Y-1
If you need more how-to, we have a video tutorial here.  The third one shows how to set up templates.

(I'll just also point out that once you've set up the templates, you can use them again and again on different portfolios.  We're also playing around with different ideas to make the investment analysis process faster with per-fabricated ratios - some users will set up their own propitiatory ones and others will be available for all users for a fee.) 

Once the information is exported to the spreadsheet, calculate the percentage changes and take the difference.  I am using a 5% band around zero to remove the small changes as I did in Gross Margin.  If there is missing data, for example one of the stocks is missing the S&A information and I got the "dividing by zero" warning, I manually enter a "zero" for the final rating.

You can see the spreadsheet here.

OK, exciting times!  All done the quality of earnings analysis and next post I'll bring it all together by summing the ratings.  Hopefully you are starting to get a sense of how bringing this financial statement data into context gives us true, meaningful insight into these companies.  This stuff is a lot deeper than most of the everyday common ratios that we can easily find on financial web-sites and in the press.

But the proof will be in the pudding - once we're done (all done, there is still some more analysis we have to do, this is just the start) I'm going to take a position and we'll see how the pick performs vis a vis the rest of the group and the market.

Thank you for reading, have a great weekend!

Sunday, May 6, 2012

Investment Analysis: Gross Margin, Part 2


As per my last post, I decided to exclude variances that are within a certain threshold.  I decided on a "+-5%" band, so that only securities with % change in Gross Margin - % change in Sales less than -5% earned a negative one rating and securities with a greater than 5% difference earned a positive rating.

I did two "if" formulas in order to reflect this:
and then summed the two together to get the "Final Rating".

**It seems to me that it should be formulatically possible to just do it in one logic test, but alas, Google docs and excel both defeat me.  If YOU know how to do it, I'd appreciate the enlightenment. 

To access the spreadsheet, click here.

We have one more quality of earnings indicator, selling and administration expenses, and then we'll take a look at the full Q of E picture.  I will post the S&A analysis by the end of the week.

Thank you for reading!

Thursday, May 3, 2012

Investment Analysis: Gross Margin

Today I'm covering the quality of earnings indicator, "Gross Margin."  

The premise behind this marker is that disproportionate changes relative to sales are informative.  According to Lev, Thiagarajan and presumably many analysts, gross margin is a better-than-earnings figure for determining the relationship between a firm's input and output prices.  This price/cost ratio reflects interesting underlying factors such as the intensity of competition and the degree of operating leverage.

This measure takes the difference between the percentage change in sales and the percentage change in gross margin:

 % change in gm - % change in sales

As I mentioned above, it is the disproportionate changes which are informative.  L & T specifically state that a larger decrease in the gross margin relative to a decrease in sales is a negative sign.

Thus, in the above example, the formula would yield a negative number.

We would also get a negative value if the % change in gm increased, but the % change sales increased more.  

We'll get a positive value when there is a larger increase in the gross margin than in sales.  We'll also get a positive value when there is a smaller decline in the gross margin when sales also decrease.

If this isn't clear, let me discuss this for a moment in business terms.  The formula for gross margin is:

(Sales - Cost of Goods Sold) / Sales

The cost of goods sold are the inputs that are going to track very closely with the actual sales made.  For example, if you make nails, you cost of goods sold will be the raw materials, steel, and the direct labour.  If your sales go down, you need less inputs and your cost of goods sold go down. The reverse happens when your sales go up.  So the normal situation is a tight correlation between sales and the cost of goods sold.

When the situation deviates from the norm it can indicate either that efficiencies have been lost or they've been gained.  They're lost if the relationship moves apart.  They're gained if they move tighter together.

We capture this "movement" in the formula above.

I'm going to do the actual investment analysis tomorrow.  There is another nuance that I want to mention with this particular measure that isn't discussed by L & T, but does concern me.  I think that either small deviations should be ignored (and given a rating of zero) by arbitrarily choosing a range (such as between -5% and +5%) OR the analyst should benchmark what is "normal" for the company and then fluctuations outside that range be rated appropriately.  It is something to consider and when we build the actual financial model on this indicator we can make some judgments.

Thank you for reading, and I'll be back tomorrow.

Tuesday, May 1, 2012

Investment Analysis: Capital Expenditure

It's been longer than anticipated between posts.  I got busy with other things, particularly the launch of our new alpha calculator.  We'll take advantage of it once this analysis is complete and the best investing option (if any) becomes apparent.  I'm also going to dedicate a post to describing the alpha calculator (which I debated calling the "alphalator" when I was feeling rather silly) once we get further down the road on this analysis.

This next factor is similar to the R&D calculation and seeks to uncover the same kind of information - how much is the company investing in staying competitive?

Capital expenditures have the potential of making the company more productive and so we consider it a good thing when these are greater than the industry average.  Another reason is that investment in capital items can indicate management confidence in future earnings.

I'm going to use the capital expenditures line item from the cash flow statement.  I think it is a nice, tidy alternative to figuring out the numbers from the balance sheet and getting involved in the non-cash, highly subjective area of amortization.

For those of you not familiar with cash flow statements, a negative number demonstrates cash out of the company, whereas a positive number indicates cash into the company.  This number should usually be negative; if it was positive it would indicate that the company was liquifying its assets.

Here is what we need to do:

  1. Create an analysis template in Verdasis with two data columns: Capital Expenditure, Y and Capital Expenditures, Y-1.  
  2. In the portfolios section, apply the analysis template to the "US Oil & Gas, Integrated" portfolio by clicking the "Analyze" button beside that portfolio in the left hand menu bar.
  3. Export to Google Docs or Excel.
  4. On the spreadsheet I calculate the industry average for both Y and Y-1 at the bottom of those two columns.  I use the following formula:
  5. I calculate the industry growth (or decline) with this formula:
  6. I repeat the above growth/decline formula for each company,
  7. I take the difference between the company's growth and the industry average with this formula:
  8. Finally, each value gets a rating.  If the number is positive, they get a "1", if expenditures are less than the industry average they get a "-1".  I use this formula:
Note to step 8.  Dividing by zero of course give us a "#DIV/0!" answer.  I just let it be until the rating, and then I manually put in a negative 1.

To see the spreadsheet Click Here.

 Thank you for reading!  The next post will be on Gross Margin.  A cliff hanger, I know, but you'll just have to wait until Thursday, May 3, 2012 to find out what happens next.