A Comparison of Bubbles by John Chew

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stock market roller-coaster

Great article on bubbles; the definition of bubbles and the history of them. Kudos to my friend David Lau of dahhuilaudavid.blogspot.com/ for finding this this article. A special thanks to John Chew for giving me permission to reprint his article. he can be reached at [email protected].

Below is the article:

QUESTION: Do you think bubbles occur because of mass error, irrational exuberance, or both? (You’re not expected to know the definitive answer; just please share your opinion so as to start discussion.)

I believe bubbles occur because of mass error caused by “easy” money (increase in the money stock) and real rates manipulated below the originary (True time preference rate) rate of interest. The irrationality, greed, envy, fear are the human reactions or symptoms of the boom bust cycle.  Furthermore, in my opinion entrepreneurs are acting rationally to price signals given by the market, but the signals from the market are distorted by government intervention (interest rate/money stock) which causes mal-investment during the boom. The more government intervention thus the increase in size and frequency of the bubble cycles.

First a definition of a bubble

The term bubble is a frequently misused in reference to any category’s price that has appreciated—true bubbles are rare (pre-2010?!) A bubble, normally identified after it has burst, is the rapid increase and subsequent decrease in prices for a specific category of equity or commodity (e.g. technology stocks in 2000; energy in 1980 and housing prices in 2006)

A group of lemmings looks like a pack of individualists compared with Wall Street when it gets a concept in its teeth—Warren Buffett.

Increases in money stock and a negative real rate of interest will elongate and/or enhance the size of the boom phase; in other words, increase the mal-investment which shows up in too many internet start-ups, empty homes, over-supply of oil, etc.  The question becomes why does a particular asset class rise in price so sharply relative to other asset classes?  Typically when we speak of a boom we mean a boom in gold, housing prices, technology stocks, etc. We talk about a specific asset.  In the long run all industries and the assets within those industries must earn equivalent returns on capital because of the law of supply and demand (regression to the mean).  When there is some type of shock (invention, political action) that reduces supply and/or increases demand then prices will go up in that asset signaling entrepreneurs to marshal more assets/capital into that asset class or industry to meet the demand.

For example, when Netscape went public in 1996 the market for technology and telecom companies had a huge influx of demand because the browser opened up the product/service possibilities for those companies. Prices rose sharply for Netscape signaling high returns on investment which attracted resources to those industries. Now if the money stock remained the same then the resources would have to be moved entirely from other sectors of the economy. “Easy” money defined as the increase in money stock and the real rate of interest pushed below the originary rate (the true time preference rate of interest) distorts the signals of the market by flooding the hot industry/asset class with capital that otherwise wouldn’t be redeployed there. But since the capital is not fully being drawn from savings that would not necessarily be attracted there if the true time preference rate of interest prevailed, there is mal-investment.

The animal spirits, “irrational exuberance” are simply a symptom of the boom.  The initial high returns on a particular asset class will draw competitors into the industry to capture those “supra-normal” profits which will increase supply and thus force down the future returns in that industry causing the inevitable shake-out/bust.  Say the real return on assets is 8% in a steel mill but now demand pushes steel prices up whereby the steel mill can earn 16% on its capital.  Investors will rush to build and buy steel mills until the rate normalizes again.  Lawyers may wish to change professions and become mill workers.  People are reacting normally to these price signals they just don’t realize the prices are distortionary due to the artificially low rate of interest.

As Ludwig von Mises explains that when the central bank lowers interest rates below the natural rate of interest, engineered by an expansion in liquidity, the drop in interest rates falsifies the businessman’s calculation. … The result of such calculations is therefore misleading. They make some projects appear profitable and realizable which a correct calculation, based on an interest rate not manipulated by credit expansion, would have shown as unrealizable. Entrepreneurs embark upon the execution of such projects. Business activities are stimulated. A boom begins. (Human Action)

There seems to be a symmetry and proportion to bubbles perhaps due to the constancy of human nature.  Rising prices attract capital and supply, but in the near term—6 months, a year two or three?—price rises attract those who buy simply because prices are rising. Envy, momentum investors (buy and sell on price movement), the foolish buy without regard to the true “normalized” economic return of the asset.  Say home prices rise above what those homes could generate in market rents. If the normalized return for home rent is 5% given the alternative returns in the market then a $200,000 home would rent for $10,000 or $833 per month. If house prices doubled to $400,000 but the rent did not increase then the return would drop to 2.5%.   Either rent would need to rise, house prices fall or some combination to bring the capitalization rate into balance.  Perhaps, a house speculator who buys at $400,000 believes prices will double to $800,000 so the cap rate falls to 1.25%.  Perhaps they are being rational but the law of supply and demand in the long run is against them. On the other side, rising house prices attract home builders and speculators, but builders build only when lenders lend. Rising home prices increases the collateral value of which to make loans, larger loans allow for more building and the cycle goes until it stops. The ending is hard to predict, but end it will.

A Bubble is a bubble is a bubble from Markets, Mobs & Mayhem by Robert Menschel

Booms & Busts % Rise

Bull Phase

Length of Bull Phase (months) % Decline Peak to Trough Length of Bear Phase (months)
Tulips (1634-1637) Netherlands +5,900% 36 -93% 10
Mississippi Shares France (1719-1721) 6,200% 13 -99% 13
South Sea Shares England (1719-1721) 1,000% 18 -84% 6
American Stock (1923-1932) 345% 71 -87% 33
Mexican Stocks (1978 – 1982) 785% 30 -73% 18
Silver U.S. (1979 – 1982) 710% 12 -88% 24
Gulf Stocks Kuwait (1978 – 1986) 7,000% 36 -98% 30
Hong Kong Stocks (1970-1974) 1,200% 28 -92% 20
Taiwan Stocks (1986 – 1990) 1,168% 40 -80% 12

Every bubble is different, and every bubble market is exactly alike. Momentum begins to build. Investors start to stampede. The stampede creates a mob mentality that seems to sweep everything along in its path until some unknowable top is reached, panic sets in, and everyone start running for the door.

“Much has been written about panics and manias, much more than with the most outstretched intellect we are able to follow or conceive,” wrote Walter Bagehot, first editor of the Economist. “But one thing is certain, that  at particular times a great deal of stupid people have a great deal of stupid money…..At intervals, from causes which are not to the present purpose, the money of these people—the blind capital, as we call it, of the country—is particularly large and craving; it seeks for someone to devour it, and there is a ‘plethora’; it finds someone, and there is ‘speculation’; it is devoured, and there is ‘panic.’”

Below is an analysis of two bubbles: The Energy Boom of the early 1980s and the Technology Bubble of the late1990’s by Kenneth Fisher in his book, The Only Three Questions That Count: Investing by Knowing What Others Don’t .  The analysis shows what happens when the market value far exceeds the asset value of the particular industry.

Kenneth Fisher: The 1999 and early 2000 tech IPO explosion reminded me eerily of the 1980 energy bubble that led the whole market into a bear market.  I fathomed tech could do the same. I tried to see how many parallels I could find between the two sectors that no one was commenting on.

Because I know stock prices are determined—always and everywhere-by supply and demand, I started with the notion that a flood of supply might topple prices. The following table demonstrated the rapid increase of stock supply in both of these sectors through respective IPO booms in the late 1970s and late 1990s. In 1980, nearly half of the increase in value of all new and existing US companies came from the energy sector. In 1999, nearly all of the increase came from the technology sector.

US ENERGY STOCKS 12/31/79 12/31/80 Change US Technology Stocks 12/31/98 12/29/99 Change
# of Energy Companies 229 301 72 # of Tech  Companies 1460 1652 192
Value of Energy Companies ($mils.) 190 325 135 Value ($mils.) $2,307 $4,930 $2,623
All US Stocks All US Stocks
# of Companies 4291 4417 126 # of Companies 8,656 8,785 129
Value  ($000s) $1,025 $1,325 301 Value  ($000s) $12,881 $15,749 $2,868
New Energy Cos. as a pct. Of total new companies 20.3% New Tech Cos. as a pct. Of total new companies 21.2%
New Energy Companies as a pct. Of total companies 1.7% New Tech Companies as a pct. Of total companies 2.2%
Increase in Energy Value relative to Total Market Value 44.8% Increase in Tech Value relative to Total Market Value 91.5%
Price/Book of Energy Stocks 2.6x Price/Book of Technology Stocks 13.9x
Price/Book of S&P 500 1.3x Price/Book of S&P 500 5.6x
Energy/S&P 500 P/B Ratio 2:1 Technology/S&P 500 P/B Ratio 2.5:1

If you look at the shaded boxes for both Energy and Technology Companies you can see the amount of investment/MAL-investment that went into those two sectors.  The amount of investment/mal-investment was unsustainable in terms of return on investment and eventually the boom crashed to equalize returns between those sectors and all other sectors in the economy.

Kenneth Fisher writes on pages 287-288, “Also, note the similarities between the percentages of new technology stocks relative to all new stocks and all U.S. stocks in 1999 to those of 1980’s energy bubble. Note also the price-to-book value of each sector relative to the market. Each was trading at roughly twice the market multiple. Who would remember today that in 1980 energy stocks were priced like growth stocks? Scary times. The key is no one saw it or mentioned it.”  Growth without returns above the firm’s cost of capital creates no economic value.

Now look at the relative weights of these two sectors in the following table. The top three tables show energy relative to the S&P 500 during the bubble and after the crash in 1979, 1980, and 19812, the bottom three show technology during 1998, 1999, and 2000.

A Brief History of Sector Bubbles S&P 500 Economic Sector Weights
December 1979 December 1980 December 1981
Basic Materials 9.64% Basic Materials 8.88% Basic Materials 8.58%
Capital Goods 10.28% Capital Goods 10.82% Capital Goods 10.03%
Communication Services 6.05% Communication Services 4.62% Communication Services 6.53%
Consumer Staples 10.9% Consumer Staples 9.23% Consumer Staples 10.58%
Consumer-Cyclicals 9.86% Consumer-Cyclicals 8.00% Consumer-Cyclicals 8.84%
Energy 22.34% Energy 27.93% Energy 22.80%
Financials 5.79% Financials 5.34% Financials 6.01
Health Care 6.42% Health Care 6.54% Health Care 7.42%
Technology 10.86% Technology 10.69% Technology 10.33%
Transportation 2.17% Transportation 2.89% Transportation 2.95%
Utilities 5.70% Utilities 5.07% Utilities 5.92%
100.00% 100.00% 100.00%
December 1998 December 1999 December 2000
Basic Materials 3.11% Basic Materials 2.99% Basic Materials 2.41%
Capital Goods 8.07% Capital Goods 8.40% Capital Goods 9.01%
Communication Services 8.33% Communication Services 7.93% Communication Services 5.47%
Consumer Staples 14.89% Consumer Staples 10.88% Consumer Staples 11.35%
Consumer-Cyclicals 9.13% Consumer-Cyclicals 9.14% Consumer-Cyclicals 7.56%
Energy 6.22% Energy 5.43% Energy 6.45%
Financials 15.59% Financials 13.20% Financials 17.22%
Health Care 12.07% Health Care 9.05% Health Care 14.10%
Technology 18.54% Technology 30.02% Technology 21.85%
Transportation 0.93% Transportation 0.70% Transportation 0.67%
Utilities 3.11% Utilities 2.28% Utilities 3.91%
100.00% 100.00% 100.00%

Note the similarities between the relative weights of energy and tech. At its 1980 peak, energy was 28% of the U.S. market. But tech’s explosion was more remarkable—growing from 5% in 1992 to just over 30% in 1999. The way I saw it, technology had further to fall. But it didn’t need to fall much further to create the same major bear market energy created from 1980 and summer of 1982. (Today, technology capitalization compared to the total market capitalization of all S&P 500 companies makes up 15% of the U.S. market as measured by the S&P 500). See https://www2.standardandpoors.com.

Also, I hope this table illustrates the distortionary effects of the boom.  The large amount of resources that flow into the energy and technology sector have to be pulled from other sectors in the economy, but too much investment in one sector will drive its future returns down while pulling resources from another industry will lead to its future returns rising—eventually returns will equalize.


In the same way there is a structure of production, there is a structure of finance and a structure of speculation. It is given to us by the yield curve, the alignment of rates over time. It can be bent out of shape by the Fed just as the relationship between capital and consumption can be distorted.

The distortion of the structure of speculation results from a stimulus in the front end of the yield curve. This enhances instability because the entire structure becomes vulnerable to a change in the cost of borrowing, that is, a change in the funds rate. When the Fed tightened in 1994, that structure topple down

If you know that the economy is dominated by the time-bound structures of production and speculation, the world comes into clearer focus. These are not just abstractions. We applied this notion of artificial stimulus very profitable in 1995 by focusing on the semiconductor industry. We saw that one consequence of tis 3% funds rate was a capital spending boom in semiconductors. We said that Micron Technology—which was then in the most active list at the NYSE—was overvalued. The stock later went from 94 to 30.

…What we do is look for extremes in markets: very undervalued or very overvalued. Austrian theory has given us an edge. When you have a theory to work from, you avoid the problem that comes with stumbling around in the dark over chairs and night stands. At least you can begin to visualize in the dark, which is where we all work.

The future is always unlit. But with a body of theory, you can anticipate where the stuructures might lie. It allows you to step out of the way every once in a while. So I would like to put in a plug, not just for the theory itself but for the application of the theory for calling th turn of cycles in the workaday world.

We are eclectic because changes in fed policy occur at the margin and were going to have an edge if we find trends in an obscure place rather than a familiar one. We look at extremes, obscurity, and the contrary outcome because that is where you get the best odds in investment and speculations.

How do we profit from whatever excess is upon us?

Dr. Copper and the Pessimists
At the risk of sounding like conservative curmudgeons who have nothing better to do than to explain why everyone else just doesn’t get it, we think one of the main problems the markets are having these days is that there is little understanding of history.

The level of anxiety and negativity, by investors, pundits and many analysts, seems out of proportion to the facts.  Negativity has reached such high levels that many people seem to have lost perspective.  This seems true from a short, medium, and longer-term point of view.

For example, we have seen a proliferation of stories in the media and blogosphere during the past few days about copper – “the metal with a Ph.D. in Economics” or “Dr. Copper.”  The stories have focused on the Greece/Euro-induced drop in copper prices from $3.65 per pound in early April to $3.00/lb. in mid-May.  This 18% drop is supposedly signaling a double-dip recession.

Don’t count on it.  The double-dip crowd has never believed in this recovery.  To them, this has always been a “dead-cat bounce” or a “figment of stimulus money.”  They believe negative data and ignore positive data.  They seem to forget the fact that copper prices bottomed at $1.34/lb. in December 2008 and even after the recent declines are still up 132% from that bottom.

The pessimists did the same thing with last week’s initial unemployment claims data.  Initial claims surprised the markets by rising from 444,000 to 471,000.  Somehow, this one week of negative data from what is clearly a volatile data source became more important than the past four months of overall employment statistics.  The Household Survey has counted almost 2 million new jobs in the past four months, while the Payroll Survey is showing solid (200,000+) job growth again.

As we have said before, anxiety has reached such dramatic levels that economic-hypochondria has taken over the punditry and many investors.  This is unfortunate.

History shows Great Depressions are very rare things.  Believing that one is happening again, and buying gold or sitting in cash is a risky strategy.

Yes, tax rates are scheduled to go higher.  We get it.  But, they won’t move up until next year at the earliest, and the actual size of the tax hike may be affected dramatically by the election in November.  Moreover, tax rates were much higher in the past and the US did not collapse.

And, yes, government is growing like crazy and deficits are huge (unbelievably huge).  But this does not guarantee collapse.  The US still has $150 trillion in assets and more than $15 trillion in annual output.  A company of that size could easily afford to carry $10 trillion in debt.

Don’t get us wrong.  We think government is too big and too intrusive and it will harm the economy over time.  But, it will not kill the economy today, or even next year.  Productivity is booming.  New technology is lifting wealth, and living standards are rising – despite government growth.

Some might say that it is not the Great Depression we should worry about, but the 1970s all over again.  This, we can agree with.  However, during certain periods of that decade, particularly during 1975-76, the economy and the stock market both boomed.  That’s what we are experiencing right now – a boom amidst an uncertain future.

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Posted on Monday, May 24, 2010 @ 11:20 AM • Post Link

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