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.

Review – Free Capital

Free Capital: How 12 Private Investors Made Millions In The Stock Market

by Guy Thomas, published 2011

A methodical review of investors and their strategies

The greatest strength of “Free Capital” is its organization and layout– it’s truly like visiting an expertly-designed website in that the author has organized his investor interviews by four major descriptive categories:

• geographers; top-down investors who begin with a macro thesis then look for companies and financial instruments which will benefit from that trend
• surveyors; bottoms-up investors who start looking at individual companies and then sometimes check to see what kind of macro conditions might affect them
• activists; investors who tend to get personally involved with their investments, taking large stakes and developing a close relationship with management
• eclectics; people who don’t really fit any mold, but might be day-traders, value investors, sometimes activists, etc.

Within each categorical section are profiles of 12 (in total) investors that Guy Thomas spoke with, many of whom are anonymous, most of whom he came into contact with via investor message boards he participates on, and all of whom are UK-based and have managed to grow their capital into millions even over the last decade or less.

Though many were once employed by others and some came from financial backgrounds, all are now independent, full-time investors who live off of their investment returns and it is this kind of self-directed lifestyle and the resources which are needed to finance it that primarily lend themselves to the book’s title.

What’s really great is that in each chapter, Guy Thomas begins with a quick “tearsheet” profile of the investor’s strategy, key phrases, holding period, etc., then neatly organizes the interview material into background on the investor’s life and development as a financial person, outlines their strategy, experiences and any particularly demonstrative coups or failures they’ve enjoyed (or suffered) and finally and extremely helpfully, summarizes all the material again in a table at the end with the major themes or ideas explored for quick reference.

As if this weren’t enough, Guy Thomas has written a lengthy (and for once, interesting) introduction to the book that serves as a combination summary of the main themes of the book as well as a how-to manual for those looking to get the most out of their reading. Thomas is correct in suggesting that the book can be read all the way through as a complete work, or explored at random based on what, if anything, sounds interesting to the reader.

It’s touches like this that show a thoughtfulness on the part of the author that leave the reader painfully aware of their absence in comparison to many other books in the genre. Frankly, it’d be nice if authors and publishers took Thomas’s lead on this point!

My favorite part: inspiration

I was excited to dig into the book in part because a friend had mentioned it to me and had commented favorably on it. He said a lot of the material covered wouldn’t be original but that I might find it inspirational to read other people’s stories of how they got where they are.

Maybe it’s where I am in my life right now, maybe it’s the subtle suggestion my friend made planted in my mind, or maybe it’s the shining spot for the book but the inspiration was one of the most important things I took away from the book. Some of the profiles were admittedly unhelpful (such as the day-trader, an investment style I can’t see any point in) or just not interesting to me (a few of the investors followed research processes I don’t have the time or motivation to emulate), but there were a couple I identified with, which made me feel empowered and hopeful about myself as I read them.

I particularly liked the two named investors, John Lee (who is a dividend-oriented value investor of sorts) and Peter Gyllenhammar (who bankrupted himself twice before hitting his stride and amassing his current fortune). I believe all of the investors lives and experiences illustrated this point well, but these two in particular were examples of the phrase “Patience is a virtue.” If a man can dust himself off after two bankruptcies and still make something of himself he can probably do just about anything given the time and the patience. Seeing as how I haven’t suffered personal bankruptcy (yet) I felt greatly advantaged to learn from this example of perseverance and triumph over failure.

Wise aphorisms

Another theme oft explored in “Free Capital” is the role simplicity plays in good investing. To that effect, I found a lot of great investing ideas captured in brief, simple aphorisms that made them both easily digestible and sufficiently memorable to make use of them myself in my own deliberations. Some examples include:

• Good investing “requires only a few good decisions” (a helpful reminder given the way many seem to imply that a true investor is marked by the numerousness and hyperactivity of his ideas)
• An activist is an investor who goes looking for trouble
• “Quiet freedom is itself exotic” (in this way, independent investors lead quite adventuresome and even exciting lives!)
• Exposure to some chances can only arise through deliberate and possibly unpopular and eccentric choices
• Investment skill consists in not knowing everything, but in judicious neglect: making wise choices about what to overlook
• Freedom is like income that cannot be taxed
• To make good decisions, you need to look actively for reasons not to buy a company. And then invest only in those where you can live with the reasons
• Time is a limited resource with strongly diminishing returns. The first hour you spend researching a company is much more important than the tenth hour
• If an investment decision requires detailed calculations, you should pass, because it’s probably too close
• The sun shines even on the poor man

Also of note is the author’s book-companion blog, which goes into a bit more detail on some of the investment themes captured in the book and which I’ve found to be a good supplement to the reading seeing that I was still interested to learn more even after I put it down.

Conclusion

“Free Capital” is a unique offering. It has a styling and organization that many books in its genre lack and I hope this effort is continued in any future titles from the author. And it treads original ground in profiling anonymous, “everyman” successful investors that no one has heard of yet who have interesting stories, experiences and lessons to share all their own. We can all learn from more than just Warren Buffett, after all.

It’s not without its flaws, of course. As the author himself states, the book doesn’t cover losing investors, people who took some of the risks investors profiled took, and failed, or who took other risks that didn’t turn out right, and then explores what lessons can be learned from their shortcomings. This probably could be a worthwhile book in itself, as there is a growing literature on “failure studies” and as the first lesson every investor must learn is “don’t lose what you’ve got”, learning of common mistakes to avoid could be helpful. Additionally, as an avid deep value (Benjamin Graham) guy myself, I could’ve done without the day trader and some of the other guys who seem like GARPy, momentum-based swing traders with short time horizons and questionable “value” metrics.

But those are minor quibbles and things that Guy Thomas could easily rectify by simply writing us more great books to read! Overall, “Free Capital” was entertaining, at times enlightening and best of all, extremely gracious with my free time as I read the entire thing in just three or four hours. Given the focus on the value of time in the book, I appreciated the fact that I could digest the meat of the book and walk away with some great insights to help my own investing… and still have time left in the day to get other things done!

Four Views On Gold And Gold Miners

1.) Atyant Capital, “What is gold saying?”:

Gold stocks lead gold and gold leads currencies and currency moves correlate with stocks and bonds. Gold stocks have been declining for two or so years now. This is in part due to unavailability of capital and credit for gold mining projects, but in our assessment, not the whole story. We believe gold stocks are also correctly forecasting lower gold prices.

Long term readers know my gold pricing model puts fair value at $1100 per ounce (Alpha Magazine Aug 24, 2011). So at $1700-$1800, gold was about 60% overvalued, floating on a sea of credit. Gold declining now tells me the sea of credit is receding here and now. This should translate to a higher US Dollar and pressure on asset prices globally.

2.) Value Restoration Project, “Gold miners – Back in the Abyss – An Update“:

Gold mining stocks remain cheap by almost any objective measure.

One way to look at mining stocks is to compare them to the price of gold itself.

Comparing miners to the price of gold itself, show miners are cheaper today than they have been in decades.

[…]

Today, gold appears undervalued relative to the growth in the monetary base that has occurred up to now, and in light of the monetary expansion the Fed and other central banks are currently undertaking, gold appears more undervalued. The Fed’s current quantitative easing program probably won’t be curtailed until households stop deleveraging and the government can handle the rising interest expense on its expanding debt.

Yet, in the face of all this, many gold mining stocks are now selling at valuations that suggest the market has priced in a decline in the price of gold back to 2007 levels, before the Fed began expanding its balance sheet during the financial crisis. Many gold mining stocks are now selling near or below their book value, which is the market’s way of saying that these businesses won’t be able to add shareholder value in the coming years by mining gold and silver. If the price of gold were to decline below $700 or so, it would certainly be the case that most mining companies wouldn’t be able to profitably sell gold. Yet such a decline in gold is the main implied assumption being priced in by the market today, and this has sent valuations of gold mining stocks to their lowest levels since the current bull market began.

3.) Robert Blumen, “What is the key for the price formation of gold?“:

The gold price is set by investor preferences, which cannot be measured directly. But I think that we understand the main factors in the world that influence investor preferences in relation to gold. These factors are the growth rate of money supply, the volume and quality of debt, political uncertainty, confiscation risk, and the attractiveness (or lack thereof) of other possible assets. As individuals filter these events through their own thoughts they form their preferences. But that’s not something that’s measurable.

I suspect that the reason for the emphasis on quantities is that they that can be measured. Measurement is the basis of all science. And if we want our analysis to be rigorous and objective, so the thinking goes, we had better start with numbers and do a very fine job at measuring those numbers accurately. If you are an analyst you have to write a report for your clients, after all they have paid for it, so they have to come up with things that can be measured and the quantity is the only thing that can be measured so they write about quantities.

And in the end this is the problem for gold price analysts, you’re talking about a market in which it’s difficult to really quantify what’s going on. I think that looking at some broad statistical relationships over a period of history, like gold price to money supply, to debt, things like that, might give some idea about where the price is going. Or maybe not, maybe you run into the problem I mentioned about synchronous correlations that are not predictive.

Part of the problem is that statistics work better the more data you have. But we really don’t have a lot of data about how the gold price behaves in relation to other things. The unbacked global floating exchange rate system has never been tried before our time. How many complete bull and bear cycles has the gold/fiat market gone through? My guess is that when we look back we will see that we are now still within the first cycle. Our sample size is one.

[…]

I do think we will have a bubble in gold, although it may take the form of a collapse of the monetary and a return to some form of gold as money in which case, the bubble will not end, it would simply transition over to the new system in which gold would go from being a non-money asset to money.

I have been following this market since the late 90s. I remember reading that gold was in a bubble at every price above 320 dollars. I very much like the writings of William Fleckenstein, an American investment writer. He has pointed out how often you read in the financial media that gold is already in a bubble, a point he quite rightly disputes. Fleckenstein has pointed out that the people who say this did not identify the equity bubble, did not believe that we had a housing bubble, nor have they identified the current genuine bubble, which in the bond market. But now these same people are so good at spotting bubbles that they can tell you that gold is in one.

Most of them did not identify gold as something which was worth buying at the bottom, have never owned a single ounce of gold, have missed the entire move up over the last dozen years, and now that they’re completely out of the market, they smugly tell us for our own good that gold is in a bubble and we should sell.

So, I don’t know that we need to listen to those people and take them very seriously.

4.) Me:

I don’t know what the intrinsic value of gold is. I don’t think gold mines are good businesses (on the whole) because they combine rapidly depleting assets with high capital intensitivity and they are constantly acquiring other businesses (mines) sold by liars and dreamers and schemers. And I don’t think this will end well, whatever the case may be. So, I am happy to own a little gold and wait and see what happens.

I wonder what the short interest is on gold miners?

Review – The Outsiders

The Outsiders: Eight Unconventional CEOs and Their Radically Rational Blueprint for Success

by William N. Thorndike, Jr., published 2012

Capital allocation uber alles

“The Outsiders” rests on a premise, that the increase in a public company’s per share value is the best metric for measuring the success of a given CEO, which lends itself to the book’s major thesis: that superior capital allocation is what sets apart the best CEOs from the rest, and that most modern CEOs seem to be only partially aware, if at all, of its critical performance to their companies long-term business success.

Notice! This book is examining the efforts and measurements of CEOs of public companies, not all businesses (public and private), so as a result in comes up a bit short in the “universal application” department. Yes, capital allocation is still critical even in a private business, but you can not measure a private business’s per share value (because there isn’t a marketable security price to reference) and the CEO of a private company is missing one of the most powerful capital allocation tools available to public CEOs, the share buyback (because there is no free float for them to get their hands on at periodically irrational prices).

The CEO capital allocation toolkit

Thorndike describes five capital allocation choices CEOs have:

1. invest in existing operations
2. acquire other businesses
3. issue dividends
4. pay down debt
5. repurchase stock

Along with this, they have three means of generating capital:

1. internal/operational cash flow
2. debt issuance
3. equity issuance

With this framework, Thorndike proceeds to review the business decisions of 8 different “outsider” CEOs, so labeled because they tended to use these tools in a contrary fashion to the mainstream wisdom of their time and to much improved effect as per comparison to their benchmarks. Some of the CEOs are well known and oft mentioned and studied (Warren Buffett, John Malone, Kay Graham, Tom Murphy) and a few are known to the value cognoscenti but may have managed to escape notice of the wider public, academic or otherwise (Henry Singleton, Bill Anders, Bill Stirlitz and Dick Smith).

The author tries to tie together the various common threads, such as how,

All were first-time CEOs, most with very little prior management experience

and many of which (such as Singleton, Buffett and Graham) were large or majority equity holders in their companies, making them part of the vaunted owner-operator club with its resulting beneficial incentives.

Thorndike also tries to use the hedgehog vs. fox metaphor, claiming,

They had familiarity with other companies and industries and disciplines, and this ranginess translated into new perspectives, which in turn helped them to develop new approaches that eventually translated into exceptional results

Interestingly, the share buyback stands out as a particularly effective capital allocation tool for all and the author claims that during the difficult inflationary conditions and market depression of the 1974-1982 period,

every single one [emphasis in the original] was engaged in either a significant share repurchase program or a series of large acquisitions

In broad strokes, Thorndike’s efforts to paint these CEOs with a common brush works, but there are numerous times where his attempt to establish commonality  in genius comes across as forced and unworkable. Often, one of these CEOs will operate in a way inconsistent with Thorndike’s major thesis and yet he’ll end up praising the CEO anyway. In poker, we’d call this the “won, didn’t it?” fallacy– judging a process by the specific, short-term result accomplished rather than examining the long-term result of multiple iterations of the process over time.

Some quibbles

This is actually one of the things that rubbed me rather raw as I read the book. In every chapter, Thorndike manages to strike a rather breathless, hagiographic tone where these CEOs can do no wrong and everything they do is “great”, “fantastic,” etc. Unfortunately, this kind of hyperbolic language gets used over and over without any variety to the point it’s quite noticeable how lacking in detail and critical analysis Thorndike’s approach is at points.

Eventually, I reached a point where I almost wanted to set the book down, take a deep breath and say, “Okay… I get it, this guy is absolutely amazing… can we move on now?”

The editing seemed a bit sloppy, too. Thorndike is a graduate of Stanford and Harvard and runs his own financial advisory. He’s obviously an accomplished, intellectual person. Yet his prose often reads like an immature blog post. It’s too familiar and casual for the subject matter and the credentials of the author. I’m surprised they left those parts in during the editing process. I think it makes Thorndike’s thesis harder to take seriously when, in all likelihood, it’d probably be quite convincing if you happened to chat with the author on an airplane.

From vice to virtue

Something I liked about “The Outsiders” was the fact that there were 8 profiles, rather than one. It was reinforcing to see that the same principles and attitudes toward business and management were carried out by many different individuals who didn’t all know each other (though some did) and ALL had huge outperformance compared to their benchmark.

And I think for someone who is just jumping into the investing, management and agency problem literature, “The Outsiders” is a good place to start to get a broad outline of the major thesis which is that companies that are run by owner-operators, or by people who think like them, where the top management focuses on intelligently allocating capital to its highest use (which, oftentimes when the company’s stock remains stubbornly low compared to its estimated intrinsic value, makes buybacks in the public market the most intelligent option versus low margin growth) consistently outperform their peers and their benchmarks on a financial basis.

I think if this was one of the first books I had read on this theme, I would’ve found it quite illuminating and exciting, a real eye-opener experience. As it were, I read this book after reading a long train of other, often times significantly more comprehensive and detailed literature, so my personal experience was rather flat– I came away thinking I hadn’t learned much.

More to the story

There’s more to this story in two senses.

In the first sense, I actually highlighted many little comments or ideas throughout the book that are either helpful reminders or concepts I hadn’t fully considered myself yet, pertaining to best operational and management practices for businesses and the people who invest in them. In other words, the book is a little deeper than I bothered to share here. As a collection of anecdotes and principles for mastering the concept of capital allocation, it’s a good resource.

In the second sense, I think there’s a lot more to the success of the businessmen and their companies profiled (along with many others) than just good capital allocation. The text alludes to this with quotes from various figures about how they operated their businesses and managed people aside from the specific challenges of capital allocation. But it never goes into it because that isn’t in focus.

And as a business person myself, I know from my own reading, thinking and personal experience that capital allocation IS a critical factor in successfully managing and growing a business over the long-term — after all, if you can’t find good places to put your cash, you’ll inevitably end up wasting a lot of it — but you won’t have capital to allocate if you aren’t operating your business and managing your relationships with employees and customers well, in addition. The book just doesn’t do much in the way of explaining how it was that Ralston Purina, or General Dynamics or Teledyne or what have you, had so much capital to allocate in the first place.

I think people like this book so much because it’s exciting to read about outsize success, regardless of how it happened.

Review – Professional Investor Rules

Professional Investor Rules: Top Investors Reveal The Secrets of Their Success

by various, introduction by Jonathan Davis, published 2013

The many faces of money management

A 1948 Academy Award-winning film popularized the slogan “There are eight million stories in the Naked City”, and after reading the eclectic “Professional Investor Rules”, I’m beginning to think there are almost as many stories about how to manage money properly.

Value and growth, momentum and macro-geography, market-timing and voodoo superstition; all these major investment strategies and themes are on display, and many more to boot, and all come bearing their own often-tortured metaphors to convey their point.

What’s more, it seems the pacing and style of the book change along with the advice-giver: while some of the entries follow the books eponymous “rule” format for organizing their thoughts, others involve myths, lengthy prose paragraph-laden essays and headings with sub-headings. Some have charts, and some do not.

One things consistent, at least– all the advisors profiled contradict one another at some point or other, and some even manage to contradict themselves in their own sections.

But it’s got this going for it, which is nice

Those are some of the glaring cons to the book. It’s not entirely without it’s pros, however.

One of the things I liked about the book is, ironically, also one of its flaws– the great variety of personas. They run the gamut from the known to the unknown, the mainstream to the contrarian, the sell-side to the buy-side. This book is published by a UK outfit (Harriman House), which means many of the professional soothsayers will be unfamiliar to US audiences, but it also means you get a selection of icons from the Commonwealth and former British territories (such as Hong Kong and other Asia-based managers) that you’d likely never hear about on CNBC or other American publishing sources.

Following this contrarian inversion theme, I liked that all the phony  fuzzy thinkers were right there next to the sharper pencils because it made their baloney that much more rotten. I think this is a great service for an uninformed investor picking up this book. If they had come across some of the more foppish money dandies on their own, elsewhere, they’d be liable to get taken in and swindled like the thousands of others who sustain such frauds. But at least in this case you’ve got a go-go glamour guy saying no price is too high for a growing company right next to a value guy warning that that way lies the path to certain, eventual doom.

And maybe this isn’t a big deal to others but I like the packaging on this hardcover edition I’ve got– it’s truly a HANDy size, the fonts and color scheme are modern and eye-catching and the anecdotal organization of the book makes it easy to pick up and put down without feeling too upset over whether or not you’ve got the time to commit to a serious read right then.

Fave five

Here are five of my favorite ideas from the book, along with the person(s) who said it:

1. At any one time, a few parts of your portfolio will be doing terribly… focus on the performance of the portfolio as a whole (William Bernstein, Efficient Frontier Advisors)
2. Far more companies have failed than succeeded (Marc Faber, The Gloom, Boom and Doom Report)
3. Fight the consensus, not the fundamentals (Max King, Investec Asset Management)
4. When someone says ‘it’s not about the money,’ it’s about the money (H.L. Mencken… consequently not actually a money manager and not alive, but it was quoted in one of the in-betweens spacing out the chapters)
5. Academics never rescind papers and never get fired (Robin Pabrook and Lee King Fuei, Schroeders Fund, Asia)

Conclusion

Who is this book for? Accomplished, well-read pro-am investors will find nothing new here and much they disagree with, so I’d recommend such readers stay away. Someone completely new to investing and the money management industry might find the book valuable as a current snapshot of the gamut of strategic strains present in the money management industry.

Overall, while “Professional Investor Rules” has its moments, overall I came away less enthused than I did with Harriman House’s earlier offering, Free Capital. For anyone looking to learn investing techniques from accomplished, self-made millionaires, that’s the book I’d point them to– the advice therein is worth multiples of that being given by the mass of asset gathering managers of OPM contained in this one.