Review – How To Read A Book (#reading, #understanding, #philosophy, #education)

How To Read A Book: The Classic Guide to Intelligent Reading

by Mortimer J. Adler, Charles Van Doren, published 1972

“Literate ignoramuses who have read too widely and not well”

HTRAB seeks to be a remedy for those described above who have read many books but understood little of any of them. As the authors define it, good reading is active reading, that is, it involves note-taking and and highlighting (write in your books to make them truly yours) and question-asking, with the ultimate question being, “What has the author tried to communicate to me and, assuming I’ve understood him, what do I think of what he has said?” A book is an absent teacher– it is ultimately your responsibility to answer on your own and for yourself the questions you might pose to it.

The 4 levels of reading

The authors set out four levels of reading, which are hierarchical in terms of complexity and skill required, and cumulative, in the sense that each level includes the skills and complexity of those below it while adding unique qualities of its own. The levels are:

  1. Elementary
  2. Inspectional
  3. Analytical
  4. Syntopical

Elementary reading is exactly what it sounds like, the most basic level of reading that all people learning to read initially experience. At this level of reading, one begins to comprehend the letters and words they form as being connected to or representative of concepts, actions, etc. Unfortunately, at this level of reading, comprehension doesn’t go much beyond this and even more tragically, few readers ever seem to graduate beyond this level, even during and after time spent in college. For elementary readers, books are full of words one must step and stumble over, but little meaning is ever found in them.

Inspectional reading is the beginning of true “reading for understanding”, which is the kind of reading HTRAB is primarily focused on. Inspectional reading is both a level of sophistication and a specific tool that can be used to heighten overall understanding and reading skill for one who “reads well.” It is a skill in the sense that an inspectional reader is able to draw out of a book its essential meaning and something about the way in which the author goes about it (as opposed to an elementary reader, who never quite gets that far, missing the meaning forest for the crowd of symbolic trees). It is a specific tool in that inspectional reading entails a deliberate process by which a reader examines the preface and introductory material of the book (or the first few pages) and the conclusion or epilogue (or last few pages) in detail, surveys the table of contents (if available) and index to get a feel for the overall structure, order and topics covered in the book and then jumps around at random through the middle of the book reading passages and pages of interest that appear to be central to the author’s theme and argument. In this way, an inspectional reader quickly learns what the book is about, how the author goes about elaborating upon it and, perhaps most importantly, whether or not it’s a message and artifice worthy of the readers attention and time.

Without this process, or at a minimum, familiarizing oneself with the table of contents, a reader who starts at the first page and tries to plow through is only making his reading more challenging because he is attempting to learn what he is attempting to understand (the topic and structure), at the same time that he is trying to understand it.

The three primary questions answered by an inspectional (summary) reading are:

  1. What kind of book is it?
  2. What is it about as a whole?
  3. What is the structural order of the work whereby the author develops his conception or understanding of that general subject matter?

Tools to prepare you for reading well

The authors suggest four essential questions to be asked by an active reader:

  1. What is the book about as a whole?
  2. What is being said in detail, and how?
  3. Is the book true, in whole or in part?
  4. What of it?

These are questions the reader should have always in the back of his mind as he reads, and which he should be able to answer confidently by the time he finishes.

The authors also recommend several techniques for “making a book your own”:

  • Underline major points and forceful statements
  • Make vertical lines in the margins for passages worthy of quoting at length
  • Stars, asterisks or other markings in the margins where the ten or twelve most critical points are made throughout the book
  • Numbers in the margin to catalog the points of an argument being made sequentially
  • Numbers of other pages in the margin indicating where in the text an idea is revisited or referenced
  • Circling of key words or phrases, similar to underlining
  • Writing in the margin or top or bottom of the page or at the end of a chapter as endnotes, to record questions (and answers), a simplified thesis of what you have read or to catalog a sequential argument in concentrated form

Several other techniques and methods are discussed in HTRAB which are critical to reading well. One is to study the title of the book and learn what you can from it. Authors usually take care in naming their books and the titles give significant clues about what the book is and is not about. Another is to practice stating the unity of the book– in a sentence or a paragraph at most, explain what kind of book it is, what it is about and list the devices the author employs to explore that theme. A final tool is to keep in mind the author’s intentions at all times– every book is written ostensibly to solve a problem, which the book is supposed to be a solution for, which begs the questions, “What is the problem the author wanted to solve by writing his book?” and “What solution does he offer to the problem in writing his book?”

The process of analytical reading

The third level of reading, and the most critical for all who wish to learn to read well, is the analytical level. At the analytical level, the primary intention of the reader is to be thorough, complete and to read for understanding. Some of the tools previously discussed are, in fact, part of the analytical reading toolkit. In total, the process or “rules” for analytical reading are:

  1. Classify the book according to kind and subject matter
  2. State what the whole book is about with the utmost brevity
  3. Enumerate its major parts in their order and relation, and outline these parts as you have outlined the whole
  4. Define the problem or problems the author is trying to solve
  5. Come to terms with the author by interpreting his key words
  6. Grasp the author’s leading propositions by dealing with his most important sentences
  7. Know the author’s arguments, by finding them in, or constructing them out of, sequences of sentences
  8. Determine which of his problems the author has solved, and which he has not; and as to the latter, decide which the author knew he had failed
  9. Do not begin criticism until you have completed your outline and interpretation of the book (do not say you agree, disagree, or suspend judgment, until you can say, “I understand.”)
  10. Do not disagree disputatiously or contentiously
  11. Demonstrate that you recognize the difference between knowledge and mere personal opinion by presenting good reasons for any critical judgment you make
  12. For criticism, special criteria apply such as: show wherein the author is misinformed, uninformed, illogical or incomplete

I made a note of some other helpful tips for reading well analytically:

  • the important words (in the sense of being critical to the author’s argument) are the one’s that give you the most trouble
  • one clue to an important word is that the author quarrels with other writers about it
  • if you never ask yourself any questions about a passage, you cannot expect the book to give you insights you did not already possess
  • it is best to do all you can without outside help because if you act on this principle consistently you will find you need less and less of it (and take more and more from your reading)

Bringing it all together: syntopical reading

Syntopical reading is the reading of multiple books, with similar topics, in order to synthesize a “conversation” amongst and between the authors. The beauty of this method of reading is it allows one to pit perspectives and arguments from differing backgrounds and even differing time periods into one intellectual commons. It also allows the reader to get a “full measure” of the literary world’s treatment of a given subject. It can be performed by either multi-inspectional reading of various titles, or multi-analytical reading of those same titles.

The steps of a successful syntopical reading are:

  1. Creative a tentative bibliography of your subject
  2. Inspect all of the books in the bibliography to ensure they’re germane and to get a clearer perspective of the subject itself
  3. Inspect the books amassed to find the most relevant passages to the subject matter
  4. Bring the authors to terms by constructing a neutral terminology that all authors can be assumed to agree with, even if they didn’t employ such terminology themselves
  5. Establish a set of neutral propositions for all of the authors by framing a set of questions to which all or most of the authors can be interpreted to have provided answers, whether they actually treat the questions explicitly or not
  6. Define the issues, major and minor, by lining up the authors’ respective viewpoints on one side or another
  7. Analyze the discussion by ordering the questions and issues so as to throw maximum light on the subject

An afterword

Despite my efforts at being analytical, this review was something of an inspectional survey itself. One thing I took away from my reading is that I do a lot of the things mentioned in the analytical reading process, although I actually neglect a lot of the inspectional reading elements and now realize their value. The reading also confirmed some of my biases by throwing into stark relief the inadequacies of many other people’s reading efforts I am aware of, either from direct personal experience or via interaction with their “interpretations” of ideas gleaned from things they have read. It is somewhat dismaying to realize how few intellectual opponents would qualify as “well read” analytical book users, and how inadequate their attempts at criticism are in light of this. One would be more satisfied to think one’s opponents were both more competent, and more honest, than that.

At the end of HTRAB, the authors provide a number of special tips for the reading of specific kinds of works (poems and plays, history, social science, hard science and math, etc.), as well as a bibliography of “great books” (similar to that found here) and a short essay on what reading well can do for an individual. Aside from the hopefully true suggestion that the mind-exercise provided by reading well can actually help one sustain the vitality and quality of their life even into old age, the discussion of the growing relationship one can develop with truly “great” books is comforting, as well. I think for me personally this passage resonated because of my own experiences reading what I refer to as “acts of philosophy” even when their subject matter is not philosophy per se (endlessly re-readable books like Security Analysis and Human Action which seem to give up new secrets and ideas with each new pass through).

Despite my epistemological misgivings about HTRAB (for example, could HTRAB, in and of itself, assist a person currently capable of nothing more than elementary reading to rise above themselves?), I do believe it itself is a title worth revisiting in the future. My first foray amongst its pages was admittedly quick and inspectional, and there were many passages I will admit I skipped just so I could get to the end and get this up on my blog. It may or may not be a “great” book (I believe I will suspend judgment on that for now), it is undoubtedly a “good” book with much to recommend it and I would encourage anyone who is interested, as well as my future self, to pick it up and give it a read.



Review – Quantitative Value (#valueinvesting, #quant, @greenbackd, @turnkeyanalyst)

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


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


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:


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 (#investing, @guy_thomas, #millionaires)

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.


“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!


Review – How To Win Friends & Influence People (#influence, #selfimprovement, #DaleCarnegie)

How To Win Friends And Influence People

by Dale Carnegie, published 1936, 1981

A master’s education in properly respectful and efficacious communication

Dale Carnegie’s 1936 classic in interpersonal communication sets the standard in techniques for dealing positively and constructively with others. The book is easy to summarize (the edition I own actually has an end-chapter summary and end-of-section summary-summary of all the major points addressed), so I’ve done that below for quick reference. But Carnegie is an excellent story teller and weaver of parables. This is a book that’s easy to pick up, hard to put down and well-suited to driving the points home in a concrete way that reading the outline by itself just can’t do. Every human being should own and know the principles of this book.

Fundamental Techniques In Handling People

  1. Don’t criticize, condemn or complain.
  2. Give honest and sincere appreciation.
  3. Arouse in the other person an eager want.

Six Ways to Make People Like You

  1. Become genuinely interested in other people.
  2. Smile.
  3. Remember that a person’s name is to that person the sweetest and most important sound in any language.
  4. Be a good listener. Encourage others to talk about themselves.
  5. Talk in terms of the other person’s interests.
  6. Make the other person feel important– and do it sincerely.

How to Win People to Your Way of Thinking

  1. The only way to get the best of an argument is to avoid it.
  2. Show respect for the other person’s opinions. Never say, “You’re wrong.”
  3. If you are wrong, admit it quickly and emphatically.
  4. Begin in a friendly way.
  5. Get the other person saying “Yes, yes” immediately.
  6. Let the other person do a great deal of the talking.
  7. Let the other person feel that the idea is his or hers.
  8. Try honestly to see from the other person’s point of view.
  9. Be sympathetic with the other person’s ideas and desires.
  10. Appeal to the nobler motives.
  11. Dramatize your ideas.
  12. Throw down a challenge.

Be a Leader: How to Change People Without Giving Offense Arousing Resentment

  1. Begin with praise and honest appreciation.
  2. Call attention to people’s mistakes indirectly.
  3. Talk about your own mistakes before criticizing the other person.
  4. Ask questions instead of giving direct orders.
  5. Let the other person save face.
  6. Praise the slightest improvement and praise every improvement. Be “hearty in your approbation and lavish in your praise.”
  7. Give the other person a fine reputation to live up to.
  8. Use encouragement. Make the fault seem easy to correct.
  9. Make the other person happy about doing the thing you suggest.

Review – Repeatability (#strategy, #business, @HarvardBiz)

Repeatability: Build Enduring Businesses for a World of Constant Change

by Chris Zook, James Allen, published 2012

What’s this book about?

I finished reading this book over three weeks ago. Since then, I have struggled to get myself to sit down and write a review. The primary reason I’ve struggled is because I am not sure I can say with confidence what this book is about, or to which genre it belongs. Is it about strategy? Business management? Business planning? Organizational theory? Something else?

“Repeatability” chants about simplicity, but it’s full of so many buzzwords, different-but-related ideas and proprietary-sounding business catchphrases that it’s hard at times to keep up. And perhaps I’ve dropped into the late middle of an earlier conversation, as the book references a “focus-expand-redefine” growth cycle elaborated upon in three earlier works known as “the trilogy”.

A more charitable explanation of my confusion might place the blame with the authors themselves. Take the way in which they describe the main shifts in strategy they say they are witnessing, which led them to write the book:

  1. less about a detailed plan and more about general direction and critical initiatives
  2. less about anticipating how change will occur, more about having rapid testing and learning processes to accelerate adaptation to change
  3. effective strategy increasingly indistinguishable from effective organization

The central insight from their research, the authors claim, is that,

complexity has become the silent killer of growth strategies

Why? The authors don’t take pains to explain or justify the assumption that the world is more complex and that “traditional” strategic notions no longer work in this new world order. They just accept it as common wisdom and run with solutions for responding to it.

Building “Great Repeatable Models”

The next several chapters detail what Zook and Allen call “Great Repeatable Models”, which are businesses defined by the following three principles:

  1. a strong, well-differentiated core
  2. clear nonnegotiables
  3. systems for closed-loop learning

According to the authors, GRMs (germs?) were

sharply, almost obviously, differentiated relative to competitors along a dimension that also allowed for differential profitability

which I think is another way of saying they have a lucrative competitive advantage.

Similarly, the authors suggest that nonnegotiables are a company’s

core values and the key criteria used to make trade-offs in decision making

while systems for closed-loop learning enabled GRMs to

drive continuous improvement across the business, leveraging transparency and consistency of their repeatable model

which I understood to mean that the businesses had a culture and process for improving their practices over time.

The Cult of the CEO

Chapter 5 of “Repeatability” seeks to demonstrate how the CEO is the guardian of the three principles of GRMs. While it clearly makes sense that the CEO, as the chief strategiest and top of the organizational pyramid would have a role in implementing and enforcing a GRM, the authors offer little here to help other than numerous examples of success and failure in following the three principles followed by a hopeful conclusion that the “right leadership” will be in place to manage the delicate balancing act they specify as ideal. It seems to place the book in the Cult of the CEO genre (idealizing the role and superhuman nature of corporate chief executives) while simultaneously causing much of their writing up to that point to seem extemporaneous.

It’s almost as if the presence of the “right leadership” implies the presence of a GRM, and the absence of a GRM implies the absence of the “right leadership.” The book suffers from hindsight bias and tautological reasoning like this in numerous areas.

My own simple interpretation

The central tenets of this book are confusing, poorly defined and at times self-contradictory. Its research methodology (inductive empirical study to explain complex social phenomena) is frowned on by this Austrian economist. Ironically, it is the occasional element touched upon at the periphery of the book’s argument, rather than its core, where the authors manage to share something meaningful to solving the dilemmas of business people.

Unfortunately, the encouragement to keep the distance between the CEO and the customer minimal and to articulate a simple vision that even lower-level employees can grasp and rally behind, for example, is rather intuitive and obvious. Why would adding layers of bureaucracy and arbitrary decision-making, or creating a business plan so elaborate your employees don’t understand it, ever be a sound practice?

There’s a lot here including many case studies and other reference materials, but not all of it is useful or makes sense when viewed through the prism of the Great Repeatable Model. For some the digging required to find the occasional nugget of wisdom may be worth it but I can’t recommend such exertion for everybody.


Video – Toby Carlisle, Q&A Notes at UC Davis Talk on Quantitative Value (@greenbackd, #QuantitativeValue)

Click here to watch the video (wear earphones and bring a magnifying glass)

UC Davis/Farnam Street Investments presents Toby Carlisle, founder and managing partner of Eyquem Investment Management and author of Quantitative Value, with Wes Gray

Normally I’d embed a video but I can’t seem to do that with the UC Davis feed. Also, these are PARAPHRASED notes to the Q&A portion of Toby’s talk only. I ignored the “lecture” portion which preceeded because I already think I get the gist of it from the book. I was mostly interested in covering his responses to the Q&A section.

The video is extremely poor quality, which is a shame because this is a great talk on a not-so-widely publicized idea. I wish there was a copy on YouTube with better audio and zoom, but no one put such a thing up, if it exists. I hope Toby does more interviews and talks in the future… hell, I’d help him put something together if it resulted in a better recording!

I had trouble hearing it and only thought to plug in some earbuds near the end. Prior to that I was contending with airplanes going overhead, refrigerator suddenly cycling into a loud cooling mode as well as my laptop’s maxed out tinny speakers contending with the cooling fans which randomly decided to cycle on and off at often the most critical moments. I often didn’t catch the question being asked, even when it wasn’t muffled, and chose to just focus on Toby’s response, assuming that the question would be obvious from that. That being said, I often conjoined questions and responses when there was overlap or similarity, or when it was easier for me to edit. This is NOT a verbatim transcript.

Finally, Toby recently created a beta forum for his book/website, at the Greenbackd Forum and I realize now in reviewing this talk that a lot of the questions I asked there, were covered here in my notes. I think he’s probably already given up on it, likely due to blockheads like me showing up and spamming him with simpleton questions he’s answered a million times for the Rubed Masses.

Major take-aways from the interview:

Q: Could we be in a “New Era” where the current market level is the “New Mean” and therefore there is nothing to revert to?

A: Well that’s really like saying stocks will revert down, not up. But how could you know? You could only look at historical data and go off of that, we have no way to predict ahead of time whether this “New Mean” is the case. I think this is why value investing continues to work, because at every juncture, people choose to believe that the old rules don’t apply. But the better bet has been that the world changes but the old rules continue to apply.

Q: So because the world is unknowable, do you compensate by fishing in the deep value ponds?

A: I like investing in really cheap stocks because when you get surprises, they’re good surprises. I find Buffett stocks terrifying because they have a big growth component in the valuation and any misstep and they get cut to pieces; whereas these cheap stocks are moribund for the most part so if you buy them and something good happens, they go up a lot.

Q: (muffled)

A: If you look at large cap stocks, the value effect is not as prevalent and the value premia is smaller. That’s because they’re a lot more efficient. There’s still only about 5% of AUM invested in value. But the big value guys portfolios look very similar; the value you have as a small investor is you don’t have to hold those stocks. So you can buy the smaller stuff where the value premia is larger. The institutional imperative is also very real. The idea of I’d like to buy 20 stocks, but I have to hold 45. That pushes you away from the optimal holdings for outperformance.

Q: (muffled)

A: The easiest way to stand out is to not run a lot of money. But no one wants to do that, everyone wants to run a lot of money.

Q: (muffled)

A: The model I follow is a bit more complicated than the Magic Formula. But there are two broad differences. I only buy value stocks, I only buy the cheapest decile and I don’t go outside of it, and then I buy quality within that decile. ROIC will work as a quality metric but only within the cheapest decile. ROIC is something Buffett talks about from a marketing perspective but I think in terms of raw performance it doesn’t make much sense. There’s definitely some persistence in ROIC, companies that have generated high returns on invested capital over long periods of time, tend to continue to do that.  If you have Warren Buffett’s genius and can avoid stepping on landmines, that can work. But if you don’t, you need to come up with another strategy.

Q: (muffled)

A: Intuition is important and it’s important when you’re deciding which strategy to use, but it’s not important when you’re selecting individual stocks. We can be overconfident in our assessment of a stock. I wonder whether all the information investors gather adds to their accuracy or to their confidence about their accuracy.

Q: (muffled)

A: All strategies have those periods when they don’t work. If you imagined you ran 4 different strategies in your portfolio, one is MF, one is cheap stocks, one of them is Buffett growth and one is special situations, and you just put a fixed amount of capital into each one [fixed proportion?] so that when one is performing well, you take the [excess?] capital out of it and put it into the one that is performing poorly, then you always have this natural rebalancing and it works the same way as equal-weighted stocks. And I think it’d lead to outperformance. It makes sense to have different strategies in the fund.

Q: (muffled)

A: QV says you are better off following an indexing strategy, but which market you index to is important. The S&P500 is one index you can follow, and there are simple steps you can follow to randomize the errors and outperform. But if you’re going to take those simple steps why not follow them to their logical conclusion and use value investing, which will allow you to outperform over a long period of time.

Q: (muffled)

A: Not everyone can beat the market. Mutual funds/big investors ARE the market, so their returns will be the market minus their fees. Value guys are 5% of AUM, can 5% outperform? Probably, by employing unusual strategies. Wes Gray has this thought experiment where he says if we return 20% a year, how long before we own the entire market? And it’s not that long. So there are constraints and all the big value investors find that once they get out there they all have the same portfolios so their outperformance isn’t so great. There’s a natural cap on value and it probably gets exceeded right before a bust. After a bust is then fertile ground for investment and that’s why you see all the good returns come right after the bust and then it trickles up for a period of time before there’s another collapse.

Q: (muffled)

A: I think the market is not going to generate great returns in the US, and I am not sure how value will do within that. That’s why my strategy is global. There are cheaper markets in other parts of the world. The US is actually one of the most expensive markets. The cheapest market in the developed world is Greece.

Q: Did you guys ever try to add a timing component to the formula? That might help you decide how to weight cash?

A: Yes, it doesn’t work. Well, we couldn’t get it to work. However, if you look at the yield, the yield of the strategy is always really fat, especially compared to the other instruments you could invest the cash in, so logically, you’d want to capture that yield and be fully invested. I think you should be close to fully invested.

Q: What about position sizing?

A: I equal weight. An argument can be made for sizing your cheaper positions bigger. I run 50 positions in the portfolio. In the backtest I found that was the best risk-adjusted risk-reward. That’s using Sortino and Sharpe ratios, which I don’t really believe in, but what else are you going to use? If you sized to 10 positions, you get better performance but it’s not better risk-adjusted performance. If you sized to 20 positions, you get slightly worse performance but better risk-adjusted performance. So you could make an argument for making a portfolio where your 5 best ideas were slightly bigger than your next 10 best, and so on, but I think it’s a nightmare for rebalancing. The stocks I look at act a little bit like options. They’re dead money until something happens and then they pop; so I want as much exposure to those as I can. I invest globally so the accounting regimes locally are a nightmare. IFRS, GAAP to me is foreign. You have to adjust the inputs to your screen for each country as a result of different accounting standards.

Q: digression

A: Japan is an interesting market. Everyone looks at Japan and sees the slump and says it’s terrifying investing in Japan but if you look at value in Japan, value has been performing really well for a really long time. So, if the US is in this position where it’s got a lot of govt debt and it’s going to follow a similar trajectory, you could look at Japan as a proxy and feel pretty good about value.

Q: (muffled)

A: I’ll take hot money, I am not in a position to turn down anyone right now. It’s a hard strategy [QV] to sell.

Q: (muffled)

A: Special situation investing is often a situation where you can’t find it in a screen, something is being spun out, you have to read a 10-K or 10-Q and understand what’s going to happen and then take a position that you wouldn’t be able to figure out from following a simple price ratio. It’s a good place to start out because it’s something you can understand and you can get an advantage by doing more work than everyone else. It’s not really correlated to the market. I don’t know whether it outperforms over a full cycle, but people don’t care because it performs well in a bad market like this.

Q: What kind of data do you use for your backtests?

A: Compustat, CRISP (Center for Research Into Securities Prices), Excel spreadsheets. You need expensive databases that have adjusted for when earnings announcements are made, that include adjustments that are made, that include companies that went bankrupt. Those kinds are expensive. They’re all filled with errors, that’s the toughest thing.

Review – How To Get Rich (@FelixDennis, #wealth, #entrepreneurialism, #books)

How To Get Rich: The Distilled Wisdom of One of Britain’s Wealthiest Self-Made Entrepreneurs

by Felix Dennis, published 2009

This will likely be one of the shortest reviews on record here. One reason is because I don’t want to spoil too much of this book for anyone else who might be interested in it; I do think it has to be fully read by oneself for it’s message to be understood.

Another reason is that I am not rich myself, so I don’t know how valuable my critical impressions of Dennis’s logic and experience will be and I don’t have any real opportunity to run a controlled experiment and find out. I’m going to take his thesis into mind and live my life as I see fit and maybe I’ll end up rich, or at least quite wealthy.

When Dennis says “rich” he means “filthy” rich. As in, it’d take several generations of slouches to piss through it all. This is the kind of rich he’s talking about. He’s not talking about retiring with a pension. And this book is psychological in that Dennis spends a lot of time detailing the mindset and motivations of people who are rich, not just particular strategies or actions to achieve this level of wealth (though he discusses that, too).

Besides the survey of rich life and rich worldviews, the book provides numerous general lessons on business, business management and entrepreneurial practices which are all valuable in their own right even if one doesn’t want to be rich, but doesn’t feel like being poor, either.

This book’s strongest point is honesty. And now, Felix Dennis’s “Eight Secrets to Getting Rich”:

  1. Analyze your need. Desire is insufficient. Compulsion is mandatory.
  2. Cut loose from negative influences. Never give in. Stay the course.
  3. Ignore ‘great ideas’. Concentrate on great execution.
  4. Focus. Keep your eye on the ball marked ‘The Money Is Here’/
  5. Hire talent smarter than you. Delegate. Share the annual pie.
  6. Ownership is the real ‘secret’. Hold on to every percentage point you can.
  7. Sell before you need to, or when bored. Empty your mind when negotiating.
  8. Fear nothing and no one. Get rich. Remember to give it all away.


Review – Professional Investor Rules (#investing, @harrimanhouse, #WallSt, #books)

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)


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.



Review – More Money Than God (#hedgefunds)

More Money Than God: Hedge Funds And The Making Of A New Elite

by Sebastian Mallaby, published 2010

A veritable pantheon of masters of the universe

Mallaby’s book is not just an attempt at explaining and defending the beginning, rise and modern state of the hedge fund industry (the US-focused part of it, anyway), but is also a compendium of all of the hedge fund world’s “Greatest Hits.” If you’re looking for information on what hedge funds are, where they come from, what they attempt to do, why they’re called what they are and how they should be regulated (SURPRISE! Mallaby initially revels in the success “unregulated” funds have had and feints as if he’s going to suggest they not be regulated but, it being a CFR book and he being a captured sycophant, he does an about-face right at the last second and ends up suggesting, well, umm, maybe SOME of the hedge funds SHOULD be regulated, after all) this is a decent place to start.

And if you want to gag and gog and salivate and hard-to-fathom paydays and multiple standard deviations away from norm profits, there are many here.

But that wasn’t my real interest in reading the book. I read it because I wanted to get some summary profiles of some of the most well known hedgies of our time — the Soroses and Tudor Joneses and such — and understand what their basic strategies were, where their capital came from, how it grew and ultimately, how they ended up. Not, “What’s a hedge fund?” but “What is this hedge fund?” As a result, the rest of this review will be a collection of profile notes on all the BSDs covered by the book.

Alfred Winslow Jones – “Big Daddy”

  • started out as a political leftist in Europe, may have been involved in U.S. intelligence operations
  • 1949, launches first hedge fund with $60,000 from four friends and $40,000 from his own savings
  • By 1968, cumulative returns were 5,000%, rivaling Warren Buffett
  • Jones, like predecessors, was levered and his strategy was obsessed with balancing volatilities, alpha (stock-picking returns) and beta (passive market exposure)
  • Jones pioneered the 20% performance fee, an idea he derived from Phoenician merchants who kept one fifth of the profits of successful voyages; no mgmt fee
  • Jones attempted market timing as a strategy, losing money in 1953, 1956 and 1957 on bad market calls; similarly, he never turned a profit following charts even though his fund’s strategy was premised on chartism
  • Jones true break through was harvesting ideas through a network of stock brokers and other researchers, paying for successful ideas and thereby incentivizing those who had an edge to bring him their best investments
  • Jones had information assymetry in an era when the investment course at Harvard was called “Darkness at Noon” (lights were off and everyone slept through the class) and investors waited for filings to arrive in the mail rather than walk down the street to the exchange and get them when they were fresh

Michael Steinhardt – “The Block Trader”

  • Background: between end of 1968 and September 30, 1970, the 28 largest hedge funds lost 2/3 of their capital; January 1970, approx. 150 hedge funds, down from 200-500 one year earlier; crash of 1973-74 wiped out most of the remainders
  • Steinhardt, a former broker, launches his fund in 1967, gained 12% and 28% net of fees in 1973, 74
  • One of Steinhardt’s traders, Cilluffo, who possessed a superstitious eating habit (refused to change what he ate for lunch when the firm was making money), came up with the idea of tracking monetary data, giving them an informational edge in an era where most of those in the trade had grown up with inflation never being higher than 2% which meant they ignored monetary statistics
  • One of Steinhardt’s other edges was providing liquidity to distressed institutional sellers; until the 1960s, stock market was dominated by individual investors but the 1960s saw the rise of institutional money managers; Steinhardt could make a quick decision on a large trade to assist an institution in a pinch, and then turn around and resell their position at a premium
  • Steinhardt’s block trading benefited from “network effects” as the more liquidity he provided, the more he came to be trusted as a reliable liquidity provider, creating a barrier to entry for his strategy
  • Steinhardt also received material non-public information: “I was being told things that other accounts were not being told.”
  • In December 1993, Steinhardt made $100M in one day, “I can’t believe I’m making this much money and I’m sitting on the beach” to which his lieutenants replied “Michael, this is how things are meant to be” (delusional)
  • As the Fed lowered rates in the early 90s, Steinhardt became a “shadowbank”, borrowing short and lending long like a bank
  • Steinhardt’s fund charged 1% mgmt fee and 20% performance fee
  • Anecdote: in the bloodbath of Japan and Canada currency markets in the early 90s, the Canadian CB’s traders called Steinhardt to check on his trading (why do private traders have communications with public institutions like CBs?)

Paul Samuelson & Commodities Corporation – “Fiendish Hypocrite Jackass” (my label)

  • Paul Samuelson is one of history’s great hypocrites, in 1974 he wrote, “Most portfolio decision makers should go out of business– take up plumbing, teach Greek, or help produce the annual GNP by serving corporate executives. Even if this advice to drop dead is good advice, it obviously is not counsel that will be eagerly followed.”
  • Meanwhile, in 1970 he had become the founding backer of Commodities Corporation and also investing in Warren Buffett; he funded his investment in part with money from his Nobel Prize awarded in the same year
  • Samuelson paid $125,000 for his stake; total start-up capital was $2.5M
  • Management of fund resembled AW Jones– each trader was treated as an independent profit center and was allocated capital based on previous performance
  • Part of their strategy was built on investor psychology: “People form opinions at their own pace and in their own way”; complete rejection of EMH, of which Samuelson was publicly an adherent
  • Capital eventually swelled to $30M through a strategy of primarily trend-surfing on different commodity prices; in 1980 profits were $42M so that even net of $13M in trader bonuses the firm outearned 58 of the Fortune 500
  • Trader Bruce Kovner on informational assymetries from chart reading: “If a market is behaving normally, ticking up and down within a narrow band, a sudden breakout in the absence of any discernible reason is an opportunity to jump: it means that some insider somewhere knows information that the market has yet to understand, and if you follow that insider you will get in there before the information becomes public”

George Soros – “The Alchemist”

  • Soros had an investment theory called “reflexivity”: that a trend could feedback into itself and magnify until it became unavoidable, usually ending in a crash of some sort
  • Soros launched his fund in 1973, his motto was “Invest first, investigate later”
  • Soros quotes: “I stood back and looked at myself with awe: I saw a perfectly honed machine”; “I fancied myself as some kind of god or an economic reformer like Keynes”
  • Soros was superstitious, he often suffered from back pains and would “defer to these physical signs and sell out his positions”
  • Soros believed in generalism: know a little about a lot of things so you could spot places where big waves were coming
  • Soros had a “a web of political contacts in Washington, Tokyo and Europe”
  • Soros hired the technical trader Stan Druckenmiller, who sometimes read charts and “sensed a panic rising in his gut”
  • As Soros’s fund increased in size he found it harder and harder to jump in and out of positions without moving the markets against himself
  • Soros rejected EMH, which had not coincidentally developed in the 1950s and 1960s in “the most stable enclaves within the most stable country in the most stable era in memory”
  • Soros was deeply connected to CB policy makers– he had a one on one with Bundesbank president Schlesinger in 1992 following a speech he gave in Basel which informed Quantum fund’s Deutschemark trade
  • “Soros was known as the only private citizen to have his own foreign policy”; Soros once off-handedly offered Druckenmiller a conversation with Kissinger who, he claimed, “does know things”
  • Soros hired Arminio Fraga, former deputy governor of Brazil’s central bank, to run one of his funds; Fraga milked connections to other CB officials around the world to find trade ideas, including the number two official at the IMF, Stanley Fischer, and a high-ranking official at the central bank of Hong Kong
  • Soros was a regular attendee at meetings of the World Bank and IMF
  • Soros met Indonesian finance minister Mar’ie Muhammed at the New York Plaza hotel during the Indonesian financial crisis
  • Soros traveled to South Korea in 1998 as the guest of president-elect Kim Dae-jung
  • In June 1997, Soros received a “secret request” for emergency funding from the Russian government, which resulted in him lending the Russian government several hundred million dollars
  • Soros also had the ear of David Lipton, the top international man at the US Treasury, and Larry Summers, number 2 at the Treasury, and Robert Rubin, the Treasury secretary, as well as Mitch McConnell, a Republican Senator

Julian Robertson – “Top Cat”

  • Managed a portfolio of money managers, “Tigers”
  • Used fundamental and value analysis
  • Once made a mental note to never buy the stock of an executive’s company after watching him nudge a ball into a better position on the golf green
  • Robertson was obsessed with relative performance to Soros’s Quantum Fund
  • Called charts “hocus-pocus, mumbo-jumbo bullshit”
  • Robertson didn’t like hedging, “Why, that just means that if I’m right I’m going to make less money”
  • High turnover amongst analysts, many fired within a year of hiring
  • Tiger started with $8.5M in 1980
  • A 1998 “powwow” for Tiger advisers saw Margaret Thatcher and US Senator Bob Dole in attendance
  • Tiger assets peaked in August 1998 at $21B and dropped to $9.5B a year later, $5B of which was due to redemptions (Robertson refused to invest in the tech bubble)

Paul Tudor Jones – “Rock-And-Roll Cowboy”

  • Jones started out as a commodity trader on the floor of the New York Cotton Exchange; started Tudor Investment Corporation in 1983, in part with an investment of $35,000 from Commodities Corporation
  • “He approached trading as a game of psychology and high-speed bluff”
  • Superstition: “These tennis shoes, the future of this country hangs on them. They’ve been good for a point rally in bonds and about a thirty-dollar rally in stocks every time I put them on.”
  • Jones was a notorious chart reader and built up his theory of the 1987 crash by lining up recent market charts with the 1929 chart until the lines approximately fit
  • Jones was interested in Kondratiev wave theory and Elliott wave theory
  • “When you take an initial position, you have no idea if you are right”but rather you “write a script for the market” and then if the market plays out according to your script you know you’re on the right track
  • Jones made $80-100M for Tudor Investment Corp on Black Monday; “The Big Three” (Soros, Steinhardt and Robinson) all lost heavily in the crash
  • Jones, like Steinhardt, focused on “institutional distortions” where the person on the other side of the trade was a forced seller due to institutional constraints
  • Jones once became the catalyst for his own “script” with an oil trade where he pushed other traders around until they panicked and played out just as he had predicted
  • PTJ never claimed to understand the fundamental value of anything he traded
  • PTJ hired Sushil Wadhwani in 1995, a professor of economics and statistics at the LSE and a monetary policy committee member at the Bank of England
  • PTJ’s emerging market funds lost 2/3rd of their value in the aftermath of the Lehman collapse

Stanley Druckenmiller – “The Linebacker” (my title)

  • Druckenmiller joined Soros in 1988; while Soros enjoyed philosophy, Druckenmiller enjoyed the Steelers
  • He began as an equity analyst at Pittsburgh National Bank but due to his rapid rise through the ranks he was “prevented from mastering the tools most stock experts take for granted” (in other words, he managed to get promoted despite himself, oddly)
  • Survived crash of 1987 and made money in the days afterward
  • Under Druckenmiller, Quantum AUM leaped from $1.8B to $5B to $8.3B by the end of 1993
  • Druckenmiller stayed in touch with company executives
  • Druckenmiller relied on Robert Johnson, a currency expert at Bankers Trust, whose wife was an official at the New York Fed, for currency trade ideas; Johnson himself had once worked on the Senate banking committee and he was connected to the staff director of House Financial Services Committee member Henry Gonzalez
  • Druckenmiller was also friends with David Smick, a financial consultant with a relationship with Eddie George, the number 2 at the Bank of England during Soros and Druckenmiller’s famous shorting of the pound
  • Druckenmiller first avoided the Dot Com Bubble, then jumped aboard at the last minute, investing in “all this radioactive shit that I don’t know how to spell”; he kept jumping in and out until the bubble popped and he was left with egg on his face, ironic because part of his motivation in joining in was to avoid losing face; Druckenmiller had been under a lot of stress and Mallaby speculates that “Druckenmiller had only been able to free himself by blowing up the fund”

David Swensen & Tom Steyer – “The Yale Men”

  • Swensen is celebrated for generating $7.8B of the $14B Yale endowment fund
  • Steyer and his Farallon fund were products of Robert Rubin’s arbitrage group at Goldman Sachs; coincidence that Rubin proteges rose to prominence during the time Rubin was in the Clinton administration playing the role of Treasury secretary?
  • Between 1990 and 1997 there was not a single month in which Steyer’s fund lost money (miraculous)
  • Farallon somehow got access to a government contact in Indonesia who advised Bank Central Asia would be reprivatized soon and Farallon might be able to bid for it
  • Some rumors claimed Farallon was a front for the US government, or a Trojan horse for Liem Sioe Liong (a disgraced Indonesian business man); it is curious that Yale is connected to the CIA, Farrallon is connected to Yale

Jim Simons & Renaissance Capital – “The Codebreakers”

  • Between the end of 1989 and 2006, the flagship Medallion fund returned 39% per annum on average (the fund was named in honor of the medals Simons and James Ax had won for their work in geometry and number theory– named in honor of an honor, in other words)
  • Jim Simons had worked at the Pentagon’s secretive Institute for Defense Analyses (another possible US intelligence operative turned hedgie?)
  • Simons strategy was a computer-managed trend following system which had to be continually reconfigured due to “Commodities Corporation wannabes” crowding the trades by trending the trends
  • Simons looked to hire people who “would approach the markets as a mathematical puzzle, unconnected to the flesh and blood and bricks and mortar of a real economy” (this is distinctly different than the Graham/Buffett approach, and one wonders how this activity is actually economically valuable in a free market)
  • “The signals that we have been trading without interruption for fifteen years make no sense. Otherwise someone else would have found them.”
  • Renaissance treated employee NDAs like a wing of the CIA– anyone who joined could never work elsewhere in the financial industry afterward, and for this reason they specifically avoided hiring from Wall St in the first place; they were required to invest a fifth of their pay in the Medallion Fund and was locked up as bail payment for four years after they departed (money hostage)

David Shaw & D.E. Shaw

  • Began trading in 1988, the same year as the Medallion fund
  • Shaw was originally hired by MoStan in 1986 into their Analytical Proprietary Trading unit which aimed at beating Steinhardt at his block-trading game using predictive computer technology
  • In 1994, Shaw’s 135-member firm accounted for 5% of the daily turnover on the NYSE
  • Jeff Bezos, of Amazon, was originally a DE Shaw employee
  • The strategy was heavily reliant on pair-trade “arbitrage”, looking for securities in similar industries which were temporarily misaligned in price/multiple
  • Circle of competence: in 1995 the firm launched the ISP Juno Online, as well as FarSight, an online bank and brokerage venture

Ken Griffin & Citadel

  • Created in 1990, grew to $15B AUM and 1400 employees by 2008
  • Griffin’s goal was to develop an investment bank model that could compete with traditional, regulated ibanks, but which was actually a hedge fund
  • Flagship funds were down 55% at the end of 2008, losing $9B (the equivalent of two LTCMs)

John Paulson

  • Paulson graduated from HBS in 1980 and went to work for Bear Stearns; he launched his hedge fund in 1994 with initial capital of $2M which grew to $600M by 2003; by 2005 he was managing $4B
  • Paulson’s main strategy was capital-structure arbitrage
  • He looked for “capitalism’s weak spot”, the thing that would blow up the loudest and fastest if the economy slowed even a little; cyclical industries, too much debt, debt sliced into senior and junior tranches, risk concentrated
  • Paulson spent $2M on research related to the US mortgage industry, assembling a proprietary database of mortgage figures and statistics
  • Many of Paulson’s investors doubted him and threatened to pull capital in 2006
  • Paulson enlarged his bets against the mortgage market through derivative swaps on the ABX (a new mortgage index) and eventually acquired over $7.2B worth of swaps; a 1% decline in the ABX earned Paulson a $250M profit, in a single morning he once netted $1.25B
  • By 2007, he was up 700% net of fees, $15B in profits and made himself $3-4B


I’m actually even more bored with this book having finished typing out my notes than I was when I finished the book the first time I read it. The book actually has some great quotes in it, from the insane delusions of grandeur of government officials and central bank functionaries, to wild facts and figures about the statistical trends of the hedge fund and financial industries over the last 60 years. I am too exhausted to go back and type some of it out right here even though I kind of wish I had some of the info here even without an idea of what I’d use it for anytime soon.

My biggest takeaway from MMTG is that most of these masters of the universe have such huge paydays because they use leverage, not necessarily because they’re really good at what they do. Many of their strategies actually involve teasing out extremely small anomalies between asset prices which aren’t meaningful without leverage. And they’re almost uniformly without a meaningful and logically consistent understanding of what risk is– though many are skeptics of EMH, they seem to all see risk as volatility because volatility implies margin calls for levered traders.

There were so many displays of childish superstition. Many of these guys are chart readers. The government intelligence backgrounds of many was creepy. And it was amazing how many relied on informational asymmetries which are 100% illegal for the average investor. These people really travel in an elite, secretive world where everyone is scratching each other’s backs. How many one on one conversations have you had with central bank presidents? How many trips to foreign countries have you been on where you were the invited guest of the head dignitary of the country? Are you starting to put the picture together like I am?

Overall, it seems so arbitrary. The best word that comes to mind to describe these titans and their success is– “marginalism”. We have lived in an inflationary economy for the last 60+ years and these players all seem to excel in such an environment. But inflationism promotes marginalism; the widespread malinvestment of perpetual inflation confuses people looking to engage in real, productive economic activity, and paper shuffling necessarily becomes a high value business.

The author himself is incredibly ignorant of economic fundamentals and the role monetary intervention plays in the economy. All of the various crises these hedgies profited from seem to come out of nowhere according to his narrative. The incredible growth in volumes of money managed by the hedge fund industry over time goes without notice, as if it was just a simple, unexceptional fact of life. Shouldn’t that be interesting? WHY ARE THERE HUNDREDS OF FIRMS MANAGING TENS OF BILLIONS OF DOLLARS EACH? Where did all this money come from?!

That makes the book pretty worthless as it’s key.

One thing that does strike me is that many of the most successful, most levered trades of Soros, Druckenmiller and others were related to currencies. These guys are all Keynesians but they probably don’t fully believe their own economic theories. However, they do understand them well enough to make huge plays against the dope money managers who DO put all their credence into what they learned at university. I should think an Austrian econ-informed large cap macro fund would have quite a time of it playing against not only the dopes, but the Soroses of the world– they’ll get their final comeuppance as this system of artificial fiat exchange finally unwinds over the next decade.

And, little surprise, the guy with the nearly perfect trading record for almost a decade (Farrallon) was involved in arbitrage trades.

Trend following is for slaves. It may have proven to be a profitable strategy (with gobs of leverage) for the contemporary crop of hedgies but I feel fairly confident in saying most of these guys will get hauled out behind the woodshed in due time if they keep it up, to the extent their strategies truly are reliant on mystic chart reading and nothing more.

Bon voyage!


Notes – A Compilation Of Ideas On Investing (@geoffgannon, #ncav, #netnet, #valueinvesting)

Why I’d Never Pay More Than Book Value For Nokia

  • You hate to see a group of the top five companies of an industry where they entered the industry at different times; this implies companies are coming and going as they please
  • You want the company you’re looking at to have a relatively high market share, ie, the company’s market share divided by the next closest competitor is high (1.5+)
  • The first line of defense in competitive environments is having the most customers relative to the alternatives; being the preferred product
  • As long as you believe a company’s competitive positions are lasting, you can buy the stock on a P/E basis

Ben Graham Net-Nets That Don’t File With The SEC

  • The simplest way to separate safe net-nets from unsafe net-nets is the number of consecutive years of profits
  • Profitable net-nets seem to be especially common candidates for abandoning the responsibilities of a public company without actually getting taken private
  • If you can’t trust the controlling family, you can’t trust the auditors

Free Cash Flow Isn’t Everything

  • Buffett-style approximation of unleveraged return on tangible equity: EBIT/(Receivables + Inventory + PPE) – (Accounts Payable + Accrued Expenses)
  • This represents the net investment; in the example of WMT, it represents their ability to finance $50B in productive assets at 0% interest
  • Reinvestment in businesses with sustainable double-digit ROIs is superior to receiving dividends (thanks to higher FCF)
  • It is harder to find companies who can earn high returns on unlevered equity and increase the size of that tangible equity over time than it is to find companies who can earn high returns on unleveraged tangible equity
  • For looking at return on invested tangible assets: EBITDA/(Receivables + Inventory + PPE) – (Accounts Payable + Accrued Expenses)
    • then, go back 15-20 years and find range, median, etc.
    • examine how much tends to be converted to net income or FCF to get an idea of profitability
  • FCF != Owner’s Earnings; only counting the cash available after a company grows will result in you passing up many good, growing businesses simply because they’re growing
  • If a company is earning good returns on their investments, it’s okay for them to not produce a lot of FCF
  • Businesses you’re investing in for profitable future growth should be 150% of the growth you think you could provide with another use of the money; the 50% represents margin of safety in your future compounding
  • Over time, more reliable returns compound better than less reliable returns
  • The most reliable ROIs tend to be in businesses built around a habit
  • Habits are the first line of defense in a business
  • The best business defenses involve:
    • defending specific customers
    • defending specific locations
    • defending specific times
  • Buffetts favorites are business which:
    • have pricing power
    • have the lowest costs (can operate profitably at margins competitors can not)
  • Your return in a good business, held forever, depends on:
    • Growth; what quantity of earnings are you purchasing today?
    • ROI; how much room is there for reinvesting those earnings in the future?
    • Earnings yield; what will you earn on those reinvested earnings?

Earnings Yield or Free Cash Flow Yield: Which Should You Use?

  • Look to the story of Hetty Green; don’t put more into an asset unless the return you can get from that addition is better than what you could get elsewhere
  • A company that grows value doesn’t have to pay anything out; with real Owner’s Earnings, no FCF is necessary
  • FCF is useful for determining how much money is available for:
    • Dividends
    • Stock buybacks
    • Debt repayment
    • Acquisitions
  • In this case, use FCF/Market Cap to determine your “equity coupon”
  • Owner’s Earnings is useful for determining: How much bigger will my snowball get this year?
  • OE are just as valuable as FCF if and only if the future return on retained earnings is comparable to the average of the past; the wider the moat, the more reliable the historical average is
  • If you think you can earn 10% in your brokerage account:
    • a company earning 12% unlevered returns on tangible net assets is probably a wash and it’d be better if they gave them to you
    • but a company earning 20% is a different beast altogether– you’re probably better off letting them compound your money for you
  • If you know ROI will stay above what you could achieve yourself, use a P/E type measure (or EV/EBIT or EV/EBITDA, depending on accounting) to price the stock, don’t use FCF
  • Valuing businesses by ROI:
    • By earnings; reliably above average returns on investment
    • By FCF; consistent companies with a mixed or impossible to evaluate ROI situation
    • By tangible book; inconsistent companies with an unreliable or poor ROI situation
  • Stated another way:
    • Good, reliable companies are snowballs; worth what it can grow as it travels downhill; dynamic
    • Mixed, reliable companies are waterfalls; worth the rate of its flow; constant
    • Unreliable, bad companies are rocks; worth its weight; static
  • Remember– assets produce earnings; earnings become assets; the process repeats
  • Ask yourself:
    • What is the sustainable rate of cash removable from the business?
    • What is the value added or subtracted from the business by the resource use decisions of management?
  • Assume that retained earnings at subpar businesses to be worth less than their stated amount; similarly, retained earnings at above average businesses are worth every penny
  • With great businesses with favorable long-term prospects, treat earnings as FCF; it’s fine to use the earnings yield
  • Never make the mistake of thinking depreciation is a provision for the future; it’s a spreading out of the past
  • At bad businesses, cash is worth much more than inventory, receivables, property, etc.; in these cases, don’t use earnings yield, use FCF yield and asset value

How To Analyze Net-Nets Undergoing Change

  • As part of a group, you can easily invest in businesses undergoing change
  • “Managers rarely rush to evacuate excess capital from a sinking ship. Usually, they’re still there trying to save the wreck.”
  • It’s generally better to invest in a corporation undergoing change than a business undergoing change
  • With changing customer habits, it can be nearly impossible to predict future earnings
  • I require at least ten years of history before investing in a company for any reason other than its cash; prefer 15-20 years of history whenever possible
  • Overcapitalized companies undergoing change are good stocks to follow
  • Worldwide, there are fewer investors looking at Swedish stocks than US stocks; that’s an advantage if you’re looking at Swedish stocks, so use it

What Broker To Use When Buying International Stocks (Gannon On Investing)

  • Geoff uses a full service broker, but recommends Interactive Brokers or Noble Trading for most others looking to buy foreign stocks
  • If going with a full service shop:
    • personally know a broker ahead of time
    • give him your account with a clear understanding of what it is you want to do; try to negotiate a flat, guaranteed commission structure so you know how much it’ll cost you and he knows you’re worth the trouble
    • a good rule of thumb is 1% per roundtrip trade; it’d be greedy for the broker to ask for more than 2%
  • If a broker promised me it could buy any stock anywhere in the world for 2% of my assets per year, I’d take that deal
  • I look at my cost in a stock on an after-commission basis
  • “My broker won’t let me buy that stock” is never a valid excuse; if the broker won’t buy the stock, get a new broker
  • “Ben Graham said investing is most intelligent when it’s most businesslike. Business often means work”
  • Never let anything get in the way of buying the best bargains, especially not your broker

How To Find Cheap Foreign Stocks

  • Online research process for finding foreign stocks:
    • Screen for stocks in specific countries using the FT Screener
    • Check the business description, EV/EBITDA, etc., at Bloomberg
    • Look at the 10-year financial history at MSN Money
    • Go to the company’s website and read their annual reports
  • Bloomberg has the best worldwide coverage of stocks in their database
  • A good screen to start with at is a single digit P/E screen– just scoop up the simplest, most obvious bargains
  • Many European companies that aren’t too tiny trade in Germany
  • Use Google Translate if you’re having language issues
  • Beware of accounting differences:
    • US uses GAAP; insists on historical cost and does not permit revaluation of non-financial assets; in general, old US companies with lots of land and inventory (using LIFO) are more likely to contain “hidden assets”
    • RoW uses IFRS; PPE and investment property less likely to be carried on balance sheet at extremely low stated value; different way of valuing biological assets; never uses LIFO accounting for inventory; less likely to mask an asset’s liquidation value than GAAP
  • Good screen in the US due to GAAP accounting for depreciation: (Accumulated Depreciation /Tangible Book Value) * (Tangible Book Value/Market Cap) > 1; shows you the cheapest stocks relative to what a competitor would pay to own their assets; produces a real Ben Graham-type list
    • should also add: Tangible Book Value > Total Liabilities
    • and: Net Income > 0
  • Due to accounting differences, if you’re new to international investing, focus on earnings bargains, not asset bargains
    • It’s okay to buy companies that are cheap P/B if they have 10 yrs of consistent earnings
    • Otherwise, stick to low P/10yr avg earnings
  • Low EV/EBITDA is good to use around the world as it erases some differences in accounting
  • Good UK-specific screener– SharelockHolmes

How To Find Foreign Stocks: 13 Promising Companies From The U.K. (Gannon On Investing)

  • I went to the London Stock Exchange website; then I browsed stocks alphabetically
  • I was looking for potentially promising companies, regardless of price
  • In other countries, I start by looking for good businesses I can understand; the bar is higher overseas
  • Use the following process for finding promising companies:
    • At the LSE website:
      • clicked “fundamentals” tab
      • scrolled down to ROIC
      • looked for positive number in the double-digits
      • 20%+ ROIC over the last few years
    • Look the company up in Bloomberg
      • If you can’t understand the business description, throw it out
      • If it sounds like it has the potential to earn very high returns on capital, proceed
    • Looked up the annual report’s cash flow statement
      • CFO > CAPEX in each of the last several years
      • ie, should be generating FCF
    • For all the companies that qualify, download the past annual reports into a folder on desktop
    • Start reading annual reports from oldest to most recent
    • Then, appraise the value of the company, ideally without looking at the price first
      • 10x normal EBIT
      • 15x normal FCF
      • if the company is trading at least 25% below the value you appraised it at and you love the business, consider buying
  • Searching alphabetically is an old school, Buffett way of stock research
  • “Having to form your own opinions from scratch does wonders for investment analysis”; searching from scratch puts you in the best mindset to value a stock objectively
  • Three dependable ways to turn up great stock ideas:
    • Go through a list from A to Z
    • Read value investing blogs
    • Direct, personal experience with the company
  • Good UK value investing blogs:
  • “My best investments come from stocks I study and pass on due to price, only to buy the same stock some 4 or 5 years later when it has its Salad Oil Scandal moment”

5 Japanese Net-Nets: And How To Analyze Them

  • Net-net investing worked in actual practice in the 1930s and 1940s in the US; Japan is similar, but worse
  • Price and value determine your returns based on four factors:
    • Earnings yield (price)
    • ROI (profitability)
    • Sales growth (growth)
    • Dividend yield (dividends)
  • The lower the yield on the stock, the higher its earnings yield, growth and ROI need to be to justify investment
  • Japan is experiencing deflation of -0.7% while the US is experiencing inflation of 2.9% so you need to add 3.6% to all Japanese yields to get the equivalent in real terms in the US
  • A company’s real dividend yield is effectively a reduction in your hurdle rate
  • Japan is a low/no growth economy, so it makes sense to pay out earnings as dividends or retain them as cash rather than tie them up in low-return, long-term investments such as PPE
  • The margin of safety in Japanese net-nets is that the dividend yield is a payback unrelated to ROI
  • With Japanese net-nets, you exchange low growth and low ROI for high dividend yields, deflation (rising cash value) and excess cash
  • Japanese net-nets offer P/E around 10, dividend yield around 3% and net cash close to market cap, meaning you get three bets:
    • the value of the stock’s future retained earnings stream
    • the value of the stock’s future dividend stream
    • the value of the stock’s future cash pile deployment
  • The biggest threat to Japanese net-nets is a decline in the value of the  yen; this is the best reason for passing on net-nets in Japan
  • “If half my money is in dollars and half is in something else and all 100% of my portfolio is in some of the cheapest stuff on earth– my results will be fine… over time”
  • The US in the 1930s is the best illustration of what net-net investing in Japan is like
  • “I prefer a lot of uncertain opportunities to make money over time to one seemingly certain exit strategy”
  • The quality of net-nets in the US is not as good as in Japan; most US net-nets are extremely unsafe; this is a consequence of a few good years in the stock market