In Part 1 I introduced you to my overall approach to picking stocks to include in my dividend growth-oriented portfolio (with a dash of speculation), how to rank each of the 15 metrics that I use to help guide me in my stock purchase decision making, and the details of 11 of those metrics and how to find or calculate them. In today's article, I'll wrap up the details of the remaining 4 metrics, how to aggregate them into a single value that can then be ranked, and what using this method has meant to my burgeoning portfolio.
As a recap, here are the 30 stocks that I'm currently tracking on my watchlist, to which I've applied My Mad Method:
Alliance Resource Partners, L.P.
Annaly Capital Mgmt
Compass Minerals Int'l, Inc
Cheniere Energy Partners, L.P.
General Electric Company
Johnson & Johnson
Lockheed Martin Corp
MV Oil Trust
National Grid, plc
National Presto Industries
Philip Morris International
Procter & Gamble
Wells Fargo & Co
The Details of the Metrics, Continued…
The following are the remaining 4 metrics that I use in My Mad Method of picking stocks to buy, and how I calculate and rank each of them. Most of these metrics and/or their components can be easily found on most popular financial websites, although some of them are a bit trickier than others to track down.
12 - PEG Ratio - This you want to be low, so rank in descending order. This can be tricky to find on your favorite financial website, so if it's not handy you can calculate it by dividing the P/E ratio by the rate (as a %, not in decimal form, e.g. 90 not .9) at which you think earnings will grow over the next few years. The earnings growth rate should be the average of all of the Wall Street analysts' predictions who are covering that stock.
13 - Graham Number Ratio - Named for Benjamin Graham, the Graham Number is the square root of the company's Earnings Per Share, or EPS, times Book Value Per Share, or BVPS, times the constant 22.5, and is used as one way to estimate the fair value of a stock. This can be a little tricky to calculate, as you don't want to use an EPS that is negative or zero; I've also found it somewhat difficult to find Book Value Per Share for all of the stocks I want to rate. As a result, when calculating the Graham Number, or GN, I first test to see if EPS is greater than zero, and if it is then I calculate the GN, and if not then I use the Current Share Price of the stock, or CSP. The formula employed, then, is:
=IF( (EPS > 0), (SQRT(22.5 * EPS * BVPS)), CSP )
However, the Graham Number by itself doesn't tell me anything about the stock vis-à-vis the other stocks I'm ranking, so next I take the ratio of the Current Share Price divided by the stock's Graham Number that I just calculated. This is the Graham Number Ratio, the number I want to rank. However, once again I have to test to make sure the Graham Number isn't zero, or else I'll end up with an error, which will prevent the entire ranking from being calculated properly. If the calculated Graham Number is zero, I default this ratio to 2 as a way of lumping these stocks near the bottom of the ranking of this ratio. So, continuing this example, the formula for the Graham Number Ratio is:
=IF( (GN>0), (CSP / GN), 2 )
This resulting ratio is then ranked in descending order, indicating that stocks whose Graham Number (fair value) is higher than their current price are ranked more favorably than those whose Graham Number is close to or lower than their current price.
14 - The BMW Method Root Mean Square (RMS) - No, this doesn't refer to the luxury car company. This metric, the Root Mean Square, or RMS, comes from a method of evaluating a stock's current price against its average Compound Annual Growth Rate, or CAGR, over a long period of time, preferably 30 years if there's enough data for that stock. The BMW Method is named for a chap who goes by the username of "BuildMWell" (hence, "BMW"), and there are several websites devoted to the concept, tools and data to allow anyone to use this approach. There is also simple and benign freeware that you can download to use to chart a stock's average CAGR, RMS and Return Factor (or RF, see next metric).
The BMW Method RMS is simply the number of standard deviations that a stock's current price is away from its average CAGR. For example, if company XYZ's current RMS were -2.00, then its current price is 2 standard deviations below the average CAGR of its price, an indication that it is underpriced compared to its price's historical CAGR, whereas if its RMS were 1.75 then its current price is 1.75 standard deviations above the average CAGR of its price.
The further below its average CAGR a stock's price is, the more desirable it is for picking up and adding to your portfolio, while the higher above its average CAGR, the more likely that it is overpriced and could be ready for a pullback correction. Of course, there's no guarantee that a stock that has a negative RMS will go up, just as there's no guarantee that a stock with a low P/E will see its price go up, either.
It's just a relative metric that can be used to evaluate a group of stocks against each other in terms of which are currently underpriced (or overpriced) based on historical data. In the case of My Mad Method, I'm looking for stocks with lower numbers, the lower the better, so rank this metric in descending order.
15 - The BMW Method Return Factor - The last metric that I use in my approach also comes from the BMW Method, this time something known as the Return Factor, or RF. The RF is an indication of how much of a return on your investment you might realize, theoretically, should a stock that is off its average CAGR return to a price that approaches or equals its average CAGR. The higher the RF, the more likely that you will get a higher return on your investment if and when the stock's price reverts to its historically average CAGR.
Any number above 1.00 indicates a theoretical positive return on your investment should the current price of the stock revert to its average CAGR, and a number less than 1.00 indicates that you're likely to lose money on that investment, theoretically, if you purchased it at the time its RF was less than 1.00.
The BMW Method theorizes that a well run company with strong products, fundamentals and management, and a good economic moat, whose stock is trading below its average CAGR, should see its stock price return to its average CAGR over time. Since we want higher numbers here rather than lower ones, rank this metric in ascending order.
Putting It All Together
Now that you've got all these metrics gathered up and ranked, it's time to aggregate them and rank that result. Calculate the average of all 15 of the rankings of the metrics, not the metrics themselves. Then, rank this resultant aggregate number in descending order. The results, given the stocks I listed in yesterday's article, come out looking like this:
All things being equal, this method will clearly show you what, based on your own set of metrics for evaluating a set of stocks, should likely be your #1 choice for the next stock to purchase; and #2, and #3, and so on.
However - and this is a big "however" - don't let this be an automated means of pulling the trigger on your next stock purchase! This method isn't foolproof; all it does is distill down all the other metrics by which you've decided you want to evaluate a set of stocks into a single number to show you how they stack up against each other. You may find that what ends up being ranked #1 doesn't pass some other criteria, not the least of which is what I refer to as my "Gut Check." Due diligence still applies!
These results above are telling me that Medtronic is my #1 choice; however, I recently purchased a block of Medtronic (although it's still on my watchlist), and it "only" yields 2.58%, compared to #2 on the list, Alliance Resource Partners, which yields a juicier 6.55%, and ARLP is only a fraction behind MDT in my ranking.
The coal industry has been taking a beating for a variety of reasons in the USA, but China and India are desperate for coal. If I end up deciding that King Coal is doomed, I could go to my #3 choice, Hatteras Financial, which is a mortgage Real Estate Investment Trust, or mRIET, to fatten that segment of my portfolio a bit more and diversify from Annaly Capital Management, another mREIT that I already own, and which ended up raking just a hair behind HTS.
Or, if I was feeling like I needed to add a bit more speculative risk to my portfolio for a possible big return, I could go with Ebix, Inc., which scored the same as NLY. So, there's more work for me to do here before I make a decision on which stock to buy next, but now I've got my big watchlist of 30 narrowed down to a handful that I can truly focus on to make my final decision.
Does it Really Work?
Have all my top picks gone on to beat the market? Well, not yet; some have done very well, and others not as well (yet), but in general, I'm pleased with this method, and trust it to help me narrow down what would otherwise be an unwieldy list of potential stocks to buy, a list that is otherwise too big and confusing to handle without employing this method.
Some of the stocks that I've bought based on this method that have done well so far include Abbott Laboratories (ABT) and Microsoft (MSFT). Others that have dropped since I acquired them, but which ranked very high and still hold long-term promise, include Corning (GLW) and Medtronic. Still others that I've recently added to my portfolio fell somewhere in the middle of the ranking pack when I was considering them, but I picked them up for other reasons, such as Cirrus Logic (CRUS), whose audio chips have become a standard component of the last several generations of the iPhone and iPad, and as a result has had its share price dragged up along with Apple's amazing ascent.
Likewise, I chose MAKO Surgical to add to my portfolio a few months back as a purely speculative play, even though they ranked rather poorly using this method, because I like their RIO knee and hip replacement robotic system and the recurring revenue that it can generate, which I feel bodes well for the long term. (MAKO is currently up 12.5% from when I bought it; so far, so good.)
I've also found it useful to employ this method to keep track of and rank the stocks that I have already purchased vis-à-vis each other as a means of quickly, visually identifying which stocks are performing well and which ones are performing poorly. In that case, I use the same metrics that I've described in this series, including the BMW Method numbers. Those help bring to light stocks that have dropped in price to the point where I might want to back up the truck and load up on some more, as well as those whose prices have risen to the point that it might not be a bad idea to take my profits, if my cost basis is low enough.
In addition, I add other metrics to these 15 for monitoring my portfolio, including but not limited to whether a stock's current price is up or down from when I bought it, and by how much, and whether I've received any dividends from that company this year, and how much.
I hope you have found this series useful. Please leave a comment or any questions you have below.