The Magic Tricks To Finding Great Stocks
Stock screeners are a dime a dozen.
A stock screener is simply a filter that takes the entire universe of stocks (usually the NYSE and NASDAQ), and compares each stock against a static set of criteria, such as "is it below this P/E ratio?" or "is the market cap above a certain minimum threshold?".
Screening is a good place to start. By applying basic value, growth, or momentum criteria, you can quickly find investment candidates that are attractive on a numerical basis.
But there is even more we can do! Today, I want to show you what and how we add some "magic tricks" to turn simple screening strategies into our market-beating "Spells" to find great investment opportunities.
The Problems With Screening Alone
Like I mentioned, screening is a great place to start. But there are several issues that can make stock screeners difficult or incomplete tools for finding stocks:
- Complexity. Even intermediate investors can be intimidated by the dozens of potential criteria that are provided by many screening tools. While powerful, this litany of options can be confusing and make it more difficult for users to find what they are looking for.
- Flawed Statistics. Most of the screening statistics offered by screening tools are very "old school", such as price-to-earnings ratio or return on equity. While these are fine, recent studies have found much better alternative statistics that incorporate additional company data to provide a better picture of how cheap or efficient a company REALLY is.
- Lack of Context. So you've run your screen and you have 150 results. Ok. But of these 150, which are most deserving of your attention? If you screened on only one statistic it is easy enough to sort, but what if your screen had 3, or 4, or more criteria? Straight screen filters don't provide much context as to which stocks are most attractive based on your criteria.
The "Magic Tricks" To Fixing These Problems
Thinking about these challenges with stock screeners, we wanted to come up with some "magic tricks" to help alleviate them - with a big assist from the methodologies invented by Joel Greenblatt for Magic Formula Investing. The result are what we call "stock spells". Here they are!
For complexity, we whittle stock spells down to just 2 criteria. For the Magic Recipe Spell, those are earnings yield and return on tangible capital (more on these later), to create a "value and quality" list. The Deep Value Spell, we focus on earnings yield and free cash flow yield, focusing SOLELY on value based on real earnings and cash flows. For the Quality Growth Spell, the criteria are 3 year revenue growth and cash return on total capital - a "growth and quality" list. Finally, the Star List Spell is a screening + ranking hybrid looking for some special cases.
We understand complexity is attractive to many investors as well, so the Spell Caster tool allows you to create a custom screening + ranking list however you want. Smaller stocks, bigger lists, only retail stocks? You can do any or all of those.
Fixing Flawed Statistics
We just finished an entire series on the new, advanced stock statistics to replace the old stalwarts of P/E, return on equity, and so forth. By using these, we are able to incorporate more data (like a company's financial health) while removing misleading factors like one-time impairment charges or tax credits that often skew traditional screens.
Fixing Lack of Context
We fix lack of context by ranking stocks against each other. The result of this is that it gives you an ordered list of which stocks are "best" given your desired criteria.
Let's do a quick example to show how this works. Say we wanted to rank 5 popular tech stocks against each other, looking for the combination of best value (earnings yield) and most efficiency (return on total capital). Here are each of the 5 stocks, with their respective statistics (as of 4/8/2016):
Apple (AAPL): Earnings yield 13.9%, return on total capital 139.6%
Alphabet/Google (GOOG): Earnings yield 4.2%, return on total capital 33.6%
Facebook (FB): Earnings yield 2.0%, return on total capital 21.6%
Microsoft (MSFT): Earnings yield 6.4%, return on total capital 55.1%
Cisco (CSCO): Earnings yield 11.0%, return on total capital 31.1%
First we rank them by earnings yield, in a descending fashion, and assign a earnings yield ranking score (EYR):AAPL 13.9% (EYR = 1)
CSCO 11.0% (EYR = 2)
MSFT 6.4% (EYR = 3)
GOOG 4.2% (EYR = 4)
FB 2.0% (EYR = 5)
Good. Now we do the same with return on total capital (ROICR):AAPL 139.6% (ROICR = 1)
MSFT 55.1% (ROICR = 2)
GOOG 33.6% (ROICR = 3)
CSCO 31.1% (ROICR = 4)
FB 21.6% (ROICR = 5)
Now add the two scores together to get a composite rank, and order the stocks by their composite rank in an ascending fashion. Voila, the "universe" of our 5 stocks ranked by our two criteria!AAPL (composite score = 2)
MSFT (composite score = 5)
CSCO (composite score = 6)
GOOG (composite score = 7)
FB (composite score = 10)
Incidentially, you can do this exact exercise using our Portfolio Ranker tool!
Wrapping It Up
Stock screeners are useful, but have their problems too. By using the "magic tricks" of advanced statistics, keeping it simple, and ranking results, we can generate lists ("spells") of attractive, market beating stocks. See all of our spells and tools by subscribing today!
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