Shale gas is not a revolution. It’s just another play with a somewhat higher cost structure but larger resource base than conventional gas.
The marginal cost of shale gas production is $4/mmBtu despite popular but incorrect narratives that it is lower. The average spot price of gas has been $3.77 since shale gas became the sustaining factor in U.S. supply (2009-2017). Medium-term prices should logically average about $4/mmBtu.
A crucial consideration going forward, however, will be the availability of capital. Credit markets have been willing to support unprofitable shale gas drilling since the 2008 Financial Collapse. If that support continues, medium-term prices for gas may be lower, perhaps in the $3.25/mmBtu range. The average spot price for the last 7 months has been $3.13.
Gas supply models over the last 50 years have been consistentlywrong. Over that period, experts all agreed that existing conditions of abundance or scarcity would define the foreseeable future. That led to billions of dollars of wasted investment on LNG import facilities.
Today, most experts assume that gas abundance and low price will define the next several decades because of shale gas. This had led to massive investment in LNG export facilities.
(CSInvesting: You should read Mr. Berman’s full report at the link below. He uses history to debunk long-term prediction models and shows the common sense of looking at markets through the long lens of history. The assumption of abundant natural gas could be wrong–many “experts” are not even thinking of vastly different outcomes to their models.)
Has the meteoric rise of passive investing generated the “greatest bubble ever”?
The better we understand the baked-in biases of algorithmic investing, the closer we can come to answers.
The following article was originally published in “What I Learned This Week” on June 15, 2017. To learn more about 13D’s investment research, visit website. https://latest.13d.com/tagged/wiltw
In an article for Bloomberg View last week titled “Why It’s Smart to Worry About ETFs”, Noah Smith wrote the following prescient truth: “No one knows the basic laws that govern asset markets, so there’s a tendency to use new technologies until they fail, then start over.” As we explored in WILTW June 1, 2017, algorithmic accountability has become a rising concern among technologists as we stand at the precipice of the machine-learning age. For more than a decade, blind faith in the impartiality of math has suppressed proper accounting for the inevitable biases and vulnerabilities baked into the algorithms that dominate the Digital Age. In no sector could this faith prove more costly than finance.
The rise of passive investing has been well-reported, yet the statistics remain staggering. According to Bloomberg, Vanguard saw net inflows of $2 billion per day during the first quarter of this year. According to The Wall Street Journal, quantitative hedge funds are now responsible for 27% of all U.S. stock trades by investors, up from 14% in 2013. Based on a recent Bernstein Research prediction, 50% of all assets under management in the U.S. will be passively managed by early 2018.
In these pages, we have time and again expressed concern about the potential distortions passive investing is creating. Today, evidence is everywhere in the U.S. economy — record low volatility despite a news cycle defined by turbulence; a stock market controlled by extreme top-heaviness; and many no-growth companies seeing ever-increasing valuation divergences. As always, the key questions are when will passive strategies backfire, what will prove the trigger, and how can we mitigate the damage to our portfolios? The better we understand the baked-in biases of algorithmic investing, the closer we can come to answers.
Over the last year, few have sounded the passive alarm as loudly as Steven Bregman, co-founder of investment advisor Horizon Kinetics. He believes record ETF inflows have generated “the greatest bubble ever” — “a massive systemic risk to which everyone who believes they are well-diversified in the conventional sense are now exposed.”
Bregman explained his rationale in a speech at a Grant’s conference in October:
“In the past two years, the most outstanding mutual fund and holding- company managers of the past couple of decades, each with different styles, with limited overlap in their portfolios, collectively and simultaneously underperformed the S&P 500…There is no precedent for this. It’s never happened before. It is important to understand why. Is it really because they invested poorly? In other words, were they the anomaly for underperforming — and is it reasonable to believe that they all lost their touch at the same time, they all got stupid together? Or was it the S&P 500 that was the anomaly for outperforming? One part of the answer we know… If active managers behave in a dysfunctional manner, it will eventually be reflected in underperformance relative to their benchmark, and they can be dismissed. If the passive investors behave dysfunctionally, by definition this cannot be reflected in underperformance, since the indices are the benchmark.”
At the heart of passive “dysfunction” are two key algorithmic biases: the marginalization of price discovery and the herd effect. Because shares are not bought individually, ETFs neglect company-by-company due diligence. This is not a problem when active managers can serve as a counterbalance. However, the more capital that floods into ETFs, the less power active managers possess to force algorithmic realignments. In fact, active managers are incentivized to join the herd—they underperform if they challenge ETF movements based on price discovery. This allows the herd to crowd assets and escalate their power without accountability to fundamentals.
With Exxon as his example, Bregman puts the crisis of price discovery in a real- world context:
“Aside from being 25% of the iShares U.S. Energy ETF, 22% of the Vanguard Energy ETF, and so forth, Exxon is simultaneously a Dividend Growth stock and a Deep Value stock. It is in the USA Quality Factor ETF and in the Weak Dollar U.S. Equity ETF. Get this: It’s both a Momentum Tilt stock and a Low Volatility stock. It sounds like a vaudeville act…Say in 2013, on a bench in a train station, you came upon a page torn from an ExxonMobil financial statement that a time traveler from 2016 had inadvertently left behind. There it is before you: detailed, factual knowledge of Exxon’s results three years into the future. You’d know everything except, like a morality fable, the stock price: oil prices down 50%, revenue down 46%, earnings down 75%, the dividend-payout ratio almost 3x earnings. If you shorted, you would have lost money…There is no factor in the algorithm for valuation. No analyst at the ETF organizer—or at the Pension Fund that might be investing—is concerned about it; it’s not in the job description. There is, really, no price discovery. And if there’s no price discovery, is there really a market?”
We see a similar dynamic at play with quants. Competitive advantage comes from finding data points and correlations that give an edge. However, incomplete or esoteric data can mislead algorithms. So the pool of valuable insights is self-limiting. Meaning, the more money quants manage, the more the same inputs and formulas are utilized, crowding certain assets. This dynamic is what caused the “quant meltdown” of 2007. Since, quants have become more sophisticated as they integrate machine learning, yet the risk of overusing algorithmic strategies remains.
Writing about the bubble-threat quants pose, Wolf Street’s Wolf Richter pinpoints the herd problem:
“It seems algos are programmed with a bias to buy. Individual stocks have risen to ludicrous levels that leave rational humans scratching their heads. But since everything always goes up, and even small dips are big buying opportunities for these algos, machine learning teaches algos precisely that, and it becomes a self-propagating machine, until something trips a limit somewhere.”
As Richter suggests, there’s a flip side to the self-propagating coin. If algorithms have a bias to buy, they can also have a bias to sell. As we explored in WILTW February 11, 2016, we are concerned about how passive strategies will react to a severe market shock. If a key sector failure, a geopolitical crisis, or even an unknown, “black box” bias pulls an algorithmic risk trigger, will the herd run all at once? With such a concentrated market, an increasing amount of assets in weak hands have the power to create a devastating “sell” cascade—a risk tech giant stocks demonstrated over the past week.
With leverage on the rise, the potential for a “sell” cascade appears particularly threatening. Quant algorithms are designed to read market tranquility as a buy-sign for risky assets—another bias of concern. Currently, this is pushing leverage higher. As reported by The Financial Times, Morgan Stanley calculates that equity exposure of risk parity funds is now at its highest level since its records began in 1999.
This risk is compounded by the ETF transparency-problem. Because assets are bundled, it may take dangerously long to identify a toxic asset. And once toxicity is identified, the average investor may not be able to differentiate between healthy and infected ETFs. (A similar problem exacerbated market volatility during the subprime mortgage crisis a decade ago.) As Noah Smith writes, this could create a liquidity crisis: “Liquidity in the ETF market might suddenly dry up, as everyone tries to figure out which ETFs have lots of junk and which ones don’t.”
J.P. Morgan estimated this week that passive and quantitative investors now account for 60% of equity assets, which compares to less than 30% a decade ago. Moreover, they estimate that only 10% of trading volumes now originate from fundamental discretionary traders. This unprecedented rate of change no doubt opens the door to unaccountability, miscalculation and in turn, unforeseen consequence. We will continue to track developments closely as we try and pinpoint tipping points and safe havens. As we’ve discussed time and again with algorithms, advancement and transparency are most-often opposing forces. If we don’t pry open the passive black box, we will miss the biases hidden within. And given the power passive strategies have rapidly accrued, perpetuating blind faith could prove devastating.
A Reader’s question that I post below so the many intelligent folks that read this can chip in their thoughts….
The part that confuses me the most is this:
From what I gather, Greenblatt typically calculates his measurement of normal EBITDA – MCX. He then puts a conservative multiple on this, typically 8 or 10 times EBITDA-MCX. He says higher quality companies may deserve 12x or more. He often says something like “this is a 10% cash return that is growing at 6% a year. A growing income is worth much more than a flat income”. He seems to do this on page 309-310 of the notes you sent me complete-notes-on-special-sit-class-joel-greenblatt_2.
My question is: Greenblatt’s calculation of earnings (EBITDA – MCX) only includes the maintenance portion of capital expenditure. The actual cash flow may be lower because of growth capex. Yet he is assuming a 6% growing income. It seems strange to me that he calculates the steady-state income (no growth capex. Only Maintenance capex), but he assumes that the income will grow. It seems like he is assuming the income will grow 6% but doesn’t incude the growth capex in his earnings calculation. Is it logical to assume that the steady-state earnings will grow, but not deducting the cost of the growth capex from the earnings?
is not a malfunctioning entrepreneurial impulse, but an artificial lengthening of production and overcapacity in fixed assets induced by the fractional reserve banking system. Everyone who keeps funds in the market or in a bank is vulnerable, since it is cash deposits that banks use to fund the reckless expansion. When the banking system blows up—as it must—conservative savers lose their savings just as surely as ardent speculators: that is the real horror and also why the existence of a dynamic sector in the economy does not change the credit bubble analysis.
I wonder how Mr. Pabrai thinks the market misprices a security by 90%. It has been my experience that when you think you have a company priced at $10 per share but worth $100, you had better check your valuation. For a stock to go up 10 times, you are betting on profitable growth or a change in the environment.
The value of the video is given in the reminder to go through your value lines or stock guides to give you context and ideas! In the course I am designing, we will have access to Value-Line to constantly search.
Go where they ain’t (but patience is needed in huge dollops):
HEDGE FUND ANALYST QUIZ
Your boss calls you into his office and asks if the Fed should keep raising rates? Then he asks if the Fed should lower rates? What do you tell him? There is ONLY one correct answer. To KEEP your job you must answer correctly.
June 19, 2017
Hyman Minsky was an economist who popularised the idea that “stability leads to instability”. According to Minsky and his followers, credit expands rapidly during the good times to the point where a lot of borrowing is being done by financially fragile/vulnerable entities, thus sowing the seeds of a financial crisis. That’s why the start of a financial crisis is now often referred to as a “Minsky moment”. Unfortunately, Minsky’s analysis was far too superficial.
Minsky described a process during which financing becomes increasingly speculative. At the start, most of the debt that is taken on can be serviced and repaid using the cash flows generated by the debt-financed investment. At this stage the economy is robust. However, financial success and rising asset prices prompt both borrowers and lenders to take on greater risk, until eventually the economy reaches the point where the servicing of most new debt depends on further increases in asset prices. At this stage the economy is fragile, because anything that interrupts the upward trend in asset prices will potentially set in motion a large-scale liquidation of investments and an economic bust.
This description of the process is largely correct, but rather than drilling down in an effort to find the underlying causes Minsky takes the route of most Keynesians and assumes that the process occurs naturally. That is, underpinning Minsky’s analysis is the assumption that an irresistible tendency to careen from boom to bust and back again is inherent in the capitalist/market economy.
In the view of the world put forward by Keynesians in general and Minsky in particular, people throughout the economy gradually become increasingly optimistic for no real reason and eventually this increasing optimism causes them to take far too many risks. The proverbial chickens then come home to roost (the “Minsky moment” happens). It never occurs to these economists that while any individual could misread the situation and make an investing error for his own idiosyncratic reasons, the only way that there could be an economy-wide cluster of similar errors at the same time is if the one price that affects all investments is providing a misleading signal. The one price that affects all investments is, of course, the price of credit.
Prior to the advent of central banks the price of credit was routinely distorted by fractional reserve banking, which is not a natural part of a market economy. These days, however, the price of credit is distorted primarily by central banks, and the central bank is most definitely not a natural part of a market economy. Therefore, what is now often called a “Minsky moment” could more aptly be called a “central-bank moment”.
I expect the next “central-bank moment” to arrive within the coming 12 months. I also expect that when it does arrive it will generally be called a “Minsky moment” or some other name that deftly misdirects the finger of blame, and that central banks will generally be seen as part of the solution rather than what they are: the biggest part of the problem.
This time, the Fiat Chrysler CEO went a step further than usual by declaring that the latest plan for the company is essentially a one-way bet on cheap gas. Production of compact cars will end to free up production capacity for high-margin, low-mileage Jeeps and RAM trucks.
This, combined with Fiat’s more or less complete lack of a fuel economy or electrification strategy beyond buying emissions credits from other manufacturers “foolish” enough to produce electric and hybrid “compliance cars,” is quickly making Marchionne, if not an industry joke, then certainly yesterday’s man.
At least, that is what people are saying. I have an alternate hypothesis. The Auto Industry Is Not Heading to a Good Place (The author, in my opinion, has the correct thesis. Ride sharing, Uber, Tesla, more complex electronics mean less demand and more investment to run in place).
Fiat vs. Ford above
Fiat (FCAU) has done slightly better than GM and much better than Ford (F). However, the auto industry is in a bad place that will worsen.
The context is frightening. Global fuel economy and emissions regulations are becoming so strict that it is possible to meet them only with partial or full electrification of the automobile. And the existing automobile production system, based primarily on stamping sheet metal and amortizing heartbreaking development costs and capital expenditures over millions of units, is incredibly capital inefficient.
What’s more, the industry’s move towards electric vehicles represents a significant challenge to the traditional strategic landscape an automaker faces. An electric vehicle has drastically fewer moving parts than an internal combustion vehicle and is, by design, far more modular, meaning that barriers to new entrants are significantly lower.
Electric vehicles are also far more uniform in their driving dynamics, because there is little scope for refining an electric motor with one moving part. Swathes of engineering and marketing investments become irrelevant. And both ride-sharing enterprises and developments in automation seem increasingly likely to grow beyond niche markets into something properly disruptive to the car ownership business model.
Marchionne Knows This
Last year, Marchionne presented a uniquely critical slide deck about the way the auto industry destroys capital. His argument was that, unless the industry consolidates and stops duplicating engineering costs (e.g., every car manufacturer has its own separately developed but fundamentally identical 2.0L 4-cylinder petrol engine), then the market will eventually force its hand, having gotten sick of miserly returns on billions in investments.
The industry response to this slide deck was more or less complete agreement, with the caveat that competitors would not have to outlast the market so much as merely outlast Fiat Chrysler. Marchionne then pursued an odd and ultimately unsuccessful merger with GM’s Mary Barra, who confidently rejected Fiat Chrysler’s plan, noting, “We are merging with ourselves.” (This presumably referred to GM’s decades-long quest to bring rationality to its stable of brands.)
GM is not only merging with itself, it is also “disrupting” itself — as evidenced by their recently announced Chevy Bolt long-range, affordable electric car. The company claimed the Bolt was designed to be the perfect car for ride-sharing apps. Just before launching the Bolt, GM announced a $500 million investment into Lyft, the main competitor to Uber.
This no doubt surprised competitors who have been making efforts to disabuse markets and investors of the notion that they would become mere providers of hardware to ride-sharing companies like Uber or autonomous car suppliers like Google. Dieter Zetsche, CEO of Daimler, remarked “We do not plan to become the Foxconn of Apple.”
Manufacturers Are Going to Have to Invest
In fact, the bosses of Daimler, BMW, and Audi went looking behind the couch for some spare change to buy joint ownership of Nokia’s (remember them?) mapping service HERE, and did so primarily to stop their rival bidder – Uber – from buying it. High-resolution maps are crucial to autonomous cars; Uber’s CEO has said that, if Tesla can make good on their promise of a long-range, autonomous electric car, he would buy “all” of them.
The Germans are thus investing billions into electric vehicles made out of carbon fiber that pilot themselves using super-high resolution maps, all the while fighting back against Apple and Google’s requests for access to their cars’ infotainment systems. Their global leadership of the auto industry will have to be pried from their cold, dead hands.
Meanwhile, all the difficult bits of the Chevy Bolt (“custom-built” for Lyft, remember) are built in large part by Korea’s LG. One wonders why Lyft (or Uber) would not simply buy the next model directly from LG? I guess even if there is no Foxconn for cars yet, there may be soon. Remember, electric cars are far more modular than internal combustion cars.
Marchionne Says “No Thanks”
Or, if not him, then certainly the Agnelli family. A sort of Italian royalty who control Fiat Chrysler (and Marchionne) via their ownership of the Exor holding company, the Agnellis have been showing signs that they are tiring of the endless drama surrounding Fiat and the auto industry in general. They bought a stake in The Economist in 2015 in a move towards media, but the recent de-conglomeration of Fiat has been noticeable in other ways.
First, in 2013, Fiat’s industrial division was de-merged and combined with CNH Global (maker of tractors under the Case IH and New Holland brands) into a separate company, CNH Industrial. Most recently, Ferrari, the jewel in the Fiat Chrysler stable of brands, was floated in New York.
Speaking of Ferrari, Marchionne took advantage of a recent dip in the fortunes of Ferrari’s eponymous Formula 1 team to unceremoniously eject Luca di Montezemolo as president and chairman of Ferrari and replace him with . . . himself. It should be noted that di Montezemolo was appointed by Gianni Agnelli himself after the death of the founder, Enzo Ferrari, and is a bona fide business superstar in Italy. Marchionne has been playing an increasingly active part in the politics of Formula 1 recently, something that will no doubt continue to make for a less stressful (but still stimulating) retirement when Marchionne puts on his famous blue sweater for the last time in 2018.
But for now, Marchionne has seen the future. Large subcontractors will produce partially or fully autonomous electric vehicles, with the sole differences between them being brand value and design. The car makers that survive may well simply produce cars for Google (Ford recently signed an agreement along these lines), Apple, or Uber. Some, like BMW or Mercedes-Benz, may survive because of their brand and design qualities. Fiat Chrysler does not have this.
Marchionne doesn’t care about expensive gas or electric vehicles because his plan is simple:
Sell the profitable Jeep/RAM brands to another conglomerate that does not compete in these segments (for example, Hyundai KIA).
Sell the unprofitable Fiat to anyone who will take it. Perhaps synergies in the lucrative European light commercial vehicle segment will attract another European maker, such as PSA Peugeot Citroën, whose CEO, Carlos Tavares, has ambitions that were thwarted at his previous employer, Renault.
Sell Alfa Romeo and Maserati to someone who could use a strong brand. Perhaps Volkswagen will finally get hold of its prized Italian trophy if they can sort out their global legal woes.
Retire to play with his giant Formula 1 Scalextric set. Marchionne has been mocked for his firms’ strategy, which has been attributed to hubris. But perhaps he is the one seeing clearest of all.
Is the best way to deal with disruption simply to step out of the way?
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Tit-for-Tat Competitive Analysis
Question: Who wins when–in a perfectly competitive market–competitors fight each other? Prize awarded for best answer.
May 8, 2017This Time is Not Different, Because This Time is Always Different John P. Hussman, Ph.D.
All rights reserved and actively enforced. Reprint Policy
“History repeats – the argument for abandoning prevailing valuation methods regularly emerges late in a bull market, and typically survives until about the second down-leg (or sufficiently hard first leg) of a bear. Such arguments have included the ‘investment company’ and ‘stock scarcity’ arguments in the late 20’s, the ‘technology’ and ‘conglomerate’ arguments in the late 60’s, the nifty-fifty ‘good stocks always go up’ argument in the early 70’s, the ‘globalization’ and ‘leveraged buyout’ arguments in 1987 (and curiously, again today), and the ‘tech revolution’ and ‘knowledge-based economy’ arguments in the late 1990’s. Speculative investors regularly create ‘new era’ arguments and valuation metrics to justify their speculation.”
– John P. Hussman, Ph.D., New Economy or Unfinished Cycle?, June 18, 2007. The S&P 500 would peak just 2% higher in October of that year, followed by a collapse of more than -55%.
“Old ways of valuing stocks are outdated. A technological revolution has created opportunities for continued low inflation, expanding profits and rising productivity. Thanks to these factors, the United States may be able to enjoy an extended period of expanding stock prices. Jumping out now would leave you poorer than you might become if you have some faith.”
– Los Angeles Times, May 11, 1999. While it’s tempting to counter that the S&P 500 would rise by more than 12% to its peak 10 months later, it’s easily forgotten that the entire gain was wiped out in the 3 weeks that followed, moving on to a 50% loss for the S&P 500 and an 83% loss for the tech-heavy Nasdaq 100..
“Stock prices returned to record levels yesterday, building on the rally that began in late trading on Wednesday… ‘It’s all real buying’ [said the head of index futures at Shearson Lehman Brothers], ‘The excitement here is unbelievable. It’s steaming.’ The continuing surge in American stock prices has produced a spate of theories. [The] chief economist of Kemper Financial Services Inc. in Chicago argued in a report that, contrary to common opinion, American equities may not be significantly overpriced. For one thing, [he] said, ‘The market may be discounting a far-larger rise in future corporate earnings than most investors realize is possible, [and foreign investment] may be altering the traditional valuation parameters used to determine share-price multiples.’ He added, ‘It is quite possible that we have entered a new era for share price evaluation.’”
– The New York Times, August 21, 1987 (the S&P advanced by less than 1% over the next 3 sessions, and then crashed)
“The failure of the general market to decline during the past year despite its obvious vulnerability, as well as the emergence of new investment characteristics, has caused investors to believe that the U.S. has entered a new investment era to which the old guidelines no longer apply. Many have now come to believe that market risk is no longer a realistic consideration, while the risk of being underinvested or in cash and missing opportunities exceeds any other.”
– Barron’s Magazine, February 3, 1969. The bear market that had already quietly started in late-1968 would take stocks down by more than one-third over the next 18 months, and the S&P 500 Index would stand below its 1968 peak even 14 years later.
“The ‘new-era’ doctrine – that ‘good’ stocks (or ‘blue chips’) were sound investments regardless of how high the price paid for them — was at bottom only a means for rationalizing under the title of ‘investment’ the well-nigh universal capitulation to the gambling fever.”
– Benjamin Graham & David Dodd, Security Analysis, 1934, following the 1929-1932 collapse
“The recent collapse is the climax, but not the end, of an exceptionally long, extensive and violent period of inflation in security prices and national, even world-wide, speculative fever. This is the longest period of practically uninterrupted rise in security prices in our history… The psychological illusion upon which it is based, though not essentially new, has been stronger and more widespread than has ever been the case in this country in the past. This illusion is summed up in the phrase ‘the new era.’ The phrase itself is not new. Every period of speculation rediscovers it.”
– Business Week, November 1929. The market collapse would ultimately exceed -80%.
This time is not different, because this time is always different.
Throwing in the towel
When a boxer is taking a beating, to avoid further punishment, a towel is sometimes thrown from the corner as a token of defeat. Yet even after the towel is thrown, a judicious referee has the right to toss the towel back into the corner and allow the fight to continue.
For decades, Jeremy Grantham, a value investor whom I respect tremendously, has championed the idea, recognized by legendary value investors like Ben Graham, that current profits are a poor measure of long-term cash flows, and that it is essential to adjust earnings-based valuation measures for the position of profit margins relative to their norms. In Grantham’s words, “Profit margins are probably the most mean-reverting series in finance, and if profit margins do not mean-revert, then something has gone badly wrong with capitalism.”
He learned this lesson early on, during the collapse that followed the go-go years of the late-1960’s. Grantham once described his epiphany: “I got wiped out personally in 1968, which was the last really crazy, silly stock market before the Internet era… I became a great reader of history books. I was shocked and horrified to discover that I had just learned a lesson that was freely available all the way back to the South Sea Bubble.”
In recent weeks, Grantham has essentially thrown in the towel, suggesting “this time is decently different”:
“Stock prices are held up by abnormal profit margins, which in turn are produced mainly by lower real rates, the benefits of which are not competed away because of increased monopoly power… In conclusion, there are two important things to carry in your mind: First, the market now and in the past acts as if it believes the current higher levels of profitability are permanent; and second, a regular bear market of 15% to 20% can always occur for any one of many reasons. What I am interested in here is quite different: a more or less permanent move back to, or at least close to, the pre-1997 trends of profitability, interest rates, and pricing. And for that it seems likely that we will have a longer wait than any value manager would like (including me).”
I’ve received a flurry of requests for my views on Grantham’s shift.
My simple response is to very respectfully toss Grantham’s towel back into the corner.
First, Grantham argues that much of the benefit to margins is driven by lower real interest rates. The problem here is two-fold. One is that the relationship between real interest rates and corporate profit margins is extremely tenuous in market cycles across history. Second, the fact is that debt of U.S. corporations as a ratio to revenues is more than double its historical median, leaving total interest costs, relative to corporate revenues, no lower than the post-war norm.
The last three months of 1999 were just about the sickest thing I’d ever seen. It was an orgy, but I simply couldn’t bring myself to buy a stock that was up $10m, hoping it would go up $15, even though it was overvalued by $100. But by choosing to sit out most of the ramp, determined to wait for the inevitable implosion, I was the Greatest Fool of All, as those around me made mind-numbing profits as, day after day. YHOO, AMZN and CGMI would gap $10 a day, immune to gravity as the Nazz, aka NASDAQ, ripped right past 3000 and didn’t even blink rocketing past 4,000. At the end of the year, the Nazz was up 83 percent, a far cry from the 5 to 7 percent stocks had returned historically. People were too busy celebrating and shouting “It’s different this time.” to realize such an adjustment was unsustainable. It is like a guy who averages five home runs a year suddenly hitting fifty. Something is not right in Mudville. —Confessions of a Wall Street Insider: A Cautionary Tale of Rats, Feds, And Banksters by Michael Kimelman
Expanding your circle of competence-Platforms and Networks
Note what Prof. Greenwald says about Amazon and Apple. If Apple is JUST a product company then I would agree, but what if Apple has network effects with its music and iPods for example?
The second major category of investments involves assets that will never produce anything, but that are purchased in the buyer’s hope that someone else – who also knows that the assets will be forever unproductive – will pay more for them in the future. Tulips, of all things, briefly became a favorite of such buyers in the 17th century.
This type of investment requires an expanding pool of buyers, who, in turn, are enticed because they believe the buying pool will expand still further. Owners are not inspired by what the asset itself can produce – it will remain lifeless forever – but rather by the belief that others will desire it even more avidly in the future.
The major asset in this category is gold, currently a huge favorite of investors who fear almost all other assets, especially paper money (of whose value, as noted, they are right to be fearful). Gold, however, has two significant shortcomings, being neither of much use nor procreative. True, gold has some industrial and decorative utility, but the demand for these purposes is both limited and incapable of soaking up new production. Meanwhile, if you own one ounce of gold for an eternity, you will still own one ounce at its end.
What motivates most gold purchasers is their belief that the ranks of the fearful will grow. During the past decade that belief has proved correct. Beyond that, the rising price has on its own generated additional buying enthusiasm, attracting purchasers who see the rise as validating an investment thesis. As “bandwagon” investors join any party, they create their own truth – for a while.
Over the past 15 years, both Internet stocks and houses have demonstrated the extraordinary excesses that can be created by combining an initially sensible thesis with well-publicized rising prices. In these bubbles, an army of originally skeptical investors succumbed to the “proof” delivered by the market, and the pool of buyers – for a time – expanded sufficiently to keep the bandwagon rolling. But bubbles blown large enough inevitably pop. And then the old proverb is confirmed once again: “What the wise man does in the beginning, the fool does in the end.”
Today the world’s gold stock is about 170,000 metric tons. If all of this gold were melded together, it would form a cube of about 68 feet per side. (Picture it fitting comfortably within a baseball infield.) At $1,750 per ounce – gold’s price as I write this – its value would be $9.6 trillion. Call this cube pile A.
Let’s now create a pile B costing an equal amount. For that, we could buy all U.S. cropland (400 million acres with output of about $200 billion annually), plus 16 Exxon Mobils (the world’s most profitable company, one earning more than $40 billion annually). After these purchases, we would have about $1 trillion left over for walking-around money (no sense feeling strapped after this buying binge). Can you imagine an investor with $9.6 trillion selecting pile A over pile B?
Beyond the staggering valuation given the existing stock of gold, current prices (In 2011, gold traded at an average price of $1,700 in $US) make today’s annual production of gold command about $160 billion. Buyers – whether jewelry and industrial users, frightened individuals, or speculators – must continually absorb this additional supply to merely maintain an equilibrium at present prices.
A century from now the 400 million acres of farmland will have produced staggering amounts of corn, wheat, cotton, and other crops – and will continue to produce that valuable bounty, whatever the currency may be. Exxon Mobil will probably have delivered trillions of dollars in dividends to its owners and will also hold assets worth many more trillions (and, remember, you get 16 Exxons). The 170,000 tons of gold will be unchanged in size and still incapable of producing anything. You can fondle the cube, but it will not respond.
Admittedly, when people a century from now are fearful, it’s likely many will still rush to gold. I’m confident, however, that the $9.6 trillion current valuation of pile A will compound over the century at a rate far inferior to that achieved by pile B.
Our first two categories enjoy maximum popularity at peaks of fear: Terror over economic collapse drives individuals to currency-based assets, most particularly U.S. obligations, and fear of currency collapse fosters movement to sterile assets such as gold. We heard “cash is king” in late 2008, just when cash should have been deployed rather than held. Similarly, we heard “cash is trash” in the early 1980s just when fixed-dollar investments were at their most attractive level in memory. On those occasions, investors who required a supportive crowd paid dearly for that comfort.
My own preference – and you knew this was coming – is our third category: investment in productive assets, whether businesses, farms, or real estate. Ideally, these assets should have the ability in inflationary times to deliver output that will retain its purchasing-power value while requiring a minimum of new capital investment. Farms, real estate, and many businesses such as Coca-Cola, IBM and our own See’s Candy meet that double-barreled test. Certain other companies – think of our regulated utilities, for example – fail it because inflation places heavy capital requirements on them. To earn more, their owners must invest more. Even so, these investments will remain superior to nonproductive or currency-based assets.
Whether the currency a century from now is based on gold, seashells, shark teeth, or a piece of paper (as today), people will be willing to exchange a couple of minutes of their daily labor for a Coca-Cola or some See’s peanut brittle. In the future the U.S. population will move more goods, consume more food, and require more living space than it does now. People will forever exchange what they produce for what others produce.
Our country’s businesses will continue to efficiently deliver goods and services wanted by our citizens. Metaphorically, these commercial “cows” will live for centuries and give ever greater quantities of “milk” to boot. Their value will be determined not by the medium of exchange but rather by their capacity to deliver milk. Proceeds from the sale of the milk will compound for the owners of the cows, just as they did during the 20th century when the Dow increased from 66 to 11,497 (and paid loads of dividends as well). Berkshire’s goal will be to increase its ownership of first-class businesses. Our first choice will be to own them in their entirety – but we will also be owners by way of holding sizable amounts of marketable stocks. I believe that over any extended period of time this category of investing will prove to be the runaway winner among the three we’ve examined. More important, it will be by far the safest.
CSInvesting: I agree with all the above except that comparing gold as an investment to productive companies is not comparing like-with-like. Of course, owning a highly productive company or business that can compound over time will beat a sterile asset like cash or gold, but even Buffett will hold cash if he can’t buy great businesses at a good price. Gold is “money” that can’t be created by governments—by fiat.
This address considers the epidemiology of narratives relevant to economic fluctuations. The human brain has always been highly tuned towards narratives, whether factual or not, to justify ongoing actions, even such basic actions as spending and investing. Stories motivate and connect activities to deeply felt values and needs. Narratives “go viral” and spread far, even worldwide, with economic impact. The 1920-21 Depression, the Great Depression of the 1930s, the so-called “Great Recession” of 2007-9 and the contentious political-economic situation of today, are considered in view of the popular narratives of their respective times. Though these narratives are deeply human phenomena that are difficult to study in a scientific manner, quantitative analysis may help us gain a better understanding of these epidemics in the future.