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Archive for the ‘Value Investment’ Category

Simoleon Sense interviews James Montier

Posted in About, Net Current Asset Value, Stocks, Value Investment, tagged , , , on March 10, 2010| 3 Comments »

I’m a huge fan of James Montier’s work on the rationale for a quantitative investment strategy and global Graham net net investing. Miguel Barbosa of Simoleon Sense has a wonderful interview with Montier, covering his views on behavioral investing and value investment. Particularly interesting is Montier’s concept of “seductive details” and the implications for investors:

Miguel: Let’s talk about the concept of seductive details…can you give us an example of how investors are trapped by irrelevant information?

James Montier: The sheer amount of irrelevant information faced by investors is truly staggering. Today we find ourselves captives of the information age, anything you could possibly need to know seems to appear at the touch of keypad. However, rarely, if ever, do we stop and ask ourselves exactly what we need to know in order to make a good decision.

Seductive details are the kind of information that seems important, but really isn’t. Let me give you an example. Today investors are surrounded by analysts who are experts in their fields. I once worked with an IT analyst who could take a PC apart in front of you, and tell you what every little bit did, fascinating stuff to be sure, but did it help make better investment decisions, clearly not. Did the analyst know anything at all about valuing a company or a stock, I’m afraid not. Yet he was immensely popular because he provided seductive details.

Montier’s “seductive details” is reminiscent of the discussion in Nicholas Taleb’s Fooled by Randomness on the relationship between the amount of information available to experts, the accuracy of judgments they make based on this information, and the experts’ confidence in the accuracy of these judgements. Intuition suggests that having more information should increase the accuracy of predictions about uncertain outcomes. In reality, more information decreases the accuracy of predictions while simultaneously increasing the confidence that the prediction is correct. One such example is given in the paper The illusion of knowledge: When more information reduces accuracy and increases confidence (.pdf) by Crystal C. Hall, Lynn Ariss, and Alexander Todorov. In that study, participants were asked to predict basketball games sampled from a National Basketball Association season:

All participants were provided with statistics (win record, halftime score), while half were additionally given the team names. Knowledge of names increased the confidence of basketball fans consistent with their belief that this knowledge improved their predictions. Contrary to this belief, it decreased the participants’ accuracy by reducing their reliance on statistical cues. One of the factors contributing to this underweighting of statistical cues was a bias to bet on more familiar teams against the statistical odds. Finally, in a real betting experiment, fans earned less money if they knew the team names while persisting in their belief that this knowledge improved their predictions.

This is not an isolated example. In Effects of amount of information on judgment accuracy and confidence, by Claire I. Tsai, Joshua Klayman, and Reid Hastie, the authors examined two other studies that further that demonstrate when decision makers receive more information, their confidence increases more than their accuracy, producing “substantial confidence–accuracy discrepancies.” The CIA have also examined the phenomenon. In Chapter 5 of Psychology of Intelligence Analysis, Do you really need more information?, the author argues against “the often-implicit assumption that lack of information is the principal obstacle to accurate intelligence judgments:”

Once an experienced analyst has the minimum information necessary to make an informed judgment, obtaining additional information generally does not improve the accuracy of his or her estimates. Additional information does, however, lead the analyst to become more confident in the judgment, to the point of overconfidence.

Experienced analysts have an imperfect understanding of what information they actually use in making judgments. They are unaware of the extent to which their judgments are determined by a few dominant factors, rather than by the systematic integration of all available information. Analysts actually use much less of the available information than they think they do.

Click here to see the Simoleon Sense interview.

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$1,300 off regular Value Investing Congress West ticket price expires midnight (PST) on March 16

Posted in About, Stocks, Value Investment, tagged on March 9, 2010| Leave a Comment »

This is a reminder that our exclusive 30% discount for the Value Investing Congress expires at midnight (PST) on March 16, 2010. On March 17, 2010 the price will go up by $1,300. Join us at the 5th Annual Value Investing Congress West, May 4 & 5, 2010, to learn from some of the world’s most successful money managers. The all-star speakers will share invaluable insights on how to navigate today’s uncertain markets ….and present their best stock picks. The wisdom you’ll gain will enhance your investing results in 2010 and beyond.

If you’re unfamiliar with the Value Investing Congress, then here’s what you need to know: One good investment idea could more than pay your cost of admission to this event and net you some great returns. The wisdom gained listening to these great investors is difficult to overstate. For a slide show of last year’s event see HERE.

Confirmed speakers include:

  • Bruce Berkowitz, Fairholme Capital Management
  • Eric Sprott, Sprott Asset Management
  • Mohnish Pabrai, Pabrai Investment Funds
  • Paul Sonkin, The Hummingbird Value Funds
  • Thomas Russo, Gardner, Russo & Gardner
  • David Nierenberg, The D3 Family Funds
  • Lloyd Khaner, Khaner Capital
  • J. Carlo Cannell, Cannell Capital
  • Patrick Degorce, Thélème Partners
  • Whitney Tilson & Glenn Tongue, T2 Partners
  • Guy Spier, Aquamarine Fund
  • Amitabh Singhi, Surefin Investments
  • Richard Vogel, Alatus SA
  • Lei Zhang, Hillhouse Gaoling Capital Management

    Click here to receive the 30% discount to VIC

    You must use discount code: P10GB8 to receive the full discount. Hurry and register!

    You’ve got exactly one week to get signed up with these savings. The regular price of the two day event is $4,295. However, Greenbackd readers pay only $2,995. That’s a 30% discount and savings of $1,300!  If you’re from out of town, the Congress has also negotiated lower room rates at the Langham Huntington for attendees.

    It’s going to be an awesome and insightful event, to say the least. Make sure you get our exclusive discount for the Value Investing Congress here. Remember that you MUST use the discount code P10GB8 to receive the full discount!

    Please let me know if you have any questions or problems when trying to register with the discount code.

    Again, the early bird rate is expiring at midnight (PST) on March 16, 2010. On March 17, 2010 the price will go up by $1,300.

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    5 contrarian candidates for mean reversion

    Posted in About, Contrarian investment, Stocks, Value Investment, tagged , on March 9, 2010| Leave a Comment »

    Mean reversion is a favorite investment topic here on Greenbackd (see, for example, my posts on Mean reversion in earnings, Contrarian value investment and Lakonishok, Shleifer, and Vishny’s Contrarian Investment, Extrapolation, and Risk).

    The premise of contrarianism is mean reversion, which is the idea that stocks that have performed poorly in the past will perform better in the future and stocks that have performed well in the past will not perform as well. Benjamin Graham, quoting Horace’s Ars Poetica, described it thus:

    Many shall be restored that now are fallen and many shall fall that are now in honor.

    LSV argue in their paper that most investors don’t fully appreciate the phenomenon, which leads them to extrapolate past performance too far into the future. In practical terms it means the contrarian investor profits from other investors’ incorrect assessment that stocks that have performed well in the past will perform well in the future and stocks that have performed poorly in the past will continue to perform poorly.

    The outstanding Shadowstock blog has identified five “strong candidates for mean reversion.” To see John’s Shadowstock.com analysis, click here.

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    Doctorin’ the Tractatus

    Posted in About, Stocks, Value Investment, Warren Buffett, tagged , on March 8, 2010| 2 Comments »

    When I started out investing I summarized Warren Buffett’s letters to shareholders into a document I jokingly called the “Tractatus Logico-Valere.” The title, Latin errors aside, was intended to be an homage to Ludwig Wittgenstein’s Tractatus Logico-Philosophicus (which, according to Wikipedia, may in turn have been an homage to the Tractatus Theologico-Politicus by Baruch Spinoza). The idea was to create a comprehensive summary of Buffett’s investment process set out in a succinct, logical fashion. I kept Wittgenstein’s seventh and final proposition – “Whereof one cannot speak, thereof one must be silent” – as my own and interpreted it to mean “where you can’t value something, don’t invest” or “stay in your circle of competence.” My Tractatus wasn’t very good, and I’m not Warren Buffett’s shoelace. Consequently, I didn’t do very well with it. (Wittgenstein was not similarly burdened with self-doubt. Wikipedia says that he concluded that with his Tractatus he had resolved all philosophical problems, and upon its publication retired to become a schoolteacher in Austria.) My abortive experience attempting to create a comprehensive guide to earnings and growth-based investing has given me a great appreciation for those who are able to successfully create such a document and live by it. One investor who has done so is setting out his process for the world to see at The Fallible Investor.

    The author of The Fallible Investor is a private investor who has “previously worked for a private hedge fund in Bermuda and Bankers Trust in Sydney, Australia.” He calls himself The Fallible Investor because he “often makes errors when he invests, and says, “Recognising such a weakness is also useful. As Taleb says:

    Soros… knew how to handle randomness, by keeping a critical open mind and changing his opinions with minimal shame… he walked around calling himself fallible, but was so potent because he knew it while others had loftier ideas about themselves. He understood Popper. He lived the Popperian life.

    I have found particularly useful his elucidation of the linkage between return-on-invested-capital, market value, replacement value, and sustainable competitive advantage:

    I define the replacement value of a business as what the business’s assets would be worth if it’s ROIC was equal to its cost of capital.

    The market value of a business with a high ROIC and no sustainable competitive advantage should (assuming the market eventually prices a business at its intrinsic value[1]) fall to its replacement value. This should happen because if an incumbent business has a high ROIC, and no sustainable competitive advantage, other businesses will enter this industry, or expand within the industry, to seek these higher returns. These competitors will drive down the incumbent business’s profits until its ROIC declines to the average return of a commodity business. Once this occurs, the incumbent business can only be worth the cost of replacing the business’s assets.

    Professor Greenwald has another way of describing this process. He points out that if an incumbent business, with no competitive advantage, has a replacement value of $100 million and its market value is $200 million[2], competitors will drive its market value down to $100 million. Competitors will calculate that by spending $100 million to reproduce the assets of that business they can also create an enterprise with a market value higher than $100 million. These competitors will think, correctly, there is no reason for why they should have a different economic experience from the incumbent because there is nothing it can do that they cannot. Remember the incumbent business has no sustainable competitive advantage. Competitors, by reproducing the assets of the incumbent business, will increase the supply of products or services in the industry. There will now be more competition for the same business. Either prices will fall or, for differentiated products, each producer will sell fewer units. In both cases, the incumbent’s profits will decline and the market value of its business will decline with them. This process, capacity continuing to expand, and the profits and the market value of the incumbent’s business falling, will continue until the incumbent’s market value falls to the replacement value of its assets ($100 million). Its competitors will suffer the same fate.

    Greenwald points out that while this process does not happen smoothly or automatically it will eventually turn out this way. It happens because the incentives for businesspeople to take advantage of the market’s excessive valuation of the incumbent’s business are too powerful.[3]

    The market value of a business with a sustainable competitive advantage can, by contrast, stay much higher than its replacement value simply because it can sustain a high ROIC.

    [1] The intrinsic value of a business is what I think the business is worth to a rational businessperson.

    [2] Assuming the business has a high market value because it has a high ROIC.

    [3] P38, ‘Value Investing: From Graham To Buffett And Beyond’, Bruce Greenwald et al, 2001.

    The Fallible Investor has provided me with a full copy of his notes. I highly recommend following his posts as he sets out his investment process on the site.

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    Seth Klarman’s Twenty Investment Lessons of 2008

    Posted in About, Seth Klarman, Value Investment, tagged , on March 5, 2010| 2 Comments »

    Seth Klarman’s teachings, which I’ve covered on this site on several occasions (see, for example, Klarman on calculating liquidation value, on identifying catalysts, and on investing in liquidations), are always worth reading. In his most recent investor letter Klarman has provided a list of twenty investment lessons of 2008 (via the always superb Zero Hedge):

    1. Things that have never happened before are bound to occur with some regularity. You must always be prepared for the unexpected, including sudden, sharp downward swings in markets and the economy. Whatever adverse scenario you can contemplate, reality can be far worse.
    2. When excesses such as lax lending standards become widespread and persist for some time, people are lulled into a false sense of security, creating an even more dangerous situation. In some cases, excesses migrate beyond regional or national borders, raising the ante for investors and governments. These excesses will eventually end, triggering a crisis at least in proportion to the degree of the excesses. Correlations between asset classes may be surprisingly high when leverage rapidly unwinds.
    3. Nowhere does it say that investors should strive to make every last dollar of potential profit; consideration of risk must never take a backseat to return. Conservative positioning entering a crisis is crucial: it enables one to maintain long-term oriented, clear thinking, and to focus on new opportunities while others are distracted or even forced to sell. Portfolio hedges must be in place before a crisis hits. One cannot reliably or affordably increase or replace hedges that are rolling off during a financial crisis.
    4. Risk is not inherent in an investment; it is always relative to the price paid. Uncertainty is not the same as risk. Indeed, when great uncertainty – such as in the fall of 2008 – drives securities prices to especially low levels, they often become less risky investments.
    5. Do not trust financial market risk models. Reality is always too complex to be accurately modeled. Attention to risk must be a 24/7/365 obsession, with people – not computers – assessing and reassessing the risk environment in real time. Despite the predilection of some analysts to model the financial markets using sophisticated mathematics, the markets are governed by behavioral science, not physical science.
    6. Do not accept principal risk while investing short-term cash: the greedy effort to earn a few extra basis points of yield inevitably leads to the incurrence of greater risk, which increases the likelihood of losses and severe illiquidity at precisely the moment when cash is needed to cover expenses, to meet commitments, or to make compelling long-term investments.
    7. The latest trade of a security creates a dangerous illusion that its market price approximates its true value. This mirage is especially dangerous during periods of market exuberance. The concept of “private market value” as an anchor to the proper valuation of a business can also be greatly skewed during ebullient times and should always be considered with a healthy degree of skepticism.
    8. A broad and flexible investment approach is essential during a crisis. Opportunities can be vast, ephemeral, and dispersed through various sectors and markets. Rigid silos can be an enormous disadvantage at such times.
    9. You must buy on the way down. There is far more volume on the way down than on the way back up, and far less competition among buyers. It is almost always better to be too early than too late, but you must be prepared for price markdowns on what you buy.
    10. Financial innovation can be highly dangerous, though almost no one will tell you this. New financial products are typically created for sunny days and are almost never stress-tested for stormy weather. Securitization is an area that almost perfectly fits this description; markets for securitized assets such as subprime mortgages completely collapsed in 2008 and have not fully recovered. Ironically, the government is eager to restore the securitization markets back to their pre-collapse stature.
    11. Ratings agencies are highly conflicted, unimaginative dupes. They are blissfully unaware of adverse selection and moral hazard. Investors should never trust them.
    12. Be sure that you are well compensated for illiquidity – especially illiquidity without control – because it can create particularly high opportunity costs.
    13. At equal returns, public investments are generally superior to private investments not only because they are more liquid but also because amidst distress, public markets are more likely than private ones to offer attractive opportunities to average down.
    14. Beware leverage in all its forms. Borrowers – individual, corporate, or government – should always match fund their liabilities against the duration of their assets. Borrowers must always remember that capital markets can be extremely fickle, and that it is never safe to assume a maturing loan can be rolled over. Even if you are unleveraged, the leverage employed by others can drive dramatic price and valuation swings; sudden unavailability of leverage in the economy may trigger an economic downturn.
    15. Many LBOs are man-made disasters. When the price paid is excessive, the equity portion of an LBO is really an out-of-the-money call option. Many fiduciaries placed large amounts of the capital under their stewardship into such options in 2006 and 2007.
    16. Financial stocks are particularly risky. Banking, in particular, is a highly lever- aged, extremely competitive, and challenging business. A major European bank recently announced the goal of achieving a 20% return on equity (ROE) within several years. Unfortunately, ROE is highly dependent on absolute yields, yield spreads, maintaining adequate loan loss reserves, and the amount of leverage used. What is the bank’s management to do if it cannot readily get to 20%? Leverage up? Hold riskier assets? Ignore the risk of loss? In some ways, for a major financial institution even to have a ROE goal is to court disaster.
    17. Having clients with a long-term orientation is crucial. Nothing else is as important to the success of an investment firm.
    18. When a government official says a problem has been “contained,” pay no attention.
    19. The government – the ultimate short- term-oriented player – cannot with- stand much pain in the economy or the financial markets. Bailouts and rescues are likely to occur, though not with sufficient predictability for investors to comfortably take advantage. The government will take enormous risks in such interventions, especially if the expenses can be conveniently deferred to the future. Some of the price-tag is in the form of back- stops and guarantees, whose cost is almost impossible to determine.
    20. Almost no one will accept responsibility for his or her role in precipitating a crisis: not leveraged speculators, not willfully blind leaders of financial institutions, and certainly not regulators, government officials, ratings agencies or politicians.

    See also Klarman’s False Lessons of 2009.

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    Mike Burry’s Scion Capital investor letters

    Posted in About, Stocks, Value Investment, tagged , on March 4, 2010| 6 Comments »

    Dr. Michael Burry has received a great deal of well-deserved attention recently as a result of Michael Lewis’s The Big Short and the Vanity Fair article Betting on the Blind Side. Yesterday a reader provided a link to Burry’s techstocks.com “Value Investing” thread (now Silicon Investor) and today another reader has supplied a link to Burry’s Scion Capital investor letters. The site also sets out a time-line of Burry’s commentary on the financial crisis illustrating that, though it was not prevented, it was “eminently predictable and preventable”.

    Burry is a superb writer. Here is a brief extract from the first quarter 2001 letter:

    When I stand on my special-issue “Intelligent Investor” ladder and peer out over the frenzied crowd, I see very few others doing the same. Many stocks remain overvalued, and speculative excess – both on the upside and on the downside – is embedded in the frenzy around stocks of all stripes. And yes, I am talking about March 2001, not March 2000.

    In essence, the stock market represents three separate categories of business. They are, adjusted for inflation, those with shrinking intrinsic value, those with approximately stable intrinsic value, and those with steadily growing intrinsic value. The preference, always, would be to buy a long-term franchise at a substantial discount from growing intrinsic value.

    However, if one has been playing the buy-and-hold game with quality securities, one has been exposed to a substantial amount of market risk because the valuations placed on these securities have implied overly rosy scenarios prone to popular revision in times of more realistic expectation. This is one of those times, but it is my feeling that the revisions have not been severe enough, the expectations not yet realistic enough. Hence, the world’s best companies largely remain overpriced in the marketplace.

    The bulk of the opportunities remain in undervalued, smaller, more illiquid situations that often represent average or slightly above-average businesses – these stocks, having largely missed out on the speculative ride up, have nevertheless frequently been pushed down to absurd levels owing to their illiquidity during a general market panic. I will not label this Fund a “small cap” fund, for this may not be where the best opportunities are next month or next year. For now, though, the Fund is biased toward smaller capitalization stocks. As for the future, I can only say the Fund will always be biased to where the value is. If recent trends continue, it would not be surprising to find the stocks of several larger capitalization stocks with significant long-term franchises meet value criteria and hence become eligible for potential addition to the Fund.

     

    Buy my book The Acquirer’s Multiple: How the Billionaire Contrarians of Deep Value Beat the Market from on Kindle, paperback, and Audible.

    Here’s your book for the fall if you’re on global Wall Street. Tobias Carlisle has hit a home run deep over left field. It’s an incredibly smart, dense, 213 pages on how to not lose money in the market. It’s your Autumn smart read. –Tom Keene, Bloomberg’s Editor-At-Large, Bloomberg Surveillance, September 9, 2014.

    Click here if you’d like to read more on The Acquirer’s Multiple, or connect with me on Twitter, LinkedIn or Facebook. Check out the best deep value stocks in the largest 1000 names for free on the deep value stock screener at The Acquirer’s Multiple®.

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    Marty Whitman on value and corporate governance

    Posted in About, Liquidation Value, Net Current Asset Value, Stocks, Value Investment, tagged , , , , on March 3, 2010| Leave a Comment »

    The superb Manual of Ideas blog has an article by Ravi Nagarajan, Marty Whitman Reflects on Value Investing and Net-Nets, on legendary value investor Marty Whitman’s conversation with Columbia Professor Bruce Greenwald at the Columbia Investment Management Conference in New York. I have in the past discussed Marty Whitman’s adjustments to Graham’s net net formula, which I find endlessly useful. Whitman has some additional insights that I believe are particularly useful to net net investors:

    “Cheap is Not Sufficient”

    At several points in the discussion with Prof. Greenwald, Mr. Whitman came back to a central theme:  It is not sufficient for a security to be “cheap”.  It must also possess a margin of safety as demonstrated by a strong balance sheet and overall credit worthiness.   In other words, there are many securities that may appear cheap statistically based on a number of common criteria investors use to judge “cheapness”.  This might include current year earnings compared to the stock price, current year cash flow, and many others.  However, if the business does not have a durable balance sheet, adverse situations that are either of the company’s own making or due to macroeconomic factors can determine the ultimate fate of the company.  A durable balance sheet demonstrates the credit worthiness a business needs to manage through periodic adversity.

    Whitman also discusses an issue near and dear to my heart: good corporate governance, and, by implication, activism:

    One other point that Mr. Whitman made while discussing corporate governance also applies to many net-net situations.  The true value of a company may never come out if there is no threat of a change in control.  This obviously makes intuitive sense because the presence of a very cheap company alone will not result in realization of value unless management is willing to act in the interests of shareholders either by liquidating a business that has no future prospects but a very liquid balance sheet or taking steps to improve the business.

    Read the balance of the article at The Manual of Ideas blog.

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    Dr. Michael Burry and The Greatest Trade Ever

    Posted in About, Stocks, Value Investment, tagged , , on March 2, 2010| 12 Comments »

    Michael Burry is a value investor notable for being one of the first, if not the first, to short sub-prime mortgage bonds in his fund, Scion Capital. He figures prominently in the Gregory Zuckerman’s book, The Greatest Trade Ever, and also in The Big Short, Michael Lewis’s contribution to the sub-prime mortgage bond market crash canon. In Betting on the Blind Side, Lewis excerpts The Big Short, which describes Burry’s short position in some detail, how he figured out that the bonds were mispriced, and how he bet against them (no small effort because the derivatives to do so didn’t exist when he started looking for them. He had to “prod the big Wall Street firms to create them.”).

    Here Lewis describes Burry’s entry into value investing:

    Late one night in November 1996, while on a cardiology rotation at Saint Thomas Hospital, in Nashville, Tennessee, he logged on to a hospital computer and went to a message board called techstocks.com. There he created a thread called “value investing.” Having read everything there was to read about investing, he decided to learn a bit more about “investing in the real world.” A mania for Internet stocks gripped the market. A site for the Silicon Valley investor, circa 1996, was not a natural home for a sober-minded value investor. Still, many came, all with opinions. A few people grumbled about the very idea of a doctor having anything useful to say about investments, but over time he came to dominate the discussion. Dr. Mike Burry—as he always signed himself—sensed that other people on the thread were taking his advice and making money with it.

    Once he figured out he had nothing more to learn from the crowd on his thread, he quit it to create what later would be called a blog but at the time was just a weird form of communication. He was working 16-hour shifts at the hospital, confining his blogging mainly to the hours between midnight and three in the morning. On his blog he posted his stock-market trades and his arguments for making the trades. People found him. As a money manager at a big Philadelphia value fund said, “The first thing I wondered was: When is he doing this? The guy was a medical intern. I only saw the nonmedical part of his day, and it was simply awesome. He’s showing people his trades. And people are following it in real time. He’s doing value investing—in the middle of the dot-com bubble. He’s buying value stocks, which is what we’re doing. But we’re losing money. We’re losing clients. All of a sudden he goes on this tear. He’s up 50 percent. It’s uncanny. He’s uncanny. And we’re not the only ones watching it.”

    Mike Burry couldn’t see exactly who was following his financial moves, but he could tell which domains they came from. In the beginning his readers came from EarthLink and AOL. Just random individuals. Pretty soon, however, they weren’t. People were coming to his site from mutual funds like Fidelity and big Wall Street investment banks like Morgan Stanley. One day he lit into Vanguard’s index funds and almost instantly received a cease-and-desist letter from Vanguard’s attorneys. Burry suspected that serious investors might even be acting on his blog posts, but he had no clear idea who they might be. “The market found him,” says the Philadelphia mutual-fund manager. “He was recognizing patterns no one else was seeing.”

    Lewis discusses Burry’s perspective on value investing:

    “The late 90s almost forced me to identify myself as a value investor, because I thought what everybody else was doing was insane,” he said. Formalized as an approach to financial markets during the Great Depression by Benjamin Graham, “value investing” required a tireless search for companies so unfashionable or misunderstood that they could be bought for less than their liquidation value. In its simplest form, value investing was a formula, but it had morphed into other things—one of them was whatever Warren Buffett, Benjamin Graham’s student and the most famous value investor, happened to be doing with his money.

    Burry did not think investing could be reduced to a formula or learned from any one role model. The more he studied Buffett, the less he thought Buffett could be copied. Indeed, the lesson of Buffett was: To succeed in a spectacular fashion you had to be spectacularly unusual. “If you are going to be a great investor, you have to fit the style to who you are,” Burry said. “At one point I recognized that Warren Buffett, though he had every advantage in learning from Ben Graham, did not copy Ben Graham, but rather set out on his own path, and ran money his way, by his own rules.… I also immediately internalized the idea that no school could teach someone how to be a great investor. If it were true, it’d be the most popular school in the world, with an impossibly high tuition. So it must not be true.”

    Investing was something you had to learn how to do on your own, in your own peculiar way. Burry had no real money to invest, but he nevertheless dragged his obsession along with him through high school, college, and medical school. He’d reached Stanford Hospital without ever taking a class in finance or accounting, let alone working for any Wall Street firm. He had maybe $40,000 in cash, against $145,000 in student loans. He had spent the previous four years working medical-student hours. Nevertheless, he had found time to make himself a financial expert of sorts. “Time is a variable continuum,” he wrote to one of his e-mail friends one Sunday morning in 1999: “An afternoon can fly by or it can take 5 hours. Like you probably do, I productively fill the gaps that most people leave as dead time. My drive to be productive probably cost me my first marriage and a few days ago almost cost me my fiancée. Before I went to college the military had this ‘we do more before 9am than most people do all day’ and I used to think I do more than the military. As you know there are some select people that just find a drive in certain activities that supersedes everything else.” Thinking himself different, he didn’t find what happened to him when he collided with Wall Street nearly as bizarre as it was.

    And I love this story about his fund:

    In Dr. Mike Burry’s first year in business, he grappled briefly with the social dimension of running money. “Generally you don’t raise any money unless you have a good meeting with people,” he said, “and generally I don’t want to be around people. And people who are with me generally figure that out.” When he spoke to people in the flesh, he could never tell what had put them off, his message or his person. Buffett had had trouble with people, too, in his youth. He’d used a Dale Carnegie course to learn how to interact more profitably with his fellow human beings. Mike Burry came of age in a different money culture. The Internet had displaced Dale Carnegie. He didn’t need to meet people. He could explain himself online and wait for investors to find him. He could write up his elaborate thoughts and wait for people to read them and wire him their money to handle. “Buffett was too popular for me,” said Burry. “I won’t ever be a kindly grandfather figure.”

    This method of attracting funds suited Mike Burry. More to the point, it worked. He’d started Scion Capital with a bit more than a million dollars—the money from his mother and brothers and his own million, after tax. Right from the start, Scion Capital was madly, almost comically successful. In his first full year, 2001, the S&P 500 fell 11.88 percent. Scion was up 55 percent. The next year, the S&P 500 fell again, by 22.1 percent, and yet Scion was up again: 16 percent. The next year, 2003, the stock market finally turned around and rose 28.69 percent, but Mike Burry beat it again—his investments rose by 50 percent. By the end of 2004, Mike Burry was managing $600 million and turning money away. “If he’d run his fund to maximize the amount he had under management, he’d have been running many, many billions of dollars,” says a New York hedge-fund manager who watched Burry’s performance with growing incredulity. “He designed Scion so it was bad for business but good for investing.”

    Thus when Mike Burry went into business he disapproved of the typical hedge-fund manager’s deal. Taking 2 percent of assets off the top, as most did, meant the hedge-fund manager got paid simply for amassing vast amounts of other people’s money. Scion Capital charged investors only its actual expenses—which typically ran well below 1 percent of the assets. To make the first nickel for himself, he had to make investors’ money grow. “Think about the genesis of Scion,” says one of his early investors. “The guy has no money and he chooses to forgo a fee that any other hedge fund takes for granted. It was unheard of.”

    Hat tip Bo.

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    How P/E juices P/B returns

    Posted in About, Quantitative investment, Stocks, Value Investment, tagged , , on March 1, 2010| 3 Comments »

    As I’ve discussed in the past, P/B and P/E are demonstratively useful as predictors of future stock returns, and more so when combined (see, for example, LSV’s Two-Dimensional Classifications). As Josef Lakonishok, Andrei Shleifer, and Robert Vishny showed in Contrarian Investment, Extrapolation, and Risk, within the set of firms whose B/M ratios are the highest (in other words, the lowest price-to-book value), further sorting on the basis of another value variable – whether it be C/P, E/P or low GS – enhances returns. In that paper, LSV concluded that value strategies based jointly on past performance and expected future performance produce higher returns than “more ad hoc strategies such as that based exclusively on the B/M ratio.” A new paper further discusses the relationship between E/P and B/P from an accounting perspective, and the degree to which E/P and B/P together predict stock returns.

    The CXO Advisory Group Blog, fast becoming one of my favorite sites for new investment research, has a new post, Combining E/P and B/P, on a December 2009 paper titled “Returns to Buying Earnings and Book Value: Accounting for Growth and Risk” by Francesco Reggiani and Stephen Penman. Penman and Reggiani looked at the relationship between E/P and B/P from an accounting perspective:

    This paper brings an accounting perspective to the issue: earnings and book values are accounting numbers so, if the two ratios indicate risk and return, it might have something to do with accounting principles for measuring earnings and book value.

    Indeed, an accounting principle connects earnings and book value to risk: under uncertainty, accounting defers the recognition of earnings until the uncertainty has largely been resolved. The deferral of earnings to the future reduces book value, reduces short-term earnings relative to book value, and increases expected long-term earnings growth.

    CXO summarize the authors’ methodology and findings as follows:

    Using monthly stock return and firm financial data for a broad sample of U.S. stocks spanning 1963-2006 (153,858 firm-years over 44 years), they find that:

    • E/P predicts stock returns, consistent with the idea that it measures risk to short-term earnings.
    • B/P predicts stock returns, consistent with the idea that it measures accounting deferral of risky earnings and therefore risk to both short-term and long-term earnings. This perspective disrupts the traditional value-growth paradigm by associating expected earnings growth with high B/P.
    • For a given E/P, B/P therefore predicts incremental return associated with expected earnings growth. A joint sort on E/P and B/P discovers this incremental return and therefore generates higher returns than a sort on E/P alone, attributable to additional risk (see the chart below).
    • Results are somewhat stronger for the 1963-1984 subperiod than for the 1985-2006 subperiod.
    • Results using consensus analyst forecasts rather than lagged earnings to calculate E/P over the 1977-2006 subperiod are similar, but not as strong.

    CXO set out Penman and Reggiani’s “core results” in the following table (constructed by CXO from Penman and Reggiani’s results):

    The following chart, constructed from data in the paper, compares average annual returns for four sets of quintile portfolios over the entire 1963-2006 sample period, as follows:

    • “E/P” sorts on lagged earnings yield.
    • “B/P” sorts on lagged book-to-price ratio.
    • “E/P:B/P” sorts first on E/P and then sorts each E/P quintile on B/P. Reported returns are for the nth B/P quintile within the nth E/P quintile (n-n).
    • “B/P:E/P” sorts first on B/P and then sorts each B/P quintile on E/P. Reported returns are for the nth E/P quintile within the nth B/P quintile (n-n).

    Start dates for return calculations are three months after fiscal year ends (when annual financial reports should be available). The holding period is 12 months. Results show that double sorts generally enhance performance discrimination among stocks. E/P measures risk to short-term earnings and therefore short-term earnings growth. B/P measures risk to short-term earnings and earnings growth and therefore incremental earnings growth. The incremental return for B/P is most striking in low E/P quintile.

    The paper also discusses in some detail a phenomenon that I find deeply fascinating, mean reversion in earnings predicted by low price-to-book values:

    Research (in Fama and French 1992, for example) shows that book-to-price (B/P) also predicts stock returns, so consistently so that Fama and French (1993 and 1996) have built an asset pricing model based on the observation. The same discussion of rational pricing versus market inefficiency ensues but, despite extensive modeling (and numerous conjectures), the phenomenon remains a mystery. The mystery deepens when it is said that B/P is inversely related to earnings growth while positively related to returns; low B/P stocks (referred to as “growth” stocks) yield lower returns than high B/P stocks (“value” stocks). Yet investment professionals typically think of growth as risky, requiring higher returns, consistent with the risk-return notion that one cannot buy more earnings (growth) without additional risk.

    (emphasis mine)

    The paper adds further weight to the predictive ability of low price-to-book value and low price-to-earnings ratios. Its conclusion that book-to-price indicates expected returns associated with expected earnings growth is particularly interesting, and accords with the same findings in Werner F.M. DeBondt and Richard H. Thaler in Further Evidence on Investor Overreaction and Stock Market Seasonality.

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    Quantifying qualitative factors

    Posted in About, Quantitative investment, Stocks, Value Investment, tagged , , on February 23, 2010| 7 Comments »

    I’ve just finished Ian Ayres’s book Super Crunchers, which I found via Andrew McAfee’s Harvard Business Review blog post, The Future of Decision Making: Less Intuition, More Evidence (discussed in Intuition and the quantitative value investor). Super Crunchers is a more full version of James Montier’s 2006 research report, Painting By Numbers: An Ode To Quant, providing several more anecdotes in support of Montier’s thesis that simple statistical models outperform the best judgements of experts. McAfee discusses one such example in his blog post:

    Princeton economist Orley Ashenfleter predicts Bordeaux wine quality (and hence eventual price) using a model he developed that takes into account winter and harvest rainfall and growing season temperature. Massively influential wine critic Robert Parker has called Ashenfleter an “absolute total sham” and his approach “so absurd as to be laughable.” But as Ian Ayres recounts in his great book Supercrunchers, Ashenfelter was right and Parker wrong about the ‘86 vintage, and the way-out-on-a-limb predictions Ashenfelter made about the sublime quality of the ‘89 and ‘90 wines turned out to be spot on.

    Ayers provides a number of stories not covered in Montier’s article, from Don Berwick’s “100,000 lives” campaign, Epagogix’s hit movie predictor, Offermatica’s automated web ad serving software, Continental Airlines’s complaint process, and a statistical algorithm for predicting the outcome of Supreme Court decisions. While seemingly unrelated, all are prediction engines based on a quantitative analysis of subjective or qualitative factors.

    The Supreme Court decision prediction algorithm is particularly interesting to me, not because I am an ex-lawyer, but because the language of law is language, not often plain, and seemingly irreducible to quantitative analysis. (I believe this is true also of value investment, although numbers play a larger role in that realm, and therefore it lends itself more readily to quantitative analysis.) According to Andrew Martin and Kevin Quinn, the authors of Competing Approaches to Predicting Supreme Court Decision Making, if they are provided with just a few variables concerning the politics of a case, they can predict how the US Supreme Court justices will vote.

    Ayers discussed the operation of Martin and Quinn’s Supreme Court decision prediction algorithm in How computers routed the experts:

    Analysing historical data from 628 cases previously decided by the nine Supreme Court justices at the time, and taking into account six factors, including the circuit court of origin and the ideological direction of that lower court’s ruling, Martin and Quinn developed simple flowcharts that best predicted the votes of the individual justices. For example, they predicted that if a lower court decision was considered “liberal”, Justice Sandra Day O’Connor would vote to reverse it. If the decision was deemed “conservative”, on the other hand, and came from the 2nd, 3rd or Washington DC circuit courts or the Federal circuit, she would vote to affirm.

    Ted Ruger, a law professor at the University of Pennsylvania, approached Martin and Quinn at a seminar and suggested that they test the performance of the algorithm against a group of legal experts:

    As the men talked, they decided to run a horse race, to create “a friendly interdisciplinary competition” to compare the accuracy of two different ways to predict the outcome of Supreme Court cases. In one corner stood the predictions of the political scientists and their flow charts, and in the other, the opinions of 83 legal experts – esteemed law professors, practitioners and pundits who would be called upon to predict the justices’ votes for cases in their areas of expertise. The assignment was to predict in advance the votes of the individual justices for every case that was argued in the Supreme Court’s 2002 term.

    The outcome?

    The experts lost. For every argued case during the 2002 term, the model predicted 75 per cent of the court’s affirm/reverse results correctly, while the legal experts collectively got only 59.1 per cent right. The computer was particularly effective at predicting the crucial swing votes of Justices O’Connor and Anthony Kennedy. The model predicted O’Connor’s vote correctly 70 per cent of the time while the experts’ success rate was only 61 per cent.

    Ayers provides a copy of the flowchart in Super Crunchers. Its simplicity is astonishing: there are only 6 decision points, and none of the relate to the content of the matter. Ayers posits the obvious question:

    How can it be that an incredibly stripped-down statistical model outpredicted legal experts with access to detailed information about the cases? Is this result just some statistical anomaly? Does it have to do with idiosyncrasies or the arrogance of the legal profession? The short answer is that Ruger’s test is representative of a much wider phenomenon. Since the 1950s, social scientists have been comparing the predictive accuracies of number crunchers and traditional experts – and finding that statistical models consistently outpredict experts. But now that revelation has become a revolution in which companies, investors and policymakers use analysis of huge datasets to discover empirical correlations between seemingly unrelated things.

    Perhaps I’m naive, but, for me, one of the really surprising implications arising from Martin and Quinn’s model is that the merits of the legal arguments before the court are largely irrelevant to the decision rendered, and it is Ayres’s “seemingly unrelated things” that affect the outcome most. Ayres puts his finger on the point at issue:

    The test would implicate some of the most basic questions of what law is. In 1881, Justice Oliver Wendell Holmes created the idea of legal positivism by announcing: “The life of the law has not been logic; it has been experience.” For him, the law was nothing more than “a prediction of what judges in fact will do”. He rejected the view of Harvard’s dean at the time, Christopher Columbus Langdell, who said that “law is a science, and … all the available materials of that science are contained in printed books”.

    Martin and Quinn’s model shows Justice Oliver Wendell Holmes to be right. Law is nothing more than a prediction of what judges will in fact do. How is this relevant to a deep value investing site? Deep value investing is nothing more than a prediction of what companies and stocks will in fact do. If the relationship holds, seemingly unrelated things will affect the performance of stock prices. Part of the raison d’etre of this site is to determine what those things are. To quantify the qualitative factors affecting deep value stock price performance.

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