Friday, November 1, 2013

Updated World Money Supply- Still Slowing

Just a quick update. The estimated M2 money stock for World continues slow. On a year-over-year basis, world M2 money stock increased at 8% rate, down from the 11% pace high water mark back in 2011 and 15.5% pace in 2008.

This suggests to me that the pace of economic activity and inflation continues to decelerate globally. This may suggest another round of monetary stimulus approaches.

Austrian Economics Going Mainstream?

Via Tyler Durden at Zero Hedge.

One has to wonder if somewhere deep down a change is occurring in America. While stock prices soar to record highs, it is clear a growing number of 'real' people are realizing the nonsense that watching a 'market' as anything indicative of reality has become. The latest 'shift' is the appearance on New Orleans local TV of a two-minute primer on an "alternative" school of economic thought - Austrian Economics. While the anchor is careful to add the caveat that the mainstream economists think the world would be a terrible place if they didn't help us along, the brief clip begins with some useful common sense, "the market alone should decide the value of products and services. If a company is not successful, it should go bankrupt." Indeed...

Click image for 2-minute clip...

Debt And Deficits Explained

via Austrian Economics Addict

The visual of this chart is outstanding, it jumped off the page when I saw it. The chart shows our Governments yearly revenue, yearly deficit, and total debt. This is from an article titled Great News! The Fiscal Crisis Is Over! by Jon Gabriel, at I got there from this article at

Here is a quote from Mr. Gaberiel, “…imagine the green is your salary, the yellow is the amount you’re spending over your salary, and the red is your MasterCard statement.”

What is sobering about this chart is how a seemingly small yearly deficit compounds into a massive amount of debt over time. What is it going to look like in three more years if we continue our $1 trillion yearly deficit?

Unfortunately the $17 trillion is really not the actual debt. If you factor in the unfunded liabilities for Social Security, Medicare, and Medicaid, which have been estimated to be between $55 to $222 trillion, look at chart here, the problem gets exponentially worse. What do you think Obamacare will add to this unsustainable mountain, or valley, of debt?

Fortunately we have the Fed which can electronically print counterfeit money to pay our way out of this mess. Oh yeah, I forgot, the only way a Government can accumulate this amount of debt is because its Central Bank funds the expansion in the first place by buying Government bonds. Without the ability to electronically print counterfeit money, Governments can only grow to the size of what they can steal or mooch through taxing and borrowing. At a certain point, individuals won’t produce above a certain level if they can’t enjoy the fruits of their labor, and they won’t purchase bonds from a seller whose level of debt makes the transaction seem to risky. The Fed can’t print its way out of the economic reality of scarcity. Their denial of this reality is why they printed us into this mess in the first place.

The New Reality of International Bonds

Sorry for the advertisement from Vanguard, but I thought you may find it interesting that the international bonds had grown to such a large market. Not only should it help you consider where your investable assets could be allocated but it also helps clarify where the next financial catastrophe could arise

The infographic below shows how international fixed income instruments have grown to become the largest investable asset class—larger than domestic stocks, international stocks, and domestic bonds. Vanguard believes that foreign bonds can diversify a traditional portfolio in much the same way that foreign stocks do, by helping to offset the risks presented by U.S.-based investments.

Does your portfolio's asset allocation reflect the important role foreign bonds play in the marketplace? To find out, log on to and view a domestic/international breakdown of your bond holdings.
International bonds

Bear Case For Oil In One Chart

OK, I lied. There are two charts, but I could not pass on providing the price chart for oil, below represented by the United States Oil Fund (Ticker USO), which tracks the price of WTI crude. Crude oil has come under selling pressure lately, and to be honest I am surprised oil gained as much price strength as it did with the economy remaining weak and the alleviation of tensions in the Middle East seen earlier in the year.

The easy bear case for oil resides in the fact that the price broke the 200 day moving average, a negative indication in my estimation. The bear case goes deeper than that though. The following charts shows the difference between the year-over-year growth in oil product related demand (excluding home heating oil, as this demand tends to be more inelastic) and oil production in the US, with GDP growth as a back drop.

Not only is demand falling, but supply is also increasing causing a divergence not seen in more than 20+ years. So as demand falls (is this due to a weakening economy, increased fuel usage efficiency, a combination of both? tough to separate the individual causes but more than likely both), but oil production continues to ramp. Not the greatest backdrop for higher commodity prices.

Ten Trading Rules To Follow

I found this at Some good advice.

by Gatis Roze
  1. Embrace the laws of nature.  Springs produce either salt water or fresh water.  Not both.  I am either trading the long side (bullish equities) or the short side (bearish equities) but never both.  That’s just experience and knowing myself.
  2. Review every chart of every position you own – every day – even if you only allocate 10 seconds of eyeball time to each position.
  3. It’s okay to be wrong; it’s unforgiveable to stay wrong.  Marty Zweig.
  4. The maximum number of positions you should hold in your trading account is determined by the number of equities you are able to know well.  Remember their costs, know their present stops and picture their charts in your mind’s eye.
  5. Keep a diary of the lessons the market taught you and don’t ever repeat them.
  6. Be aware when you distort market information to fit your personal beliefs.  These trades are most likely to fail.  You must learn to neutralize your feelings and accept whatever reality the markets present.  Learn to manage your own perceptions.
  7. Monitor and manage your precious time.  Be selective in all your tasks and stick to the routines you’ve assembled that accommodate the realities of your personal schedule.
  8. Don’t let sudden success result in an inflated opinion of yourself and cause you to forget proper trading rules.  Even a broken clock is right twice a day!
  9. Don’t blindly adopt others’ trading tools.  Tutor yourself about each new indicator, and test it out within your own style of investing before you begin to embrace it.
  10. Subscribe to CANI.  Constraint and never-ending improvement each and every day.  Tony Robbins

Why the Fed Can’t Taper

The author holds some misgivings and just wrong assumptions on the Austrian School and I will let you guess where the issues arise. The tone of the article tends to be conciliatory of the Fed and its misguided actions. That aside, it appears to be a growing view that the Fed may not be able to taper. Additionally, I find it astonishing that people cannot see the link between distorted asset prices and the dangers arising from a misaligned and manipulated economy.

By Frances Coppola

John Aziz has a post explaining why the Austrian school of economics is wrong to believe that the Fed can’t taper because of the risk of asset collapse and hyperinflation.

I actually have some sympathy for the Austrian argument that the Fed cannot taper, but not for their reasons. They wrongly focus on base money creation as the main problem. But as Aziz says, base money creation would have to be a) far more extensive and b) have a far more direct effect on broad money to result in the hyperinflation that they fear. The real risks come from the market effects of persistent QE.

Central banks have become the largest players in global markets. It is somewhat unclear as to whether markets respond to central banks or vice versa – it’s probably a bit of both – but we really can’t pretend that central bank actions have no effect on global markets. The Fed is the largest and most important central bank in the world. Its actions are critical to the operation of global markets. Prices along the yield curve are governed by market view of the Fed’s likely future actions – often the wrong view, because the Fed’s price signals are far from clear, despite its vaunted commitment to “forward guidance”: to see just how conflicted Fed price signals can be, you only have to look at Bernanke’s announcement of imminent tapering followed by delay after delay. There remains a high degree of uncertainty in the markets regarding the future path of US monetary policy, which makes markets unstable and over-reactive. It’s as if everyone is in a state of “amber alert” – there is a hurricane coming, but we don’t know exactly when or where it will hit or how bad the damage will be.

Exactly how QE affects the economy is a matter of considerable debate. Inflation expectations tend to rise when QE commences, because many investors still think expansion of base money = inflation. But there appears to have been little or no effect on consumer prices, and it is unclear to what extent asset purchases benefit the wider economy. However, the one thing we KNOW QE does is support asset prices – all classes of asset, not just government bonds and MBS. Global markets have become used to this support: investment decisions are now governed to a large extent by the desire either to avoid capital erosion on safe assets (hence moves into assets that give zero yield, such as cash – zero yield is better than negative yield) or find some positive yield somewhere.

Tapering is removing central bank support of asset prices. Unless not just the US economy but the GLOBAL economy is “on the up” at the time that tapering commences, the result of tapering will be a global fall in asset prices. That isn’t going to cause hyperinflation, as the Austrian school thinks, but it would cause a global recession.

I’m afraid it is not US fundamentals, but global fundamentals that will determine the Fed’s ability to taper. If the Fed tapers when the global economy is already in the doldrums, as it is at the moment, the recessionary rebound to the US economy would be considerable.

It would also in my view be highly irresponsible of the Fed to cause a global recession by ill-judged tapering. Because of the US dollar’s pre-eminence (and the pre-eminence of USTs, too – we don’t talk about that enough), the Fed is effectively the world’s central bank. It is high time that the US accepted that its monetary (and fiscal) policies must be driven by the needs of the global economy, not just the US. The “exorbitant privilege” is an exorbitant responsibility, too.

Miners Better Value Than Tech, But Tread Carefully- Peter Spina

I admit I have not heard of Spina before listening to the below interview. But his points are very good.

Volume Off the High- Oct. 31 Trading Day Edition

Still seeing a high degree of volatility on both sides of the volume mover coin.

High Volume High- Oct. 31 Edition

Still seeing a lot of what I will call volatility hitting the volume lists

The Beatings Continue Until Moral Improves- S&P 500 Price/Volume Heat Map Oct. 30 Edtion

We saw a follow through day with the weakness seen after the Fed's announced the (non) results of its October meeting. That said and despite the market closing lower, trading was volatile throughout the day, as equity prices traded at one side or the other of the zero demarcation most the of the trading day. Weakness and supply did gain control late in the trading day (the stalking grounds of institutional investors) and the S&P 500 finally closed off nearly 40 basis points in weakness across most sectors.

Although prices were generally weak, the price/volume heat map does not suggest that the supply dynamics exhibited ubiquitous trends across all sectors. First, the weakness seemed concentrated in roughly three groups, i.e. staples, energy, and financials with weakness defined as more than 50% of the names in the sector showing falling prices supported by volume. More so, the price decline in the market yesterday seemed to result from a lack of demand. In any event, volatility looks like it is picking up here.

Schiff Discusses Fama's Confusion

But that is what happens when you follow Keynesian nonsense

Yellen- An Economic Disater, Schiff Interviews Paul

Fed Wants Inflation to Sustain Asset Bubbles- Schiff

The argument presented here has an air of ridiculousness. Rising prices, as measured by the CPI, shows a symptom of inflation. Inflation is a outsized rise in monetary supply, which had been running at a rate around 9% annually versus an economy growing at about 2% to 2.5%.

Thursday, October 31, 2013

Employment Still Points to Weak Economy

You have undoubtedly heard the narrative about continue employment gains suggests continued economic growth, some sort of better outlook,  or something tho that effect. What most fail to realize is that the gain in employment gains continue to decelerate. More so, the acceleration and deceleration in employment tends to indicate the track of economic growth, or in some instance forewarn about a change in change.

In September, the BLS states that the economy added 148,000 jobs in the month according to the establishment survey while according to the household survey, the number of employed gained by over 200,000. That is all well and good, but it ignores that the gains continue to weaken. In September, total household employment was 1.3 million persons better than the year-ago level. Looking at the year-ago change in the total number of employed thought, the increase is 1.5 million persons less than the 2.8 million gain in the year ago period. Overtime, this acceleration/deceleration measure is what tracks economic growth. Lets look at the chart.

The above chart shows year-over-year GDP growth versus the acceleration/deceleration in employment gains. The turns in both are consistent. Now you might ask about the period in the mid 1990's when employment A/D turned negative but GDP remained strong. Well, this is an anomaly. Longer-term, a negative turn in the employment A/D that corresponds with continued positive GDP has only occurred twice in the post war period. Here is the chart of the employment A/D and GDP since the mid-1940's

There were two periods when employment A/D turned negative and GDP remained positive. In fact and in both of these periods, GDP growth was well over 5%. In no period since has employment A/D turned negative in conjunction with GDP growth of sub 2% that the economy did no subsequently roll into a recession. Considering that the Fed has pumped over $2 trillion of cash into economy, we are really seeing unprecedented times in more ways than one.

Watch For The Dragon King

No really. This article that appeared in Wired and by Adam Mann details the study of chaotic systems and the uncanny affect of dragon king alignments presaging a crash or break down event. I am skeptical of the discussion concerning the ability to prevent and manage catastrophic events, as I am reminded of the law of unintended consequences, but  having some advanced notice that a system is breaking down could be far more valuable.

Stop a stock trade and avoid a catastrophic global financial crash. Seal a microscopic crack and prevent a rocket explosion. Push a button to avert a citywide blackout.

Though such situations are mostly fantasies, a new analysis suggests that certain types of extreme events occurring in complex systems – known as dragon king events – can be predicted and prevented.
“A chaotic system may be in flux, and look like random behavior,” said physicist Daniel Gauthier of Duke University, co-author of a paper appearing Oct. 30 in Physical Review Letters. “But maybe there’s some internal structure we can identify that leads to destabilizing events.”

By looking at a simple experimental chaotic system, Gauthier and his co-authors have been able to detect telltale signs that a dragon king event was approaching and, most importantly, stop it from happening. If this work can be generalized to more complex systems, such as climate, power grids, and financial markets, it could be used to forecast and perhaps forestall extreme behavior.

The story of this finding begins in the mid-90s when Gauthier was studying the behavior of simple electronic circuits that were trained to follow one another. His team did this by periodically measuring the difference in either the voltage or current between the two circuits. They would use this difference to give one system a tiny kick. The idea was to synchronize the circuits as much as possible. And, for the most part, it worked: One circuit followed the behavior of the other.

But occasionally, the two circuits would get out of whack. Essentially, the leader circuit was losing control of its follower, which would go off on its own and exhibit completely different behavior. This desynchronization event would eventually get corrected – the tiny kicks would push the follower circuit back to the same behavior as its leader. But the results remained a bit of a head scratcher, until Gauthier figured out what was going on.
A strange attractor first characterized by Edward Lorenz. Image: Fractint/Wikimedia

Chaotic systems are often very simple. They can be characterized by just  a few parameters – in this case the voltage and current of the circuit – but they also exhibit random and unpredictable behavior. Yet the voltage and current of the system can’t take on just any value. Instead, the parameters will stay within a somewhat narrow range. The possible values within this range are what mathematicians call a “strange attractor.” When plotted on an x and y axis, strange attractors often take on odd shapes, sometimes looking like the wings of an arithmetic butterfly.

The meeting points of these two wings – the “body” of the butterfly – was where the desynchronization was happening in Gauthier’s circuits. Imagine one circuit is traveling around on a wing of the butterfly, pulling the follower circuit slightly behind it. From time to time, the leader circuit would enter the meeting point of the wings and jump to the opposite side. Usually, the follower circuit would come right along with it but, every so often, the difference between them would be just enough so that the follower circuit wouldn’t make the hop, instead staying on the same wing.

“We would say that’s when they shred from each other,” said Gauthier. “The two systems get ripped apart, basically going as far apart as they can.”

And that was it. Gauthier studied these toy circuits, found an interesting behavior, and explained it. At the time, it didn’t seem like a big deal. But in the last few years, scientists in many fields have been looking closely at the behavior of extreme events – very large fluctuations in a system that often leads to catastrophic results. These occur in many complex, chaotic systems: enormous rogue waves in the ocean, extreme weather in the climate, or global stock market crashes.

One particular class of these extreme events is known as a dragon king event. This is a catastrophic occurrence that falls far outside a normal expected probability. The name comes from looking at the wealth distribution in a medieval society. If you plot the number of people who have a particular amount of wealth, you would see many, many poor farmers and a smaller number of wealthier landowners and noblemen. Plotting the number of people versus a given amount of wealth would give you a straight line.

Now the medieval king, who typically has an enormous amount of wealth, would be outside this plot, far above the rest. Think of someone like Bill Gates or Carlos Slim whose wealth dwarfs even that of a modern one-percenter. While the rest of the population is described by the simple line plot, these people are outliers.

So why dragon kings? Because, like dragons, certain extreme events are entirely outside the normal classification scheme. “Dragons are extraordinary animals of extraordinary properties,” said economist Didier Sornette of the Swiss Federal Institute of Technology Zurich, another co-author of the work.
The signature of a dragon king event, which is far above the normal distribution and occurs far more often than other extreme events. Image: Hugo LD de S Cavalcante et al, “Predictability and suppression of extreme events in a chaotic system”,Physical Review Letters

Dragon king events may be freakish, but they are not freakishly rare. In fact they occur much more frequently than you would expect. Small fluctuations in the stock market happen all the time and very large ones rarely. But a dragon-king-type stock market drop would be one that was both extremely large and occurred somewhat regularly. It would be like seeing a once-in-a-century stock market crash every decade or so.
But stock markets are complex systems and hard to study. So Gauthier, Sornette, and their collaborators looked at the difference between the parameters of the two circuits in the leader-follower system. Very small differences in the voltage or current were common, as expected. But the extreme “shredding” events when the two circuits were very far apart occurred much more often than would be expected from a normal distribution. They had found one of the most pronounced dragon king event signatures ever seen.

Even more interestingly, the researchers found that dragon king events displayed characteristic signals announcing their approach (they could only occur when the two circuits were on the “body” of the strange attractor butterfly). Knowing that a dragon king was coming, they could apply tiny perturbations to make sure the circuits stayed in sync. In essence, they could forecast the arrival of a catastrophic event and suppress it, prevent it from occurring.

By studying this simple circuit system, the scientists hope they might be able to apply some lessons to more complex chaotic systems. Economists, for instance, think some sort of rules might govern the stock market (the rest of us aren’t so sure). If number crunchers could uncover some of these rules and find the warning bells that are correlated with crashes, perhaps they could also be avoided.

Of course, that’s been the dream of every trader since the London Stock Exchange first opened up in a coffee shop in 1698. The question is really whether or not the simple circuit-toy model can be applied to a more complicated real-world system.

“That is where we’re really taking a leap,” said Gauthier.

The leader-follower circuits can be characterized entirely by a few variables. Something like climate or the financial system is composed of significantly more parameters, and no one really knows which ones might be relevant or not.

In his work, Sornette has been working to identify what might or might not be useful in predicting the behavior of the stock market. His team keeps tabs on more than 20,000 assets worldwide to try and diagnose bubbles. Using statistical analysis, they search for what he called “trenchant super-exponential growth,” which is where the price of an asset grows much faster than a simple compound interest. It is possible that such behavior is a warning bell for financial bubbles.

“We are extremely active in the development of statistical methods to apply to a major outstanding unsolved problem: the financial stability, or instability, of the world,” he said. His research has looked at possible ways to forecast changes in the financial market with some encouraging results.

Being able to study dragon king events in an experimental system could be extremely useful, says physicist Cristina Masoller of the Polytechnic University of Catalonia in Spain, who studies extreme events in complex systems but was not involved in the new study.

“Most of these events are in nature: precipitation, oceanic, or economic systems,” she said. “The fact that they can be built in the lab allows us to explore the origin of these events, and learn how to generate and suppress them.”

But even if the research may one day help identify precursor signals to dragon king events, there is no guarantee that they can be controlled, added Masoller.

“Maybe the parameters that we need to control in order to avoid these extreme events are a parameter we can not change,” she said.

Say that oceanic temperature is a relevant parameter in avoiding catastrophic climate changes. Tuning such a variable up and down precisely is likely to be out of human control. Even in something like a financial system, the key parameter may be the amount of money each individual in the world has. Changing something like that might be out of the realm of possibility.

In complex systems “it’s possible the laws are simple, but maybe the parameters we need to control are not very accessible,” she said.

Gauthier and Sornette are aware of the limitations of their experimental model. But the point of the research was to “at least plant the thought in people’s minds” that it might be possible to predict and prevent dragon king events, said Gauthier. To make that happen, however, scientists would probably have to develop entirely new mathematical tools to identify the key variables in different complex systems, he adds.