Over the last 140+ years, real commodity and producer prices
(that is, commodity and producer prices deflated by the consumer
price index (
)), have been highly correlated with the earnings yield (the ratio
of earnings to stock prices, or the inverse of the P/E ratio) on
American stocks ([[SPY]], [[DIA]], [[QQQ]]) over the medium to long
term, just as nominal producer prices were highly correlated with
long-term interest rates from the 1720s until World War I over
medium- to long-term intervals. This latter relationship is what
Keynes called "
," in deference to A. H. Gibson's rediscovery of the relationship
in the 1920s.
(click to enlarge)
(Sources: Roy Jastram's
The Golden Constant
, Robert Shiller's
(click to enlarge)
(Sources: Jastram, Bank of England)
Over the short term, the relationship tends to be more
complicated than that. Commodity prices ([[RJA]], [[GSG]], [[DJP]])
can rise quite dramatically with stock prices (thus driving down
the earnings yield, all else being equal) or fall in tandem. Not
only that, but over the short term, different commodities appear to
react in different ways to this relationship.
Oil, for example, tends to be an early mover while precious
metals (most notably, gold) tend to be the last to show up to the
party. Oil prices ([[CRUD]], [[USO]], [[OIL]]) peaked in 2008,
while gold (NYSEARCA:[[GLD]]), silver (NYSEARCA:[[SLV]]), and
platinum peaked in 2011. The great spikes in precious metals prices
three years ago were, as in 1980, indicators that the decade of
rising earnings yields (or, falling P/Es, if you prefer) and
commodity prices was ending.
The oil/gold ratio is a simple way of representing that contrast
between how oil and gold "respond to" or "predict" the earnings
yield and commodity prices. (For charts and a more detailed review
of energy and precious metals price behavior discussed in this
piece, please see my previous article, "
Inflation and Yields: The Rules of the Game
Gold and crude oil are both somewhat peculiar commodities,
however, because it has only been four decades or so that their
prices have been allowed to float, having each been tied to the
dollar up until the early 1970s. And, if we look at silver,
although it has been cut loose from the dollar since the American
Civil War, it did not exhibit this sort of extreme behavior prior
to the 1970s either.
In other words, with the collapse of the Bretton Woods
arrangements at the end of the great post-War boom, we were given
this curious new twist to what appears to be a very ancient
relationship between goods prices and yields. On that basis, the
combination of low/flat energy prices and parabolic precious metals
prices within the larger context of a general collapse in commodity
prices over the last five years has indicated that we are in a
secular bull market in stocks and a bear market in commodities (a
statement that seems much more obvious today than when I argued in
this vein over a year ago).
Based on these relationships alone, if this great boom in stocks
is to end, the history of the last half-century suggests that we
will have to see a significant rise in crude
(WTI at $150) and/or a further collapse in precious metals prices
(gold at $800) first.
Over the last year, and especially the last six months, as the
trend in commodity and stock prices has become less subject to
debate, I have been focusing more on the "internal" relationship
between stock prices and earnings. Just as a year or so ago, I felt
like I had to argue against those who were claiming that the
collapse in commodity prices were somehow failing to "confirm" the
stock market rally, I have since felt that I have to argue against
those who claim that stocks are on the brink of collapse simply
because P/Es and similar valuation ratios are "high."
I have tried to show that the relative
of earnings is as important as the
of earnings and stocks when it comes to predicting stock market
behavior and that history indicates that although this stock market
boom is starting to mature, we probably have another two to three
years left of very high returns. Interest rates, and especially the
yield curve, say the same thing. (See
for the relationship between the yield curve and stock returns, and
, among others, for the relationship between earnings volatility
and stock returns).
Historical precedent seems fairly clear to me on this point: the
next two to three years will likely see a powerful surge in stocks
and bonds and a further collapse in commodity prices. As I have
been arguing, we are not living in another Great Depression but a
concatenation of the
1920s and 1980s/1990s
. And, we are fast approaching a crossroads. Investors who are
thinking beyond the next 12 months' returns, indeed, already have
to choose between the possibility of exceptional short-term
(2/3-year) gains and a long-term (10-year) slide. Obviously, it is
not for me to say what a given investor should do; that depends on
any number of factors, but I think that there is more "upside risk"
than "downside risk" at the moment.
By "upside risk," I mean three things.
, that the gains over the next two or three years might be so
dramatic as to offset a long-term decline in stock prices after
they finally peak, although that window appears to be closing with
every passing month now. For example, in the mid-1990s, when P/E
ratios were near historic highs, the stunning rise in stock prices
over the subsequent five years far outweighed the crashes and flat
growth that followed. Although the balance of risk is already
beginning to shift in favor of a "long-term bearish" position, we
do not appear to be at the tipping point quite yet. A long-term
investor, I strongly suspect, can still gain long-term returns over
the short term.
, that the more right I am about the short-term boom, the more
traumatic will be the following collapse. Whereas today's bears are
thinking about how high P/E ratios relate to the elements of the
previous paragraph (i.e., the narrow question of how absolute P/E
levels relate to stock returns), I worry about how these high
ratios relate to the stability of the global economic and
geopolitical order. To me, the similarities between the present
decade and the 1920s are just too close for comfort. The more
"optimistic" I am about the 2010s, the more "pessimistic" I must be
about the 2020s. Here we are again, trapped between asset price
booms and deflationary woe in the real economies of the world.
Meanwhile, there appears to be a whole series of micro-level
political shifts that are now starting to be felt at the
macro/geopolitical level, connected, as in the early 1920s, with an
initial post-commodity-boom shock. At the moment, the old order
remains intact. The faces in the halls of power generally remain
familiar. But, there are movements and parties that hold
significant minority positions in the parliaments around the world,
including the West, that seem poised to capitalize on the next big
economic shock, if one should arise.
Such a shock seems increasingly likely. What is an optimistic
but realistic expectation for economic growth over the next five
years? And, what are the chances that we will have a
shock/recession in that same period? I will be surprised if the Fed
can raise rates next year without chaos ensuing the year after
that. I don't think the Fed can do any good at this point, but they
can probably do a fair amount of damage in order to regain a bit of
reason I am worried about "upside risk" is because of the "impact"
that a booming stock market will have on commodity prices. If I am
right about a brief but dramatic extension in the boom in stock
the correlation between commodities and the earnings yield, we
should expect significant downward pressure on commodity prices as
well as (worsening) crises in emerging markets over the next three
years, somewhat akin to the late 1990s crises, which saw a massive
boom in American equities and collapses in the Global East and
South alongside commodity markets.
Here is where the experience of the 1990s and the 1920s begins
to part somewhat. In both instances, we saw a similar sequence: a
boom in equities, an unprecedented run-up in stock valuations, and
a collapse in inflation and commodity prices. After the dot.com
crash, however, we saw a boom in commodities and BRIC economies,
whereas after the 1929 crash, we saw a further collapse in
commodity prices and a more or less global Depression. In the
1930s, there was a strong commodity rally, but only after prices
finally bottomed in 1932. In the 2000s, in contrast, commodities
recovered much more quickly and substantially.
(click to enlarge)
(click to enlarge)
So, even if we price in a stock market boom over the next three
years, what will the next ten years (that is, the three boom years
plus the seven post-boom years) look like? Inflation or deflation?
Or some bizarre combination of the two? For example, a surge in
real commodity prices while nominal commodity prices remain flat or
falling? Could we really experience such a severe form of
deflation, though? If we really wanted to generate inflation, don't
we have the tools do so, i.e. barrel bombs of cash dropped from
Bernanke's old helicopter fleet? I would say that the question
probably hangs on how durable the post-Bretton Woods order is,
which is as much a political as a financial question. And, yet,
this seems to be precisely the sort of question nobody is asking
right now. Rather, it is, when will the Fed raise short-term rates
by 25-basis points? We are again in the age of parsing Fed
chair(wo)men's statements, as good a contrarian signal as any,
In short, what I mean by "upside risk" is a situation in which
the boom is not only creating conditions for the subsequent bust
(which is a fairly standard way of looking at the relationship
between the two, I think) or masking the present bust (a standard
anti-central banking position, I believe) but, in fact, is the
convex side of the present bust. In other words, under our global
monetary regime, the Dollar Hegemony/Pax Americana, a stock market
boom is also a commodity bust. The two go hand in hand.
REVERSE-ENGINEERING COMMODITY PRICES
The obvious question that the correlation between the earnings
yield (or yields generally) and commodity prices begs is that of
causation. Is this correlation between yields and commodities a
product of necessity or coincidence? But, let's not jump the gun.
Certainly, answering that question is the ultimate goal, but that
is not the first question we should be asking ourselves. There is
no reason (that I am familiar with) in economics that suggests why
yields generally and commodity/producer prices particularly should
be tied together as closely as they have been. And, this
relationship has gone unnoticed, as far as I can tell, among
intermarket and other technical analysts, even though those sorts
of relationships are the reason that sort of analysis exists.
What I mean is,
there is a causal relationship, it has not been obvious for some
reason, and considering all of the alleys that economic theory has
run down over the last 250 years, nobody (as far as I know) either
noticed or posited the existence of that particular correlation. I
doubt that we can rationalize our way to a competent theoretical
account of such a relationship, therefore. Instead, I think we
should ask a much smaller question stemming from what was,
initially, not much more than a curious by-product of my previous
comparisons of inflation and yields.
That question is, why is it that
commodity and producer price indexes have been more highly
correlated with yields than the vast majority of individual
commodity prices were
? In my
of historical commodity and producer prices with yields over the
last three centuries, I found again and again that although nearly
all individual commodities were positively correlated with yields,
the indexes were almost always more highly correlated.
The correlation between the (log of the) real Grilli-Yang
Commodity Price Index (GYCPI)--specifically, the GYCPICW series,
the geometric mean--and the (log of the) earnings yield from
1900-2011 was 0.70 whereas the median correlation for the 24
individual commodity components was 0.52 and the maximum
correlation was 0.62.
Why might that be significant? A simple thought experiment might
be useful here.
Imagine if the earnings yield were 10.0% and remained at that
level for the next five or ten or twenty years (whatever period you
like). In order for the commodity index to remain flat as well (say
at the "100" level), either every single component of the index
would have to also remain flat or every price movement in one
commodity must be balanced out by shifts in prices in the other
commodities. Now, what those shifts would look like would be
influenced quite a bit by the weighting of the index.
If the weighting was not regularly rebased (which seems to be
the case for the GYCPI, the standard historical commodity index),
then in order for the index to remain more highly correlated than
the components, a price change in one commodity must generally be
met by a counter-move in one or more other commodities. (The size
of those counter-moves would be dependent on each commodity's
relative share of the index). If the earnings yield rose over a
ten-year period, say, and the GYCPI rose, too, even if each
individual commodity rose during that period, in order for the
strength of the correlation to remain intact, any outsized rise in
one commodity (nickel, for example) would have to be balanced by a
slower rise in corn or coal or cocoa, simply as a mathematical
Likewise, a dramatic fall in one commodity, or a class of
commodities, must be balanced out by a reduced fall or rise in the
There are, of course, situations in which general commodity
prices are falling but individual commodities might be rising
rather significantly. This was the case in the 1980s, when a number
of industrial metals (nickel sticks out in my mind) were setting
new records while agriculture prices were falling. Just speaking
mathematically, in order for that correlation to be maintained over
the long term, it suggests a remarkable amount of volatility that
is inevitable within the commodity class, with relative commodity
prices necessarily shifting quite dramatically, even though they
individually remain correlated with one another and the price index
over the long term.
Interestingly, and as something of an aside, I found that the
higher the correlation between a given commodity and the index, the
higher the correlation between that commodity and the earnings
yield. This suggests that for those who do not care for my
insistence on connecting commodity prices and yields, they can
ignore many of the subsequent references to the earnings yield and
think of this discussion purely in terms of the way that
commodities relate to one another singly and collectively. It is
probably okay to mentally substitute the phrase "commodity index"
for "earnings yield" in many of the statements below.
(click to enlarge)
(Sources: Pfaffenzeller and Shiller)
Right. So, then imagine how a stock market boom must then be
"felt" in the commodity sector. If stocks boom, and the earnings
yield falls significantly, unless all of the commodities move in
lock-step, there is apt to be an incredible amount of volatility
within the commodity sector. In addition to the general downward
pressure on commodity prices, there will also be this "jostling"
amongst commodities. One can imagine what that might do to the
terms of trade for different emerging markets and the volatility
that will cause there.
The deeper question, again, is that of causality.
Is that a metaphorical, mathematical jostling or is there, in
some manner, an actual jostling somehow between disparate
Does the price of grains have an impact (a relatively inverse one)
on the price of metals and vice versa? If the earnings yield is
falling but metals are rising, must agriculture and/or energy make
up the difference by falling dramatically? Mathematically, that has
clearly been the case, but is that inevitable?
When writing about commodities, either individually or in
relation to yields, I have focused almost exclusively on metals and
energy prices in previous articles, largely because my initial
interest was in
. However, the bulk of commodity price indexes are made up of
agricultural commodities. The GYCPI has metals and agricultural
commodities but no energy or gold (or iron ore, for that matter).
The World Bank "Pink Data" indexes separate energy prices and
precious metals from other commodities, but agriculture takes up
the majority of the remainder (roughly 65%, plus 3% for
fertilizers). Even though food commodities are the biggest
sub-group in the World Bank commodity index (40%), no individual
food commodity is very heavily weighted, whereas sawn wood, copper,
aluminum, and iron ore collectively take up roughly a third of the
index. Also, both the GYCPI and the World Bank indexes are weighted
by export values rather than production values.
Moreover, using the GYCPI indexes from 1900-2011, the
agricultural indexes are more highly correlated with the earnings
yield than is the metals index. The "Gibson Effect" is, in other
words, perhaps primarily an agricultural phenomenon.
It becomes necessary to ask: to what extent does index weighting
influence the outcome? If the price of wheat doubles but the price
of avocados halves, should a commodity index based on those two
goods show a rise, a fall, or no change? If one has a very specific
question in mind, then a fitting index can be constructed rather
easily, I think. It seems that most historical commodity indexes
are constructed with questions about terms of trade and development
economics chiefly in mind rather than broader questions about the
nature of commodity prices as such. Since we are working
"backwards" from correlation to causation, it is not immediately
clear whether or not wheat should weigh more or less than avocados
and if so by how much.
This may seem like a rather arcane, tangential question, but as
I hope to show, as it turns out, consideration of the problem of
index weighting actually opens up a whole new level of
relationships within the commodity complex that will help us
understand commodity prices better and what to look out for in the
coming years in global markets. What I mean to say is that thinking
about the problem of index weighting actually answers more
questions (and more interesting questions) than the otherwise dry
problems surrounding index-construction. There is a lot more at
stake than a technical issue.
PRICES AND PRODUCTION
My first step was take a look at the data. I began with the
agricultural data at the UN's Food and Agriculture Organization
Perhaps everybody and their grandmother already knows this, but
I was surprised to see that the prices of agricultural commodities
listed by the FAO for 2012 were almost simple inverse functions of
their production volumes.
United Nations Food and Agriculture
If that were perfectly true, of course, then the total
production value of rice would be exactly the same as the total
production value of watermelons, which of course, is not the case
(rice production is ten times more valuable than watermelon
production), but for the most part, that relationship holds. Onion
production, for example, is less than twice as valuable as pear
production. Wheat production is 34% more valuable than tomato
In the chart above, I compared the top 50 agricultural
by production value
and put them on a scatter plot.
But, if you look at the top 50 agricultural commodities arranged
by sheer volume of production
, the correlation weakens. In other words, the higher the total
value of a commodity's production, the more likely it is that its
total production will behave as an inverse function of its price
relative to similarly significant commodities.
The inverse correlation between the price and the production is
somehow tied to its total value, in other words.
If we look at these two data sets again on a line graph, we can
see how the relationship changes depending on the total value of
production for a particular good relative to that of another good.
Take the second set first. In the following chart, I have lined up
the top 50 agricultural commodities by volume of production and
organized them by their total value of production (with the value
falling from left to right).
As the total production of goods falls, the less likely that
the unit price and total production are to be inverse functions of
(click to enlarge)
If we take the top 50 agricultural commodities by total value of
production and place them on a line graph in similar fashion, we
find that the inverse correlation is much stronger, although the
most valuable commodities by total value of production are also
somewhat less sensitive to this relationship, as well: the relative
increase in production does not drive the unit price down as much
as it does the other commodities.
(click to enlarge)
Among the top 50 agricultural goods (by total value of
production), the correlation between price and production is
-0.77. Among the first 25 of those, it is -0.80, and among the
second 25, it is -0.99. Among the top 50 agricultural goods
organized by total amount of production, it is -0.44.
How is that significant, apart from being interesting in its own
right? For one, it suggests that it is not necessary to exert any
great effort in weighting commodities. If they tend to be inverse
functions of their production values, then regularly weighing the
commodities by total value of production unnecessarily amplifies
the price behavior of the most extreme commodity price
fluctuations. Instead, we can simply use a geometric average of
whatever basket of commodities we are looking at. On the other
hand, if it is characteristic of major commodities to exhibit this
inverse correlation between (relative) price and (relative)
production, then there might be a reason to employ some sort of
threshold for commodities. Perhaps some commodities are more
commoditized than others? Tangerines should not be weighted equally
with wheat, but perhaps coffee should?
More importantly, perhaps, is what this suggests about the
larger questions we are attempting to make sense of. If, as was
suggested by the discussion above, individual commodity prices are
influenced (in whatever fashion) by movements in yields and by the
movement of other commodities, and if relative prices are to some
degree a function of relative production (or vice versa),
we might expect to see a shift in relative prices coincide with
adjustments in relative production volumes
. The relative impact is different from that implied by the Gibson
Under the Gibson Effect, all else being equal, a fall in one
commodity price would raise other commodity prices on average, but
if relative production and relative prices are an inverse function
of one another, then, all else being equal, a rise in the price of
wheat should result in a rise in all other (agricultural)
commodities, more or less--or, somewhat paradoxically, where prices
for all other commodities remain stable, an expansion in
production. In other words,
if we take these relative relationships naively, a 50% rise in
the price of commodity X would imply a 50% drop in production of
that commodity, a 50% rise in the price of all other commodities, a
50% increase in the production of all other commodities, or some
combination of the three.
Of course, that assumes that 2012 was not a fluke.
Fortunately, the USGS provides a fair amount of long-term data
on global production and prices for major mineral commodities. Like
the GYCPI commodity index, much of it goes back to 1900.
FROM AGRICULTURE TO MINERALS
Taking eleven major mineral commodities (gold, silver, tin,
zinc, lead, aluminum, iron ore, bauxite, phosphate rocks, copper,
and nickel), we can see that this inverse correlation between
relative prices and relative production holds throughout the last
(click to enlarge)
United States Geological Service
There are, in fact, a lot of interesting things going on in
these charts apart from the general stability of the
From sometime around the Depression, there seems to have been a
slight shift in the slope of the line somewhat enhancing the
"weight" of production relative to price. That is, the expansion in
production among the cheaper minerals tended to rotate the end of
the curve for expensive metals downwards somewhat, especially up
until the 1960s. Since the early 1970s, the relationship between
price and production has been more evenly balanced.
(click to enlarge)
Better than these correlations and snapshot scatter-plots of
random years, however, is a scatter-plot of the entire 112-year
period. The chart below appears to suggest that
there has been a massive expansion in the production of the
cheaper metals while rarer metals have responded with rising
. For example,
the price of gold has tended to rise and fall with the
production of commodities like iron ore and phosphate
As global production has expanded, thus shifting the overall
slope towards the "northwest" of the chart, the correlation has
remained intact, and it has done so (among rarer metals) by price
expansion rather than expansion of production, as shown by the
slopes of the individual commodities (across time).
If you look at the slope of the price-to-production curve again
and how it surged downwards up during the post-War boom up until
the early 1970s, just on this relationship alone, it is not
surprising that the US could no longer suppress the price of gold,
or oil, for that matter.
(click to enlarge)
(Source: USGS, Shiller)
More recently, this makes me wonder somewhat about the supposed
surge into gold last year by Asian buyers while the gold price
tanked. If absolute supply and demand determine prices, then the
gold price should have risen on the surge in demand, if we take the
gold bugs at their word. But, if supply, demand, and price are
relative phenomena, it is possible that
the collapse in gold prices on surging demand was linked to
slowdowns in emerging markets.
Tying this back into the outlook over the next three years,
then, if we are due for another downdraft in commodities, and if
the precious metals markets are usually the last to know, and
precious metals tend to react more strongly than other commodities,
as in the late 1990s, we should perhaps not be too surprised if
this coincides with turmoil in emerging markets that are heavily
tied into global commodity production. Obviously, the BRICs come to
mind first, especially the most prominent member of that group.
And, we should not be too surprised to see another surge of
buyers, perhaps, into the precious metals markets as gold and
silver tumble while American stocks rocket upwards.
WATER AND DIAMONDS
Before concluding with the long-term scenarios for commodity
prices, however, it is important to point out that this discussion
has essentially been the obverse side of the hoariest classical
macroeconomic puzzle, the "
water and diamonds paradox
," which asks why useless commodities (e.g., diamonds) are more
expensive than useful commodities (e.g., water). The simple and
obvious response has been that diamonds are far rarer than water. I
would assume, though, that the
of water would exceed the total value of diamonds. But, this
investigation seems to hint at the possibility that that is not the
case, or at least that their respective total values are closer
than we might otherwise imagine.
Of the eleven mineral commodities I looked at here, except for
the period when gold was being held down to an unnatural level in
the Bretton Wood years before Nixon closed the gold window, the
total value of annual gold production has almost always been one of
the top three mineral commodities. Only iron ore, aluminum, and
copper are comparable. That seems slightly paradoxical to me. It is
not that hard to understand why the per unit value of gold (or
diamonds) might be higher than that for more useful commodities
like iron or copper (or water) but I am not sure I understand
why total gold production should be comparable to the value of
iron ore production
. If all the gold and diamonds vanished tomorrow, I suspect that we
could recover from the trauma much easier than if all of the iron
ore were to vanish. I would expect that, all else being equal, that
the utility of a commodity would tend to increase the total value
of production of that commodity above that of a relatively useless
(click to enlarge)
To put this another way: if you think it is perfectly obvious
that relative commodity prices should be an inverse function of
relative volumes of production, then you will be perfectly content
with the idea that the total value of global water production may
be equal to the total value of global diamond production (assuming
that both water and diamonds obey the "laws" we have described
here), but I imagine that that is not a perfectly obvious condition
for most people and will even seem somewhat perverse.
BETWEEN WATER AND DIAMONDS
Whatever might account for the tendency towards parity among
major primary commodities, these two relationships that we have
discussed here--the Gibson Effect and the inverse correlation
between relative price and relative production--suggests that
both the price and production levels of a given commodity are
influenced as much by the behavior of the other commodities as it
is by that commodity's own "fundamentals" (e.g., supply and
If commodity prices do fall further over the next three years,
as I believe they will, we should not expect to see an orderly
retreat, but rather waves of sudden drops in one set followed by
collapses in others. We should also expect to see a contraction in
the production of basic commodities (especially commodities like
iron, aluminum, phosphate, rice, wheat, and corn) along with severe
drops in more expensive commodities such as precious metals, but
also industrial metals like nickel.
In other words, during these sorts of commodity market
contractions, if history is any guide, we should expect to see
a reversal of the longer term trend of rising lower-end
production and high-end prices
If we look at the correlation between the price of gold and the
levels of production of the other minerals, the correlation is
highest among the cheapest commodities. In simple English, this
means that, as we discussed above, the price of gold will tend to
move with the level of production of commodities. Prices and
production in a commodity bust both contract but not necessarily in
the same commodities.
(click to enlarge)
What this means for our outlook over the next two, three, five,
or ten years is that, we should expect to see an exacerbation of
the present predicament--high asset and low commodity prices during
a period of lackluster global growth--with pressure felt
increasingly in emerging markets. Global growth (and commodity
production) will slow and prices will fall. Stocks will continue to
rise. But, then comes the crash.
THE LONG TERM
The question then is what yields and commodity prices will do
after the crash. We are accustomed to high P/E ratios being the
consequence of high stock prices, but that is really a
post-Depression phenomenon. High P/E ratios used to be primarily a
consequence of low earnings (think of the Great Depression of the
late Nineteenth Century). In other words, if we are going to face a
Depression-like situation in the 2020s, we may see a simultaneous
collapse in stock prices, profits, and commodity prices, somewhat
similar to what happened during the worst moments of the late
crisis, but this time stretched out over years.
This economy does not seem like it has much cushioning left for
another shock or a prolonged slump, and the question now seems to
be how global political and monetary institutions will respond to
those sorts of outcomes. The present trend seems to point to a
long, deflationary slump to follow our deflationary boom, but if
that should become more palpable than it was even in 2009, that
would seem to increase the possibility that those institutions
would become more creative in their attempts to generate inflation.
In the event of 1930s-style political crises, there may be a much
greater impetus to engage in more heavy-handed interference in
market processes than bailouts and quantitative easing.
In short, the return of stock-picking and Fed-watching means
that the market is not "correctly" pricing in the possibility that
the P/E ratio will go to 50 (putting the earnings yield at 2%) and
what that means over both the short, medium, and long terms.
On the broader question of the very nature of commodity prices,
let me conclude with the basic problems we are left with after this
review of the history of commodity prices and production.
1. What is the nature of the correlation between
commodity/producer prices and yields, particularly the earnings
2. In light of the tendency for commodity indexes to be more
highly correlated than individual commodities to yields, how might
the change of the price in one commodity inversely impact the price
(in aggregate) of all the other commodities?
3. In light of the inverse correlation between prices and
production levels for commodities relative to one another, what
sort of mechanism would account for the change in price and/or
production level of one commodity positively impacting the prices
and/or production levels of all other commodities over time? That
is, why is it that an increase in production of one commodity seems
to necessitate an increase in price and/or production for all other
4. Why is it that the inverse correlation between relative
prices and production levels is itself positively correlated to
total production values? In other words, why is it that this
inverse correlation is felt greatest in the "biggest"
5. Why is it that commodity production values gravitate towards
parity in terms of their total
, apparently irrespective of their total
? That is, why is it that the gold and diamonds of the world are
roughly equal in price to the iron ore and water of the world?
The author has no positions in any stocks mentioned, and no plans
to initiate any positions within the next 72 hours. The author
wrote this article themselves, and it expresses their own opinions.
The author is not receiving compensation for it. The author has no
business relationship with any company whose stock is mentioned in
KBR Inc.: Deepening Pessimism And Increased Bidding
Costs Point To Possible Bottom