Review – Common Stocks And Uncommon Profits

Common Stocks and Uncommon Profits: And other writings by Philip A. Fisher

by Philip A. Fisher, published 1996, 2003

Stock market investors who have studied Warren Buffett in detail know that he has cited two “philosophers” of investment theory more than anyone else in being influential in the formation of his own investment approach: Benjamin Graham and Phil Fisher. Graham represents the cautious, conservative, balance sheet-driven Buffett, while Fisher represents the future-oriented, growth-focused, income statement-driven Buffett. If you ask Buffett, while Graham got him started and taught him key lessons in risk management (Margin of Safety and the Mr. Market metaphor), Fisher was the thinker who proved to have the biggest impact in both time and total dollars accumulated. Buffett today, whether by choice or by default due to his massive scale, is primarily a Phil Fisher-style investor.

And yet, in my own investment study and practice, I have dwelled deeply on Graham and did little if anything with Fisher. I tried to read Fisher’s book years ago when I was first starting out and threw my hands up in disgust. It seemed too qualitative, too abstract and frankly for a person of my disposition, too hopeful about the future and the endless parade of growth we’ve witnessed in the markets for several decades since the early 1980s. Surely there would be a time where the Fisher folks would hang their heads in shame and the Grahamites would rise again in the fires of oblivion! After all, “Many shall be restored that are now fallen and many shall fall that are now in honor.”

As my professional career wore on, however, I found there was less and less I could do with Graham and more and more of what Fisher had said that made sense. And if you’re in business, you can’t help but be growth oriented– buying cheap balance sheets isn’t really the way the world works for the private investor. So, I decided it was time to take another look at Fisher’s book and see what I could derive from it as an “older and wiser” fellow. What follows is a review of Part I of the book; I plan to read and review Part II, which is a collection of essays entitled “The Conservative Investor Sleeps Well At Night”, separately.

Keep Your Eye On The Future

One thing I noticed right away is the consistent theme of future-orientation throughout Fisher’s book. Whereas balance sheets and the Graham approach look at what has happened and what is, Fisher is always emphasizing a technique that involves conceptualizing the state of the future. For example, in the Preface he states that one of the most significant influences on his own investment results and those of other successful investors he was aware of was,

the need for patience if big profits are to be made from investment.

“Patience” is a reference to time preference, and time preference implies an ability to envision future states and how they differ from the present and therein see the arbitrage available between the two states. The other key he mentions is being a contrarian in the market place, which sounds a lot to me like the lesson of Mr. Market.

Fisher also says that market timing is not a necessary ingredient for long-term investment success,

These opportunities did not require purchasing on a particular day at the bottom of a great panic. The shares of these companies were available year after year at prices that were to make this kind of profit possible.

While he cites the structural inflationary dynamic of the modern US economy and seems to suggest the federal government’s commitment to responding to business cycle depressions with fiscal stimulus puts some kind of ultimate floor under US public company earnings (unlike in Ben Graham’s time where large companies actually faced the threat of extinction if they were caught overextended in the wrong part of the cycle, Fisher suggests the federal government stands ready to create conditions through which they can extend their debt liabilities and soldier on), he says that the name of the game over the long-term is to find companies with remarkable upside potential which are, regardless of size, managed by a determined group of people who have a unique ability to envision this potential and create and execute a plan for realizing it. In other words, the problem of investing is recognizing strong, determined management teams for what they are, that is, choosing superior business organizations in industries with long runways.

Getting the Goods: The Scuttlebutt Approach

People who know about Fisher typically identify him with the “scuttlebutt approach”. Fisher says scuttlebutt can be generated from:

• competitors
• vendors
• customers
• research scientists in universities, governments and competitive companies
• trade association executives
• former employees (with caveats)

Before one can do the scuttlebutt, however, one has to know where to look. Fisher says that “doing these things [scuttlebutt] takes a great deal of time, as well as skill and alertness […] I strongly doubt that [some easy, quick way] exists.” So, you don’t want to waste your time by going to all the trouble for the wrong idea. He says that 4/5 of his best ideas and 5/6 of the total gains generated over time that he could identify originated as ideas he gleaned from other talented investors first, which he subsequently investigated himself and found they fit the bill. Now, this is not the same thing as saying 4/5 ideas he got from others were worth investing in– the proportion of “good” ideas of the “total” he heard about is probably quite low, but the point again is not quantitative, but qualitative. He’s talking about where to fish for ideas, not how successful this source was.

When I thought about this section, I realized the modern day equivalent was investment bloggers. There are many out there, and while some are utter shit (why does this guy keep kidding himself?) some are quite amazing as thinkers, business analysts and generators of potential ideas. I have too many personal examples of my own here to make mention of them all. But I really liked this idea, cultivating a list of outstanding investment bloggers and using that as your primary jumping off point for finding great companies. The only problem for me in this regard is most of my blogroll are “value guys” that are digging in the trash bins (as my old boss sarcastically put it), whereas to find a Fisher-style company I would need to find a different kind of blogger interested in different kind of companies. But that’s a great to-do item for me to work on in this regard and should prove to be highly educational to boot!

So, assuming you’ve got a top notch idea, what’s next? Fisher is pretty clear here: do not conduct an exhaustive study of the company in question just yet. (In other words, don’t do this just yet, though I loved SoH’s follow-up where he explained what kind of things would get him to do that.) What he does do is worth quoting at length:

glance over the balance sheet to determine the general nature of the capitalization and financial position […] I will read with care those parts covering breakdown of total sales by product lines, competition, degree of officer or other major ownership of common stock […] all earning statement figures throwing light on depreciation, profit margins, extent of research activity, and abnormal or non-recurring costs in prior years’ operations

Then, if you like what you see, conduct your scuttlebutt, because,

only by having what “scuttlebutt” can give you before you approach management, can you know what you should attempt to learn when you visit a company […] never visit the management of a company [you are] considering for investment until [you have] first gathered together at least 50 per cent of all knowledge [you] would need to make the investment

This is the part that really gives a lot of investors pause about Phil Fisher’s approach, including me. Can you really do scuttlebutt, as he envisions it, in the modern era? Can the average investor get the ear of management? Does any of this stuff still apply?

First, some skepticism. Buffett’s biographer Alice Schroeder has said in interviews that much of what made Buffett successful early on in his career is now illegal and would amount to insider trading. The famous conversation with the GEICO chief is one of many that come to mind. This was classic scuttlebutt, and it worked amazingly well for Buffett. And even if it wasn’t illegal, most individual investors are so insignificant to a company’s capital base that they can’t expect nor will they ever receive the ear of management (unless they specialize in microcap companies, but even then management may be disinterested in them, even with significant stakes in their company!) And, assuming they DO somehow get management’s ear, they aren’t liable to learn much of value or interest specifically because most managements today are not only intellectually and politically sophisticated, but legally sophisticated and they are well aware that if they say anything more general than “We feel positive about our company” they’re liable to exposure under Reg FD. This seems like a dead end.

But let me try to tease the idea out a little more optimistically. Managements do provide guidance and color commentary on quarterly earnings calls, and if you are already dealing with a trustworthy, capable management (according to the 15 points outlined below), then there is opportunity to read between the lines here, even while acknowledging that there are many other people doing the same with this info. And people who do get managements’ ear are professional analysts employed by major banks. Again, lots of people read these reports, but there is some info here and it adds color and sometimes offers some “between the lines” information some might miss. And while the information you can get from any one company may be limited, by performing this analysis on several related companies you might be able to fill in some gaps here and there to the point that you can get a pretty fair picture of how the target company stacks up in various ways.

I hesitate a little, but I think the approach can be simulated to a fair degree even today. It’s still hard work. It can’t be done completely, or perhaps as Fisher imagined it. But I think it can be done. And it still comes down to the fact that, even with all this info that is out there, few will actually get this up close and personal with it. So, call it an elbow-grease edge.

After all,

Is it either logical or reasonable that anyone could do this with an effort no harder than reading a few simply worded brokers’ free circulars in the comfort of an armchair one evening a week? […] great effort combined with ability and enriched by both judgment and vision [are the keys to unlocking these great investing opportunities] they cannot be found without hard work and they cannot be found every day.

The Fisher 15

Fisher also is known for his famous 15 item investment checklist, a checklist which at heart searches for the competitive advantage of the business in question as rooted in the capability of its management team to recognize markets, develop products and plans for exploiting them, execute a sales assault and finally keep everything bundled together along the way while being honest business partners to the minority investors in the company. Here was Fisher’s 15 point checklist for identifying companies that were highly likely to experience massive growth over decades:

1. Does the company have sufficient market scale to grow sales for years?
2. Is management determined to expand the market by developing new products and services to continue increasing sales?
3. How effective is the firm’s R&D spending relative to its size?
4. Is the sales organization above-average?
5. Does the company have a strong profit margin?
6. What is being done to maintain or improve margins? (special emphasis on probable future margins)
7. What is the company’s relationship with employees?
8. What is the company’s relationship with its executives?
9. Is the management team experienced and talented?
10. How strong is the company’s cost and accounting controls? (assume they’re okay unless you find evidence they are not)
11. Are there industry specific indications that point to a competitive advantage?
12. Is the company focused on short or long-term profits?
13. Can the company grow with its own capital or will it have to continually increase leverage or dilute shareholders to do it?
14. Does the management share info even when business is going poorly?
15. Is the integrity of the management beyond reproach? (never seriously consider an investment where this is in question)

What I found interesting about these questions is they’re not just good as an investment checklist, but as an operational checklist for a corporate manager. If you can run down this list and find things to work on, you probably have defined your best business opportunities right there.

In the chapter “What to Buy: Applying This to Your Own Needs”, Fisher attempts to philosophically explore the value of the growth company approach. First, he tries to dispel the myth that this approach is only going to serve

an introverted, bookish individual with an accounting-type mind. This scholastic-like investment expert would sit all day in undisturbed isolation poring over vast quantities of balance sheets, corporate earning statements and trade statistics.

Now, this is ironic because this is actually exactly how Buffett is described, and describes himself. But Fisher insists it is not true because the person who is good at spotting growth stocks is not quantitatively-minded but qualitatively-minded; the quantitative person often walks into value traps which look good statistically but have a glaring flaw in the model, whereas it is the qualitative person who has enough creative thinking power to see the brilliant future for the company in question that will exist but does not quite yet, a future which they are able to see by assembling the known qualitative facts into a decisive narrative of unimpeded growth.

Once a person can spot growth opportunities, they quantitatively have to believe in the strategy because

the reason why growth stocks do so much better is that they seem to show gains in value in the hundreds of percent each decade. In contrast, it is an unusual bargain that is as much as 50 per cent undervalued. The cumulative effect of this simple arithmetic should be obvious.

And indeed, it is. While great growth stocks might be a rarer find, they return a lot more and over a longer period of time. To show equivalent returns, one would have to turnover many multiples of incredibly cheap bargain stocks. So this is the philosophical dilemma– fewer quality companies, fewer decisions, and less room for error in your decisions with greater return potential over time, or many bargains, many decisions, many opportunities to make mistakes but also less chance that any one is critical, with the concomitant result that your upside is limited so you must keep churning your portfolio to generate great long-term results.

Rather than being bookish and mathematically inclined (today we have spreadsheets for that stuff anyway), Fisher says that

the successful investor is usually an individual who is inherently interested in business problems. This results in his discussing such matters in a way that will arouse the interest of those from whom he is seeking data.

And this still jives with Buffett– it’s hard to imagine him boring his conversation partner.

Timing Is Everything?

So you’ve got a scoop on a hot stock, you run it through your checklist and you conduct thorough scuttlebutt-driven due diligence on it. When do you buy it, and why?

to produce close to the maximum profit […] some consideration must be given to timing

Oh no! “Timing”. So Fisher turns out to be a macro-driven market timer then, huh? “Blood in the streets”-panic kind of thing, right?

Wrong.

the economics which deal with forecasting business trends may be considered to be about as far along as was the science of chemistry during the days of alchemy in the Middle Ages.

So what kind of timing are we talking about then? To Fisher, the kind of timing that counts is individualistic, idiosyncratic and tied to what is being qualitatively derived from one’s scuttlebutt. Timing one’s purchases is not about market crashes in general, but in corporate missteps in particular. Fisher says:

the company into which the investor should be buying is the company which is doing things under the guidance of exceptionally able management. A few of these things are bound to fail. Others will from time to time produce unexpected troubles before they succeed. The investor should be thoroughly sure in his own mind that these troubles are temporary rather than permanent. Then if these troubles have produced a significant decline in the price of the affected stock and give promise of being solved in a matter of months rather than years, he will probably be on pretty safe ground in considering that this is a time when the stock may be bought.

He continues,

[the common denominator in several outstanding purchasing opportunities was that ] a worthwhile improvement in earnings is coming in the right sort of company, but that this particular increase in earnings has not yet produced an upward move in the price of that company’s shares

I think this example with Bank of America (which I could never replicate because I can’t see myself buying black boxes like this financial monstrosity) at Base Hit Investing is a really good practical example of the kind of individual company pessimism Phil Fisher would say you should try to bank on. (Duh duh chhhhh.)

He talks about macro-driven risk and says it should largely be ignored, with the caveat of the investor already having a substantial part of his total investment invested in years prior to some kind of obvious mania. He emphasizes,

He is making his bet upon something which he knows to be the case [a coming increase in earnings power for a specific company] rather than upon something about which he is largely guessing [the trend of the general economy]

and adds that if he makes a bad bet in terms of macro-dynamics, if he is right about the earnings picture it should give support to the stock price even in that environment.

He concludes,

the business cycle is but one of at least five powerful forces [along with] the trend of interest rates, the over-all government attitude toward investment and private enterprise [quoting this in January, 2017, one must wonder about the impact of Trump in terms of domestic regulation and taxation, and external trade affairs], the long-range trend to more and more inflation and — possibly most powerful of all — new inventions and techniques as they affect old industries.

Set all the crystal ball stuff aside– take meaningful action when you have meaningful information about specific companies.

Managing Risk

Fisher also gives some ideas about how to structure a portfolio of growth stocks to permit adequate diversification in light of the risk of making a mistake in one’s choices (“making at least an occasional investment mistake is inevitable even for the most skilled investor”). His example recommendation is:

• 5 A-type, established, large, conservative growth companies (20% each) -or-
• 10 B-type, medium, younger and more aggressive growth companies (10% each) -or-
• 20 C-type, small, young and extremely aggressive/unproven growth companies (5% each)

But it is not enough to simply have a certain number of different kinds of stocks, which would be a purely quantitative approach along the lines of Ben Graham’s famous dictums about diversification. Instead, Fisher’s approach is again highly qualitative, that is, context dependent– choices you make about balancing your portfolio with one type of stock require complimentary additions of other kinds of stocks that he deems to offset the inherent risks of each. We can see how Buffett was inspired in the construction of his early Buffett Partnership portfolio weightings here.

For example, he suggests that one A-type at 20% might be balanced off with 2 B-type at 10% each, or 6 C-type at 5% each balanced off against 1 A-type and 1 B-type. He extends the qualitative diversification to industry types and product line overlaps– you haven’t achieved diversification with 5 A-types that are all in the chemical industry, nor would you achieve diversification by having some A, B and C-types who happen to have competing product lines in some market or industry. For the purposes of constructing a portfolio, part of your exposure should be considered unitary in that regard. Other important factors include things like the breadth and depth of a company’s management, exposure to cyclical industries, etc. One might also find that one significant A-type holding has such broadly diversified product lines on its own that it represents substantially greater diversification than the 20% portfolio weighting it might represent on paper. (With regards to indexation as a strategy, this is why many critics say buying the S&P 500 is enough without buying “international stock indexes” as well, because a large portion of S&P 500 earnings is derived from international operations.)

While he promotes a modicum of diversification, “concentration” is clearly the watchword Fisher leans toward:

the disadvantage of having eggs in so many baskets [is] that a lot of the eggs do not end up in really attractive baskets, and it is impossible to keep watching all the baskets after the eggs get put into them […] own not the most, but the best […] a little bit of a great many can never be more than a poor substitute for a few of the outstanding.

Tortured egg basket metaphors aside (why on earth do people care what their egg baskets look like?!), Fisher is saying that the first mistake one can make is to spread your bets so thin that they don’t matter and you can’t efficiently manage them even if they did.

Aside from portfolio construction, another source of risk is the commission of errors of judgment.

when a mistake has been made in the original purchase and it becomes increasingly clear that the factual background of the particular company is, by a significant margin, less favorable than originally believed

one should sell their holdings, lick their wounds and move on. This needs to be done as soon as the error is recognized, no matter what the price may be:

More money has probably been lost by investors holding a stock they really did not want until they could “at least come out even” than from any other single reason. If to these actual losses are added the profits that might have been made through the proper reinvestment of these funds if such reinvestment had been made when the mistake was first realized, the cost of self-indulgence becomes truly tremendous.

Further,

Sales should always be made of the stock of a company which, because of changes resulting from the passage of time, no longer qualifies in regard to the fifteen points… to about the same degree it qualified at the time of purchase […] keep at all times in close contact with the affairs of companies whose shares are held.

One vogue amongst certain investors is to be continually churning the portfolio from old positions to the latest and greatest idea, with the assumption being that time has largely run its course on the earlier idea and the upside-basis of the new idea is so much larger that liquidity should be generated to get into the new one. Fisher advises only using new capital to pursue new ideas rather than giving in to this vanity because,

once a stock has been properly selected and has borne the test of time, it is only occasionally that there is any reason for selling it at all

The concept of “investment” implies committing one’s resources for long periods of time. You can’t emulate this kind of trading activity in the private market, which is a very strong indication that you should try to avoid this behavior in public markets. A particularly costly form of this error is introducing macro-market timing into one’s portfolio management, ie, this stock has had a big run up along with the rest of the market, things are getting heady, I will sell and get back in at a lower cost. I’ve done this myself, most recently with Nintendo ($NTDOY) and even earlier with Dreamworks ($DWA). Fisher says it’s a mistake:

postponing an attractive purchase because of fear of what the general market might do will, over the years, prove very costly […] if the growth rate is so good that in another ten years the company might well have quadrupled, is it really of such great concern whether at the moment the stock might or might not be 35 per cent overpriced? That which really matters is not to disturb a position that is going to be worth a great deal more later.

It plays to a logical fallacy that a company that has run up has “expended” its price momentum, while a company that has not had a run-up has something “due” to it. On the contrary, Fisher points out that many times the material facts about a company’s future earnings prospects change significantly over time from the original purchase, often to the good, such that even with a big run-up, even more is in the offing because the future is even brighter than before– remember, always keep an eye on the future, not the present or the past!

And similarly, if one has an extremely cheap cost basis in a company, one has an enormous margin of safety that should give further heed to trying to jump in and out of the stock when it is deemed to be overvalued.

He adds that, like wines, well-selected portfolio holdings get better with age because,

an alert investor who has held a good stock for some time usually gets to know its less desirable as well as more desirable characteristics

and through this process comes to develop even more confidence in his holdings.

If you’ve read some of my thinking about the philosophy of building multi-generational wealth through a family business, you’ll see once again the direct parallel to private market investing in Fisher’s conclusion:

If the job has been correctly done when a common stock is purchased, the time to sell it is– almost never.

Conclusion

Distilling Part I down to its essence, I concluded that the most important skill for generating long-term gains from one’s investing is still about having a disciplined and consistent investment program followed without interruption and in the face of constantly nagging self-doubt (“In the stock market a good nervous system is even more important than a good head.”) The particular program that Fisher recommends be followed is to:

1. Create a network of intelligent investors (bloggers) from which to source ideas
2. Develop a strong scuttlebutt skill/network to develop superior investment background
3. Check with management to confirm remaining questions generated from the 15 step list
4. With the conviction to buy, persevere in holding over a long period of time

If you can’t do this, you probably shouldn’t bother with the Fisher approach. Whether it can be done at all is an entirely separate matter.

Review – Quantitative Value

Quantitative Value: A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors + website

by Wesley R. Gray and Tobias E. Carlisle, published 2012

The root of all investors’ problems

In 2005, renowned value investing guru Joel Greenblatt published a book that explained his Magic Formula stock investing program– rank the universe of stocks by price and quality, then buy a basket of companies that performed best according to the equally-weighted measures. The Magic Formula promised big profits with minimal effort and even less brain damage.

But few individual investors were able to replicate Greenblatt’s success when applying the formula themselves. Why?

By now it’s an old story to anyone in the value community, but the lesson learned is that the formula provided a ceiling to potential performance and attempts by individual investors to improve upon the model’s picks actually ended up detracting from that performance, not adding to it. There was nothing wrong with the model, but there was a lot wrong with the people using it because they were humans prone to behavioral errors caused by their individual psychological profiles.

Or so Greenblatt said.

Building from a strong foundation, but writing another chapter

On its face, “Quantitative Value” by Gray and Carlisle is simply building off the work of Greenblatt. But Greenblatt was building off of Buffett, and Buffett and Greenblatt were building off of Graham. Along with integral concepts like margin of safety, intrinsic value and the Mr. Market-metaphor, the reigning thesis of Graham’s classic handbook, The Intelligent Investor, was that at the end of the day, every investor is their own worst enemy and it is only by focusing on our habit to err on a psychological level that we have any hope of beating the market (and not losing our capital along the way), for the market is nothing more than the aggregate total of all psychological failings of the public.

It is in this sense that the authors describe their use of “quantitative” as,

the antidote to behavioral error

That is, rather than being a term that symbolizes mathematical discipline and technical rigor and computer circuits churning through financial probabilities,

It’s active value investing performed systematically.

The reason the authors are beholden to a quantitative, model-based approach is because they see it as a reliable way to overcome the foibles of individual psychology and fully capture the value premium available in the market. Success in value investing is process-driven, so the two necessary components of a successful investment program based on value investing principles are 1) choosing a sound process for identifying investment opportunities and 2) consistently investing in those opportunities when they present themselves. Investors cost themselves precious basis points every year when they systematically avoid profitable opportunities due to behavioral errors.

But the authors are being modest because that’s only 50% of the story. The other half of the story is their search for a rigorous, empirically back-tested improvement to the Greenblattian Magic Formula approach. The book shines in a lot of ways but this search for the Holy Grail of Value particularly stands out, not just because they seem to have found it, but because all of the things they (and the reader) learn along the way are so damn interesting.

A sampling of biases

Leaning heavily on the research of Kahneman and Tversky, Quantitative Value offers a smorgasbord of delectable cognitive biases to choose from:

• overconfidence, placing more trust in our judgment than is due given the facts
• self-attribution bias, tendency to credit success to skill, and failure to luck
• hindsight bias, belief in ability to predict an event that has already occurred (leads to assumption that if we accurately predicted the past, we can accurately predict the future)
• neglect of the base case and the representativeness heuristic, ignoring the dependent probability of an event by focusing on the extent to which one possible event represents another
• availability bias, heavier weighting on information that is easier to recall
• anchoring and adjustment biases, relying too heavily on one piece of information against all others; allowing the starting point to strongly influence a decision at the expense of information gained later on

The authors stress, with numerous examples, the idea that value investors suffer from these biases much like anyone else. Following a quantitative value model is akin to playing a game like poker systematically and probabilistically,

The power of quantitative investing is in its relentless exploitation of edges

Good poker players make their money by refusing to make expensive mistakes by playing pots where the odds are against them, and shoving their chips in gleefully when they have the best of it. QV offers the same opportunity to value investors, a way to resist the temptation to make costly mistakes and ensure your chips are in the pot when you have winning percentages on your side.

A model development

Gray and Carlisle declare that Greenblatt’s Magic Formula was a starting point for their journey to find the best quantitative value approach. However,

Even with a great deal of data torture, we have not been able to replicate Greenblatt’s extraordinary results

Given the thoroughness of their data collection and back-testing elaborated upon in future chapters, this finding is surprising and perhaps distressing for advocates of the MF approach. Nonetheless, the authors don’t let that frustrate them too much and push on ahead to find a superior alternative.

They begin their search with an “academic” approach to quantitative value, “Quality and Price”, defined as:

Quality, Gross Profitability to Total Assets = (Revenue – Cost of Goods Sold) / Total Assets

Price, Book Value-to-Market Capitalization = Book Value / Market Price

The reasons for choosing GPA as a quality measure are:

• gross profit measures economic profitability independently of direct management decisions
• gross profit is capital structure neutral
• total assets are capital structure neutral (consistent w/ the numerator)
• gross profit better predicts future stock returns and long-run growth in earnings and FCF

Book value-to-market is chosen because:

• it more closely resembles the MF convention of EBIT/TEV
• book value is more stable over time than earnings or cash flow

The results of the backtested horserace between the Magic Formula and the academic Quality and Price from 1964 to 2011 was that Quality and Price beat the Magic Formula with CAGR of 15.31% versus 12.79%, respectively.

But Quality and Price is crude. Could there be a better way, still?

Marginal improvements: avoiding permanent loss of capital

To construct a reliable quantitative model, one of the first steps is “cleaning” the data of the universe being examined by removing companies which pose a significant risk of permanent loss of capital because of signs of financial statement manipulation, fraud or a high probability of financial distress or bankruptcy.

The authors suggest that one tool for signaling earnings manipulation is scaled total accruals (STA):

STA = (Net Income – Cash Flow from Operations) / Total Assets

Another measure the authors recommend using is scaled net operating assets (SNOA):

SNOA = (Operating Assets – Operating Liabilities) / Total Assets

Where,

OA = total assets – cash and equivalents

OL = total assets – ST debt – LT debt – minority interest – preferred stock – book common equity

They stress,

STA and SNOA are not measures of quality… [they] act as gatekeepers. They keep us from investing in stocks that appear to be high quality

They also delve into a number of other metrics for measuring or anticipating risk of financial distress or bankruptcy, including a metric called “PROBMs” and the Altman Z-Score, which the authors have modified to create an improved version of in their minds.

Quest for quality

With the risk of permanent loss of capital due to business failure or fraud out of the way, the next step in the Quantitative Value model is finding ways to measure business quality.

The authors spend a good amount of time exploring various measures of business quality, including Warren Buffett’s favorites, Greenblatt’s favorites and those used in the Magic Formula and a number of other alternatives including proprietary measurements such as the FS_SCORE. But I won’t bother going on about that because buried within this section is a caveat that foreshadows a startling conclusion to be reached later on in the book:

Any sample of high-return stocks will contain a few stocks with genuine franchises but consist mostly of stocks at the peak of their business cycle… mean reversion is faster when it is further from its mean

More on that in a moment, but first, every value investor’s favorite subject– low, low prices!

Multiple bargains

Gray and Carlisle pit several popular price measurements against each other and then run backtests to determine the winner:

• Earnings Yield = Earnings / Market Cap
• Enterprise Yield(1) = EBITDA / TEV
• Enterprise Yield(2) = EBIT / TEV
• Free Cash Flow Yield = FCF / TEV
• Gross Profits Yield = GP / TEV
• Book-to-Market = Common + Preferred BV / Market Cap
• Forward Earnings Estimate = FE / Market Cap

The result:

the simplest form of the enterprise multiple (the EBIT variation) is superior to alternative price ratios

with a CAGR of 14.55%/yr from 1964-2011, with the Forward Earnings Estimate performing worst at an 8.63%/yr CAGR.

Significant additional backtesting and measurement using Sharpe and Sortino ratios lead to another conclusion, that being,

the enterprise multiple (EBIT variation) metric offers the best risk/reward ratio

It also captures the largest value premium spread between glamour and value stocks. And even in a series of tests using normalized earnings figures and composite ratios,

we found the EBIT enterprise multiple comes out on top, particularly after we adjust for complexity and implementation difficulties… a better compound annual growth rate, higher risk-adjusted values for Sharpe and Sortino, and the lowest drawdown of all measures analyzed

meaning that a simple enterprise multiple based on nothing more than the last twelve months of data shines compared to numerous and complex price multiple alternatives.

But wait, there’s more!

The QV authors also test insider and short seller signals and find that,

trading on opportunistic insider buys and sells generates around 8 percent market-beating return per year. Trading on routine insider buys and sells generates no additional return

and,

short money is smart money… short sellers are able to identify overvalued stocks to sell and also seem adept at avoiding undervalued stocks, which is useful information for the investor seeking to take a long position… value investors will find it worthwhile to examine short interest when analyzing potential long investments

This book is filled with interesting micro-study nuggets like this. This is just one of many I chose to mention because I found it particularly relevant and interesting to me. More await for the patient reader of the whole book.

Big and simple

In the spirit of Pareto’s principle (or the 80/20 principle), the author’s of QV exhort their readers to avoid the temptation to collect excess information when focusing on only the most important data can capture a substantial part of the total available return:

Collecting more and more information about a stock will not improve the accuracy of our decision to buy or not as much as it will increase our confidence about the decision… keep the strategy austere

In illustrating their point, they recount a funny experiment conducted by Paul Watzlawick in which two subjects oblivious of one another are asked to make rules for distinguishing between certain conditions of an object under study. What the participants don’t realize is that one individual (A) is given accurate feedback on the accuracy of his rule-making while the other (B) is fed feedback based on the decisions of the hidden other, invariably leading to confusion and distress. B comes up with a complex, twisted rationalization for his  decision-making rules (which are highly inaccurate) whereas A, who was in touch with reality, provides a simple, concrete explanation of his process. However, it is A who is ultimately impressed and influenced by the apparent sophistication of B’s thought process and he ultimately adopts it only to see his own accuracy plummet.

The lesson is that we do better with simple rules which are better suited to navigating reality, but we prefer complexity. As an advocate of Austrian economics (author Carlisle is also a fan), I saw it as a wink and a nod toward why it is that Keynesianism has come to dominate the intellectual climate of the academic and political worlds despite it’s poor predictive ability and ferociously arbitrary complexity compared to the “simplistic” Austrian alternative theory.

But I digress.

Focusing on the simple and most effective rules is not just a big idea, it’s a big bombshell. The reason this is so is because the author’s found that,

the Magic Formula underperformed its price metric, the EBIT enterprise multiple… ROC actually detracts from the Magic Formula’s performance [emphasis added]

Have I got your attention now?

The trouble is that the Magic Formula equally weights price and quality, when the reality is that a simple price metric like buying at high enterprise value yields (that is, at low enterprise value multiples) is much more responsible for subsequent outperformance than the quality of the enterprise being purchased. Or, as the authors put it,

the quality measures don’t warrant as much weight as the price ratio because they are ephemeral. Why pay up for something that’s just about to evaporate back to the mean? […] the Magic Formula systematically overpays for high-quality firms… an EBIT/TEV yield of 10 percent or lower [is considered to be the event horizon for “glamour”]… glamour inexorably leads to poor performance

All else being equal, quality is a desirable thing to have… but not at the expense of a low price.

The Joe the Plumbers of the value world

The Quantitative Value strategy is impressive. According to the authors, it is good for between 6-8% a year in alpha, or market outperformance, over a long period of time. Unfortunately, it is also, despite the emphasis on simplistic models versus unwarranted complexity, a highly technical approach which is best suited for the big guys in fancy suits with pricey data sources as far as wholesale implementation is concerned.

So yes, they’ve built a better mousetrap (compared to the Magic Formula, at least), but what are the masses of more modest mice to do?

I think a cheap, simplified Everyday Quantitative Value approach process might look something like this:

1. Screen for ease of liquidity (say, $1B market cap minimum)
2. Rank the universe of stocks by price according to the powerful EBIT/TEV yield (could screen for a minimum hurdle rate, 15%+)
3. Run quantitative measurements and qualitative evaluations on the resulting list to root out obvious signals to protect against risk of permanent loss by eliminating earnings manipulators, fraud and financial distress
4. Buy a basket of the top 25-30 results for diversification purposes
5. Sell and reload annually

I wouldn’t even bother trying to qualitatively assess the results of such a model because I think that runs the immediate and dangerous risk which the authors strongly warn against of our propensity to systematically detract from the performance ceiling of the model by injecting our own bias and behavioral errors into the decision-making process.

Other notes and unanswered questions

“Quantitative Value” is filled with shocking stuff. In clarifying that the performance of their backtests is dependent upon particular market conditions and political history unique to the United States from 1964-2011, the authors make reference to

how lucky the amazing performance of the U.S. equity markets has truly been… the performance of the U.S. stock market has been the exception, not the rule

They attach a chart which shows the U.S. equity markets leading a cohort of long-lived, high-return equity markets including Sweden, Switzerland, Canada, Norway and Chile. Japan, a long-lived equity market in its own right, has offered a negative annual return over its lifetime. And the PIIGS and BRICs are consistent as a group in being some of the shortest-lifespan, lowest-performing (many net negative real returns since inception) equity markets measured in the study. It’s also fascinating to see that the US, Canada, the UK, Germany, the Netherlands, France, Belgium, Japan and Spain all had exchanges established approximately at the same time– how and why did this uniform development occur in these particular countries?

Another fascinating item was Table 12.6, displaying “Selected Quantitative Value Portfolio Holdings” of the top 5 ranked QV holdings for each year from 1974 through 2011. The trend in EBIT/TEV yields over time was noticeably downward, market capitalization rates trended upward and numerous names were also Warren Buffett/Berkshire Hathaway picks or were connected to other well-known value investors of the era.

The authors themselves emphasized that,

the strategy favors large, well-known stocks primed for market-beating performance… [including] well-known, household names, selected at bargain basement prices

Additionally, in a comparison dated 1991-2011, the QV strategy compared favorably in a number of important metrics and was superior in terms of CAGR with vaunted value funds such as Sequoia, Legg Mason and Third Avenue.

After finishing the book, I also had a number of questions that I didn’t see addressed specifically in the text, but which hopefully the authors will elaborate upon on their blogs or in future editions, such as:

1. Are there any reasons why QV would not work in other countries besides the US?
2. What could make QV stop working in the US?
3. How would QV be impacted if using lower market cap/TEV hurdles?
4. Is there a market cap/TEV “sweet spot” for the QV strategy according to backtests? (the authors probably avoided addressing this because they emphasize their desire to not massage the data or engage in selection bias, but it’s still an interesting question for me)
5. What is the maximum AUM you could put into this strategy?
6. Would more/less rebalancing hurt/improve the model’s results?
7. What is the minimum diversification (number of portfolio positions) needed to implement QV effectively?
8. Is QV “businesslike” in the Benjamin Graham-sense?
9. How is margin of safety defined and calculated according to the QV approach?
10. What is the best way for an individual retail investor to approximate the QV strategy?

There’s also a companion website for the book available at: www.wiley.com/go/quantvalue

Conclusion

I like this book. A lot. As a “value guy”, you always like being able to put something like this down and make a witty quip about how it qualifies as a value investment, or it’s intrinsic value is being significantly discounted by the market, or what have you. I’ve only scratched the surface here in my review, there’s a ton to chew on for anyone who delves in and I didn’t bother covering the numerous charts, tables, graphs, etc., strewn throughout the book which serve to illustrate various concepts and claims explored.

I do think this is heady reading for a value neophyte. And I am not sure, as a small individual investor, how suitable all of the information, suggestions and processes contained herein are for putting into practice for myself. Part of that is because it’s obvious that to really do the QV strategy “right”, you need a powerful and pricey datamine and probably a few codemonkeys and PhDs to help you go through it efficiently. The other part of it is because it’s clear that the authors were really aiming this book at academic and professional/institutional audiences (people managing fairly sizable portfolios).

As much as I like it, though, I don’t think I can give it a perfect score. It’s not that it needs to be perfect, or that I found something wrong with it. I just reserve that kind of score for those once-in-a-lifetime classics that come along, that are infinitely deep and give you something new each time you re-read them and which you want to re-read, over and over again.

Quantitative Value is good, it’s worth reading, and I may even pick it up, dust it off and page through it now and then for reference. But I don’t think it has the same replay value as Security Analysis or The Intelligent Investor, for example.