The Big Picture - Macro Perspective on the Capital Markets, Economy, Technology, and Digital Media

Stock market movements since the start of the credit crisis have been characterised by relatively high volatility as uncertainty became paramount. And as new pieces of the economic recovery puzzle are added every day, investors are increasingly struggling to make sense of the most likely direction of stock prices.

It seems to be a case of so many pundits, so many views. Has the market started topping out and is a primary bear market about to resume, or will the secular bull market merely be correcting the strong rally that commenced in March 2009, before moving higher? Or is a “muddle-through” trading range in store?

It is one thing to trade the market’s rallies and corrections, but this is easier said than done, with not many people actually getting it right with any degree of consistency. Others are of the opinion that the recipe for creating wealth is simply to follow the patient approach, saying that “it’s time in the market, not timing the market” that counts.

This gives rise to the all-important question: does one’s entry level into the market, i.e. the valuation of the market at the time of investing, make a significant difference to subsequent investment returns?

In an attempt to cast light on this issue, my colleagues at Plexus Asset Management have updated a previous multi-year comparison of the price-earnings (PE) ratios of the S&P 500 Index (as a measure of stock valuations) and the forward real returns, as done by Jeremy Grantham’s GMO. Our study covered the period from 1871 to April 2011 and used the S&P 500 (and its predecessors prior to 1957). In essence, PEs based on rolling average ten-year earnings were calculated and used together with ten-year forward real returns.

In the first analysis the PEs and the corresponding ten-year forward real returns were grouped in five quintiles (i.e. 20% intervals) (Diagram A.1).

The cheapest quintile had an average PE of 8.9 with an average ten-year forward real return of 11.0% per annum, whereas the most expensive quintile had an average PE of 25.5 with an average ten-year forward real return of only 2.1% per annum.

This analysis clearly shows the strong long-term relationship between real returns and the level of valuation at which the investment was made.

The study was then repeated with the PEs divided into smaller groups, i.e. deciles or 10% intervals (see diagrams A.2 and A.3).

This analysis strongly confirms the downward trend of the average ten-year forward real returns from the cheapest grouping (PEs of less than six) to the most expensive grouping (PEs of more than 21). The second study also shows that any investment at PEs of less than 12 always had positive ten-year real returns, while investments at PE ratios of 12 and higher experienced negative real returns at some stage.

A third observation from this analysis is that the ten-year forward real returns on investments made at PEs between 12 and 19 had the biggest spread between minimum and maximum returns and were therefore more volatile and less predictable.

As a further refinement, holding periods of one, three, five and 20 years were also analysed. The research results (not reported in this article) for the one-year period showed a poor relationship with expected returns, but the findings for all the other periods were consistent with the findings for the ten-year periods.

Although the above analysis represents an update to and extension of an earlier study by GMO, it was also considered appropriate to replicate the study using dividend yields rather than PEs as valuation yardstick. The results are reported in diagrams B.1, B.2 and B.3 and, as can be expected, are very similar to those based on PEs.

Based on the above research findings, with the S&P 500 Index’s current ten-year normalised PE of 27.1% and dividend yield of 1.8%, investors should be aware of the fact that the market is by historical standards in “extreme overvaluation” territory. As far as the market in general is concerned, this argues for unexciting long-term returns, and possibly a “muddle-through” trading range for quite a number of years to come.

Although the research results offer no guidance as to calling market tops and bottoms, they do indicate that it would not be consistent with the findings to bank on above-average returns based on the current valuation levels. As a matter of fact, there is a distinct possibility of below-average returns.

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Back on the Kudlow Report at 7:00 pm this evening with Vince Farrell. We will be discussing Markets, the Fed, and Inflation.

My takeaway:

• We are not bullish, but opportunistic — these are trades (less than 1 year holds)

• We are now 90% long, 10% cash

• Over the past few weeks, we have added, BA, VRTX, HSY, CBOE, VTI (Vanguard Total Stock Market)

• There is a 25% correction coming, but we don’t see any evidence it is imminent . . .

We are looking to add more trades opportunistically, we are now 90/10 long cash, with no shorts (which feels dangerous to me emotionally)

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Videos posted here

. . . or, how to fool the gullible amongst us in 26 easy steps!

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Click for larger graphic

MoJo via boingboing

Author Barry Ritholtz and Mark Fisher, CEO of MBF Asset Management discuss how Chairman Ben Bernanke addressed the rising commodity prices in his news conference on Wednesday.

Visit msnbc.com for breaking news, world news, and news about the economy

It has been a while since we last showed a Best & Worst days chart, so we are overdue for another update.

Today’s version is courtesy of Mike Gayed of Pension Partners, and it shows what your returns look like if you were merely a Buy & Hold investor, if you were unlucky enough to miss the 5 best days, or lucky enough to avoid the 5 worst ones:
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Missing the 5 Best/Worst Days, S&P500

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Previously:
Missing Best & Worst Days of S&P500 (September 2010)

Paul Farrell notes that “Many, many experts did predict and warn of the 2008 meltdown years in advance.”  Yet it seems that business, finance and political leaders ALWAYS fail to see the next collapse coming. Why is that?

To answer this, Farrell channels Jeremy Grantham:

“Why do national leaders fail over and over to learn the lessons of history? Grantham said it best in a Barron’s interview a couple years ago: “Why is it that several dozen people saw this crisis coming for years? I described it as being like watching a train wreck in very slow motion. It seemed so inevitable and so merciless, and yet the bosses of Merrill Lynch and Citi and even Treasury Secretary Paulson and Fed Chairman Bernanke, none of them seemed to see it coming.”

Farrell enumerates seven reasons this always has, and is likely again, to lead to more trouble. He advises you to not forget any of the following elements:

1. Many, many experts did predict and warn of the 2008 meltdown years in advance.

2. Wall Street banks, corporate executives and Washington politicians are short-term decision-makers.

3. Most business, banking and financial leaders are short-term thinkers, focused on today’s trades, quarterly earnings and annual bonuses. Long-term historical thinking is a low priority.

4. As a result, it is virtually certain that America’s leaders will focus on upbeat, good news and always miss the next meltdown because warnings of a coming catastrophe are ignored.

5. Warnings from the few with a long-term perspective will always be dismissed during every investment cycle and every future recession/recovery cycle. Always. It’s in their DNA, trapped in their brain cells and demanded by their followers.

6. If you are a typical left-brain Wall Street or corporate executive, it’s virtually certain that you will miscalculate the timing/impact of the next meltdown, the next big collapse that’s off your radar. As a result, your company’s assets are at risk of suffering massive losses that are “predictable, not random.” But because you’re in denial, you will not deem it necessary to take steps to protect your assets.

7. If you’re a right-brain thinker, your longer-term historical perspective will give you a clear advantage in preparing for the next crash and the depression that follows.

File this away, and look back at it in a few years — I like to do that with Outlook or Yahoo Calendars, and get a pop message. This one is scheduled for 2014 . . .

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Source:
2008 crash deja vu: We’ll relive it, and soon
Paul B. Farrell
Marketwatch, April 26, 2011
http://www.marketwatch.com/story/2008-crash-deja-vu-well-relive-it-and-soon-2011-04-26

From Sal Arnuk, Co-authored with R.T. Leuchtkafer:

THEM — Analysis — Whats Changed Since the Flash Crash — FINAL 04 25 11 (2)

March Pending Home Sales rose 5.1% m/o/m, better than expectations of a gain of 1.5% but is still down 11.5% y/o/y which was boosted by the tax credit. The best gain was seen in the South where contract signings rose by 10.3%. The West and Midwest also saw gains while the Northeast region saw a drop of 3.2%. This data is seasonally adjusted but we are in the best season of the home buying business and we’ll see how many of the contract signings translate into closings because of the repeated issues of tight lending standards and appraisal issues. With respect to the overall economic data seen of late, there has been a moderation relative to expectations and likely explains why the 10 yr note yield is matching the lowest level in 6 weeks, notwithstanding the daily depreciation in the US$ and repeated highs in US stocks.

Initial Jobless Claims disappointed for a 3rd straight week totaling 429k, 34k higher than expected and up from 404k last week. It’s the highest since the end of Jan. The 4 week average is now back above 400k at 409k. Continuing claims, delayed by a week, fell by 68k and Extended Benefits, delayed by two weeks, fell by a net 76k. Bottom line, the trend over the past few weeks is clearly disappointing as signs were pointing to a more sustainable pick up in the labor market. It is likely though that with the growing concern with rising commodity prices as co’s do their best to maintain margins combined with uncertainty for those that rely on Japan, a short term reluctance to expand is occurring.

Q1 Real GDP rose 1.8% annualized, below expectations of 2% and Nominal GDP was up just 3.7% vs the forecast of 4.3%, thus a price deflator .4% below forecasts prevented Real Q1 GDP from coming in even less than estimated. While Personal Consumption rose a better than expected 2.7% (est 2.0%) and spending on equipment and software rose a solid 11.6%, construction, trade and government spending (led by defense and local gov’t) were a drag. Inventories added about 1% pt to GDP. Of noticeable weakness, Real Final Sales which take out inventory, rose just .8%, the weakest since Q3 ’09. Bottom line, some factors that negatively influenced Q1 GDP (such as weather) some believe will reverse over the next few quarters and that this slowdown will be reversed as the consensus for the next few Q’s are 3%+. A positive influence in the 2nd half of ’11 will be co’s taking advantage of the accelerated depreciation for R&D with a bump in cap ex which will reverse in ’12. With this said, overall GDP growth is only averaging 2.3% so far in this recovery.

Plummeting prices of LCD screens, via this month’s Wired.
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With everyone so focused on Inflation, I (naturally) want to discuss Deflation. Or rather, the lack of it in Technology prices. Instead, lets  look at the Recency Effect and the life cycles of new tech products.

Technology poses a special challenge to the hordes of inflation watchers — Larry Kudlow calls them inflationistas. During the 2000s, this crowd completely missed the biggest inflationary spike since the 1970s until Oil was well over $100 and foodstuffs had skyrocketed. This was after decades of ignoring ballooning medical and college costs.

Having missed the last run up in prices, this same crowd now sees hyper-inflation everywhere.

There seems to be an inability to understand how CPI is officially constructed, and why it typically understates inflation. Complicating matters is the challenge of  recognizing the impact of Technology, and how it create the appearance of deflation.

The key is understanding Technology’s normal adaptation cycle, what this means for cyclical pricing declines, and why falling prices do not automatically equate with Deflation.

The Fed gets this wrong. Wall Street misunderstands this. Most economists seem not to recognize qualitative difference between the 1st Big Screen TV that rolls of the assembly line and the 10 millionth. (Those who want to delve into the finer wonkish points about this can see the Technology adoption lifecycle by Joe M. Bohlen and George M. Beal, (1957), later refined in Everett M. Rogers’ Diffusion of Innovations).

Consider this simple factoid: New technologies and products come down in price over time, regardless of the state of the economy, Fed monetary policies, Federal stimulus, or even income inequality in the broader society.

If tech prices are independent of the Fed and Congress and money supply and the value of a dollar, then its hard to say (as so many do) that this is deflationary per se. It is a simple fact of adoption cycles, and not the usual drivers of inflation.

Whether we are discussing washing machines, radios, auto airbags, cellphones, or even PCs — all manufactured goods go through a well established adoption process. In the classic definition (see chart below), the first group of people to use any new technology are called “innovators,” followed by “early adopters,” then the “early majority” and “late majority,” and lastly, the “laggards.”

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Technology Adoption Lifecycle

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The key to understanding this is recognizing the differences in perceived social status value of these products.

The impact of this adoption process and the manufacturing economies of scale are significant determinant of technology product prices. But understand the following: What the Innovators buy is a very different product qualitatively — in terms of social status and perceived value – than what the laggards purchase.

Here is a grossly over-simplified version of how this works: When innovators buy a product, they essentially pay for all of the R&D costs, and other development expenses. You paid 365 labor units for a VCR in 1972 because they were a limited production, custom product that was practically hand made. When a PC cost 465 labor units, chip fabs were nowhere near as plentiful as today — and the biggest cost in early PCs were the exorbitant chipsets contained in them.

Let’s take a closer look at the perceived social status value of these products: When you are the only person in town in 2000 who has a 50 inch flat screen TV — and it cost $10,000 — there are non-monetary, status benefits of ownership. Compare that in 2010, when EVERYONE has a big screen, thanks to the cheap Korean flatties sold for less than $600 at Best Buy.

The claim that the price drop is deflationary assumes these two products are nearly identical, and further ignores irrational human behavior regarding these early innovator purchases. These products are not identical, at least in terms of the value conferred social value of status-seeking consumers.

The early adopters pay less than the innovators, as factories get built to mass produce chips or tape transport mechanisms or cell phone keypads. But they also buy a product with lower social status. What was a nearly custom made product becomes a merely limited-production, high-end one. Where the innovators paid for the R&D, the early adopters paid for the fabs and factories to be built.

Recall the days before cell phones were ubiquitous: The early majority doesn’t get the use of the product for the first few years, but they get a big price benefit of manufacturing economies of scale.  But they also did not get the status symbol of those giant beige Motorola brick phones with their 8 inch black antenna. Mass production of components bring prices down; successful products attract competition to the space, and soon more manufacturers are cranking out more units. Through competition, prices begin dropping faster and faster. The late majority gets even cheaper prices. Consider the laggards and the VCR today — they cost about $29 each.

But the status associated with being the very first to own this is why the Innovators pay more for these products. And its also why the 100 millionth 50 inch television screen to roll off the assembly line has no status associated with it — where has the first few 1000 had massive status attached to it.

Technology adoption cycles reflect this in their price changes. Technology price decreases across their production life cycle are not only about industrial economies of scale — they are also about the decreasing status of an object as it becomes an everyday household product.

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Previously:
Hackonomics (February 2008)

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Be sure to check out “Fight of the Century: Keynes vs. Hayek Round Two” posted earlier today in our video section.

Great fun, educational stuff

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