Wednesday, 3 June 2015

The Intelligent Investor

Fast forward to 2014.

After years of trying my hand at trading (unsuccessfully), reading about trading, studying charts, subscribing to charting services, creating my own charts, trying to interpret what the heck I had just charted, and driving myself crazy throughout, I put it all aside and picked up The Intelligent Investor by Benjamin Graham annotated by Jason Zweig.

I didn't just read it once, I read it twice over, and I'll probably read it twice over again in order to constantly remind myself of the lessons therein.  <If you have not read The Intelligent Investor and you are currently active in the market, I highly recommend reading it. It will set you back $20, about the cost of one round trip trade, and it will be the best $20 you ever spend>.  And then, something clicked.

I realized that I had spent years upon years out of focus.  I was focusing on the arbitrariness of price in a vaccuum by focusing on a plot of price at a point in time, without having the faintest clue about the underlying businesses of the company's shares I was trading!

I certainly had the background and ability to delve into financial statements and dissect them every which way, but I was taking the easy route out and focusing only on price.

Now don't get me wrong, there are some hugely successful chart traders out there, and I have no doubt that building a successful trading system predicated on trading price (or indicators derived from price) is possible.  For me, this doesn't fit my personality, and I think that understanding your own personality in the context of investing is critical.  If you're trying to build wealth by taking action that is contra to your own beliefs/investing ideology, in my opinion, over time, this will translate into destruction instead of accumulation of wealth.  This ties back to my comment regarding putting it all together.

In the summer of 2014, I picked up a copy of Barron's, and inside there was fantastic article on Joel Geenblatt, who coined the term "Magic Formula Investing".  Joel Greenblatt is an adjunct professor of finance at Columbia Business School, and a professional money manager.  In 2005, Greenblatt wrote a book called The Little Book That Beats the Market, which is now considered to be a modern day finance classic.  I ran out and bought The Little Book That Still Beats The Market and read it cover to cover in one day.

You can find the original Barron's article here:

I became intrigued with the idea that a methodology as simple as buying a diversified basket of good (high return on capital) and cheap (high earnings yield) companies could actually produce investment returns greater than the market return (S&P 500).

Greenblatt even has a website called Magic Formula Investing which uses the principles outlined in the Little Book That Beats the Market to generate a list of stocks which, relative to all other stocks in the rankable stock universe (i.e., US stocks), score best on the combined merits of good (high return on capital) and cheap (high earnings yield).

Anyone can join the website and run the screen using different market cap paramaters.  Plug in a market cap of $50M or more and the website will crunch all the numbers behind the scenes and produce a list of the 50 best relatively ranked good and cheap companies.

Here's the rub:  I couldn't bring myself to just blindly trust the results of an unknown algorithm working behind the scenes without auditing the results myself.  So I built my own database.

The premise underpinning what constitutes good (high return on capital) and cheap (high earnings yield) is fairly straightforward.

According to Greenblatt's teachings:

Good (High return on capital) is measured as:

Earnings before interest and taxes (EBIT)  / capital

Where, capital is equal to:

Net working capital + net property, plant and equipment.

<Note that for the purposes of Greenblatt's capital calculation, he excludes goodwill and intangibles.  I'm not sure I agree with this adjustment fully as certain types of companies carry limited or unlimited life intangibles which are essential to their operation.  For example, assume a fictitious company carries an exclusive license to carry out a particular service classified as a limited life intangible on the company's balance sheet, as the company had to pay a cost upfront to obtain license exclusivity.  Further assume that in the absence of obtaining this license exclusivity, it's current operations would be materially different.  As a result, this exclusive right could be viewed as a long lived capital asset.  My thoughts are that the net amortized (or unamortized) cost should be reflected in the capital calculation, which would reduce the return on capital and change Greenblatt's ranking.

Note also that the flipside of the argument here is that dominant companies which spend a substantial amount on R&D, marketing, advertising, or overall maintenance of their franchise/moat should actually report higher EBIT.  Their EBIT in theory is lower by the amount these companies spend each year on sustaining their competitive advantage.  But the accounting rules being what they are, this type of ongoing moat-maintenance spend must be expensed, and it's up to us investors to figure out what the true EBIT should be given a company's competitive position in the marketplace.>


Cheap (High earnings yield) is measured as:

Earnings before interest and taxes (EBIT) / Enterprise Value

Why Enterprise Value and not Market Cap?  Because, per Greenblatt, the ratio of earnings before interest and taxes takes all perspectives into account (both bondholders and shareholders) and is a pre-leverage measure of earnings power.  Net income is a post leverage measure of earnings power and should not theoretically be compared across companies with different leverage in their capital structure. When focusing on the value of the firm to all stakeholders, Enterprise Value should be the correct measure of value because it includes net debt.  Overall, Greenblatt's earnings yield appears to be a cleaner and more comparable measure across companies vs. ROE which can be skewed awkwardly by the effects of leverage.

I'm guessing that the algorithm at runs a screener that ranks a database of stocks combining the best elements of both good and cheap.  My understanding is that the database is updated quarterly behind the scenes.  For example, if the database contains 5,000 stocks, it's not good enough for a stock to just be cheap.  There are plenty of cheap stocks at any one point in time.  The stock must be both good (high return on capital) and cheap (high earnings yield), and unless the stock shows a strong combination of both elements relative to every other rankable stock in the database, it won't end up being highly ranked overeall.

Greenblatt proposes that buying a diversifed basket (between 20 and 30) of top ranked good and cheap stocks will beat the market, and he's probably correct.

My issue with this approach is twofold:

1) It's akin to throwing darts at a basket of 20 to 30 stocks, some of which are deservedly cheap for good reason.  I'm not saying that throwing darts is a bad approach.  In fact, I'd wager that a good percentage of professional participants make their living throwing darts (they either don't see it this way, or they do and just don't admit it).  At least by using a combination of good and cheap, the odds of some of the darts finding their mark and producing excess returns might be skewed in an investors favour.  The diversification factor of holding 30 good and cheap stocks insulates against any one (or a small number) of the darts ending up being cigar butts.

2) The approach likely requires annual monitoring and turnover.  This may not work for the passive investor who wants to accumulate a diversified portfolio of stable dividend growers over time and leave the porftolio on autopilot.  It's a given that a portion of the darts in the portfolio under this approach will remain cheap and will end up being cigar butts.  The approach thus requires at least annual weeding, and quite possibly 100% annual turnover if the subsequent year's screen re-ranks an entirely new list of good and cheap stocks.

So where does this leave the investor looking to build a stable portfolio, which can grow on autopilot, and which requires minimal tinkering over time?

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