StockBuz's Posts (662)

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Will Credit Cause A Slowdown

Saxo Bank thinks a slowdown in credit growth is bad news

IF THERE is a consensus at the moment, it is that the global economy is finally managing a synchronised recovery. The purchasing managers' index for global manufacturing is at its highest level for six years; copper, the metal often seen as the most sensitive to global conditions, is up by a quarter since May

But Steen Jakobsen of Saxo Bank thinks this strength will not last. His leading indicator is a measure of the change in private sector credit growth. This peaked at the turn of the year and is now heading down sharply. Indeed the change in trend is the most negative since the financial crisis (see chart). Since this indicator leads the economy by 9-12 months, that suggests a significant economic slowdown either late this year or early  in 2018. He says that

This call for a significant slowdown coincides with several facts: the ECB’s QE programme will conclude by end-2017 and will at best be scaled down by €10 billion per ECB meeting in 2018.  The Fed, for its part, will engage in quantitative tightening with its announced balance sheet runoff. All in all, the market already predicts significant tightening by mid-2018.

Given the role played by central banks in propping up the economy and markets since 2009, it is certainly plausible that their role will be vital in ending the recovery.  And while copper is a good leading indicator, so is the bond market. At the turn of the year, most people thought the ten-year government bond yield would rise as a Trump stimulus fulled the global recovery; the yield is now 2.06%, down from 2.44%.

Courtesy of TheEconomist

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Market Complexity Could Trigger the Next Crash

Complex systems are all around us.

By one definition, a complex system is any system that features a large number of interacting components (agents, processes, etc.) whose aggregate activity is nonlinear (not derivable from the summations of the activity of individual components) and typically exhibits hierarchical self-organization under selective pressures.

In today’s infographic from Meraglim we use accumulating snow and an impending avalanche as an example of a complex system – but really, such systems can be found everywhere. Weather is another complex system, and ebb and flow of populations is another example.

Markets are Complex Systems

Just like in the avalanche example, where various factors at the top of a mountain (accumulating volumes of snow, weather, temperature, geology, gravity, etc.) make up a complex system that is difficult to predict, markets are similarly complex.

In fact, markets meet all the properties of complex systems, as outlined by scientists:

1. Diverse
System actors have different points of view. (i.e. bullish, bearish, long, short, leveraged, non-leveraged, etc.)

2. Connected
Capital markets are over-connected, and information spreads fast. (i.e. chat rooms, phone calls, emails, Thomson Reuters, Dow Jones, Bloomberg, trading systems, order entry systems, etc.)

3. Interaction
Trillions of dollars of securities are exchanged in transactions every day (i.e. stocks, bonds, currencies, derivatives, etc.)

4. Adaptive Behavior
Actors change their behavior based on the signals they are getting (i.e. making or losing money, etc.)

And like the avalanche example, where a single snowflake can trigger a much bigger event, there are increasing signs that the complexity behind the stock market has also reached a critical state.

Markets in a Critical State

Here are just some examples that show how the market has entered into an increasingly critical state:

Record-Low Volatility
The VIX, an index that aims to measure the volatility of the market, hit all-time lows this summer.

Bull Market Length
Meanwhile, the current bull market (2009-present) is the second-longest bull market in modern history at 3,109 days. The only bull market that was longer went from the 1987 crash to the Dot-com bust.

Valuations at Highs
Stock valuations, based on Robert Schiller’s CAPE ratio (which looks at cyclically-adjusted price-to-earnings), are approaching all-time highs as well. Right now, it sits 83.3% higher than the historical mean of 16.8. It was only higher in 1929 and 2000, right before big crashes occurred.

Market Goes Up
Investor overconfidence leads investors to believe the market only goes up, and never goes down. Indeed, in this bull market, markets have gone up 67 of the months (an average gain of 3.3%), and have gone down only 34 months (average drop of -2.6%).

Here are some additional signs of systemic risk that make complex markets less stable:

  • A densely connected network of bank obligations and liabilities
  • Over $70 trillion in debt added since Financial Crisis
  • Over $1 quadrillion in notional value of derivatives
  • Non-bank shadow finance through hedge funds and securitization make risk impossible to measure
  • Increased leverage of banks in some markets
  • Greater concentration of financial assets in fewer companies

In other words, there are legitimate reasons to be concerned about “snow” accumulation – and any such “snowflake” could trigger the avalanche.

In complex dynamic systems that reach the critical state, the most catastrophic event that can occur is an exponential function of scale. This means that if you double the system, you do not double the risk; you increase it by a factor of five or 10

– Jim Rickards, author of Road to Ruin

The Next Snowflake

What could trigger the next avalanche? It could be anything, including the failure of a major bank, a natural disaster, war, a cyber-financial attack, or any other significant event.

Such “snowflakes” come around every few years:

1987: Black Monday
The Dow fell 508 points (-22.6%) in one day.

1994-95: The Mexican peso crisis
Systemic collapse narrowly avoided when the U.S. government bailed out Mexico using the controversial $20 billion “Exchange Stabilization Fund”.

1997: Asian financial crisis
East Asian currencies fell in value by as much as -38%, and international stocks by as much as -60%.

1998: Long Term Capital Management
Hedge fund LTCM was in extreme distress, and within hours of shutting down every market in the world.

2000: The Dotcom crash
Nasdaq fell -78% in 30 months after early Dotcom companies crashed and burned.

2008: Lehman Brothers bankruptcy
Morgan Stanley, Goldman Sachs, Bank of America, and J.P. Morgan were days away from same fate until government stepped in.

Shelter from the Avalanche

The Fed and mainstream economists use equilibrium theory, regressions, and correlations to quantify the markets. And while they pay lip-service to black swans, they don’t have a good way of forecasting them or predicting them.

Markets are complex – and only complexity theory and predictive analytics can help to shed light on their next move.

Alternatively, investors can seek shelter from the storm by investing in assets that cannot be digitally frozen (bank accounts, brokerage accounts, etc.) or have their value inflated away (cash, fixed-income). Such assets include land, precious metals, fine art, and private equity.

Courtesy of: Visual Capitalist

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China Plans To Ban Sales Of Fossil Fuel Cars Entirely

China’s big electric vehicle push is about to get even bigger: The country is planning to end the sale of fossil fuel-powered vehicles entirely, with regulators working currently on a timetable of when the ban will ultimately take effect, according to Bloomberg.

China is the world’s largest auto market, with 28.03 million vehicles sold last year, a boost in demand of 13.7 percent vs. 2015 sales numbers. The nation has already done a lot to incentivize manufacturers to develop and sell new EVs, including allowing foreign automakers to create a third joint venture with local automakers (a standard requirement for doing business in the country for auto OEMs) so long as it’s dedicated to the creation of EVs exclusively.

The government has also created a number of incentive programs for OEMs, including subsidies. This will add to its positive efforts to drive more EV sales in China with the ultimate negative condition on the other side – at some point, automakers just won’t be able to do business at all in the country if they’re still selling a mix of fossil fuel and electrified vehicles.

This isn’t the first time a governing body has said it would eventually phase out the sale of traditional fuel vehicles: France said it will stop selling fossil fuel cars by 2040 in July, and the UK has committed to the same timeline for sales of those vehicles.

Critics have suggested that a ban on fossil fuel vehicles is likely impractical, because it would stretch an already taxed supply chain, which has some hard limits in terms of the volume of lithium available for lithium-ion battery cells, for instance. But automakers are already responding to this rising trend with expanded EV model lineups and, in the case of Volvo for instance, plans to eventually sell exclusively all-electric or hybrid cars.

China’s timeline for establishing this ban will be crucial in terms of how quickly we see the global shift to EVs occur, as it’s going to be an immense lever in terms of automaker strategic planning internationally, as well as in the country.

Courtesy of TechCrunch

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Well, here it comes—September. It’s widely considered the worst month of the year for equities for good reason since it has historically seen the worst performance. Per Ryan Detrick, Senior Market Strategist, “September is the banana peel month, as some of the largest dips tend to take place during this month. Although the economy is still quite strong, this doesn’t mean some usual September volatility is out of the question—in fact, we’d be surprised it volatility didn’t pick up given how calm things have been this year.”

With the Federal Reserve, Bank of Japan, and the European Central Bank all set to announce interest rate decisions this month, and the S&P 500 Index up on a total return basis nine consecutive months as of the end of July, the stage is set for some fireworks in September.

Here’s some data to consider as September approaches:

• Since 1928, no month sports a lower average return than September, with the S&P 500 down 1.0% on average. February and May are the only other months that are generally in the negative, while July surprisingly tends to be the strongest month of the year.

• Since 1928, the S&P 500 has been higher in September only 43.8% of the time, which is by far the lowest amount—as no other month is less than 50%. December is up most often at 73.0%.

• Since 1950, September has been the worst month of the year down 0.5%, while the past 20 years it has been the second weakest month, with August faring worse.

• The worst September ever for the S&P 500 resulted in a 30% drop in 1931. In fact, no other month has had more 10% drops than September at seven. Interestingly, January is the only month that has never been down 10% or more.

• Over the past 10 years, September has been positive on average, with the S&P 500 up 0.1%. But it is worth noting that September has been lower each of the past three years.

• Since 1950, if the S&P 500 starts the month of September above its 200-day moving average (like 2017 will), it tends to do much better, as it is up 0.4% on average versus down 2.7% if it starts the month below the 200-day moving average.

• Last, August is historically a weak month as well. Generally, when the S&P 500 is lower in August what we tend to see in September is that the month is down as well. On average it’s been down 0.4%, right in line with the average monthly return.

IMPORTANT DISCLOSURES
*Please note: The modern design of the S&P 500 stock index was first launched in 1957. Performance back to 1950 incorporates the performance of predecessor index, the S&P 90.
The economic forecasts set forth in the presentation may not develop as predicted.
The S&P 500 Index is a capitalization-weighted index of 500 stocks designed to measure performance of the broad domestic economy through changes in the aggregate market value of 500 stocks representing all major industries.
The 200-day moving average (MA) is a popular technical indicator which investors use to analyze price trends. It is the security or index’s average closing price over the last 200 days.

Courtesy of lplResearch

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Watch The Potential Double Tops

Doubles Tops are forming in two key ETFs, the Semiconductor SPDR (XSD) and the Consumer Discretionary SPDR (XLY), and chartists should watch these important groups for clues on broad market direction in the coming week or two. First, let's talk about the Double Top. These patterns form with two peaks near the same level and an intermittent trough that marks support. A break below support confirms the pattern and targets a move based on the height of the pattern. 

Achtung! A Double Top is just a POTENTIAL Double Top until confirmed with a break below the intermittent low. In other words, the trend is still up as long as support holds. Furthermore, Double Tops are bearish reversal patterns and trend continuations are more likely that trend reversals. 

The chart above shows a potential Double Top brewing in XSD over the last three months or so. Because this is an ETF with dozens of moving parts (components), I am marking a support zone using the mid May low and the June low. A close below 60 would confirm the pattern and project a move to the 53 area. Note that the height of the pattern is 7 points (~67 to ~60). As long as XSD is near support, chartists should also be on guard for a bounce off support and break above first resistance at 63. The next chart shows a Double Top brewing in XLY with similar characteristics. 

A number of things can happen going forward on both charts. First, support could hold and the uptrend could continue from here. Second, support could fold and the Double Top could play out. Third, there could a support break and then a bounce off the rising 200-day EMA (bear trap). Just keep an open mind and prepare for different outcomes. 

The Semiconductor SPDR (XSD) is a broad-based ETF with 35 stocks. Quick! Can you guess the top two holdings? Stop for a moment and think.....Would you have guessed First Solar (FSLR 4.33%) and SunPower (SPWR 3.77%).? I certainly would not have guessed those two. According to SPDRs.com, the top ten stocks account for around 35% of the ETF. The Consumer Discretionary SPDR (XLY) is a market-cap weighted sector ETF with Amazon weighing in at a whopping 15.13%. According to sectorspdr.com, the top ten components account for around 57% of the ETF. Chartists interested in XLY should also watch AMZN, CMCSA, HD, DIS and MCD.

Courtesy of StockCharts

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“Low volatility could be ‘the quiet before the storm,’” Nobel laureate Robert Shiller told CNBC last week, adding: “I lie awake worrying.” Over the past 20 years, the CBOE Volatility Index (VIX) has closed below 10 on only 21 days, 13 of which have been in the past two months. The current streak of 270-plus days without a 5% drawdown in any of the major U.S. indices is the longest since 1996. Meanwhile, U.S. equity values continue to diverge from earnings — Schiller’s Cyclically Adjusted PE Ratio (CAPE) has only been higher two times in market history: 1929 and 2000.

Yet, despite the many bulls claiming low volatility is historically normal, and therefore not a warning sign, evidence is beginning to mount that U.S. equity markets may be near a volatility-driven tipping point. With the market consolidated (WILTW June 29, 2017) and buoyed by the lowest interest rates in 5,000 years, investors have taken on more and riskier leverage in search of yield. Compounding the risk, much of that leverage has been “justified” by passive strategies pegged to low volatility. As Baupost Group’s Jim Mooney warned last week: “Low volatility would not be a problem if not for strategies that increase leverage when volatility declines.”

If passive strategies have a bias to buy, they can also have a bias to sell — a threat we explored in WILTW June 15, 2017. With hundreds of billions of dollars of investments now linked to volatility, a spike in the VIX could trigger a devastating algorithmic sell cascade.

Time and again in these pages, we have stressed the need to look beyond the U.S. for opportunity. The longer volatility remains low, the more imperative this becomes. It is impossible to pinpoint when the low-volatility regime will end, but as Howard Marks stressed in an Oaktree client letter last week: “It’s better to turn cautious too soon…than too late after the downslide has begun.”

Mooney believes low volatility could be the harbinger of the next financial crisis. Business Insider synopsized his reasoning:

While leverage is not directly responsible for every financial disaster, it usually can be found near the scene of the crime,” Baupost’s president and head of public investments wrote in the letter. “The lower the volatility, the more risk investors are willing to or, in some cases, required to incur.”

Assets whose performance is linked to volatility include a huge amount of money…These funds, including quant funds and so-called risk parity funds, target a specific level of risk, and when volatility spikes, sending risk upwards, it can trigger selling…

As such, any spike in equity market realized volatility, even to historical average levels, has the potential to drive a significant amount of equity selling (much of it automated). Such selling would, in turn, further increase volatility which would call for more deleveraging and yet more selling.”

Wolf Street’s Wolf Richter pointed out last week that total outstanding leveraged loans in the U.S. reached $943 billion at the end of 2Q17. Moreover, covenant-lite loans — high-risk instruments issued by junk-rated borrowers, with few protections for creditors — made up 72.5% of that total, a record. Yet still, the amount of high-risk leverage in the market is likely even higher. Securities- based loans (SBLs) — or “shadow margin” — are often not disclosed by financial firms, meaning totals remain opaque. However, for the firms that have revealed statistics, growth rates suggest SBLs are also at record highs: Morgan Stanley’s SBLs have doubled since 2013 to $36 billion and Bank of America Merrill Lynch’s SBLs were at $40 billion at the end of 2016, up 140% from 2010.

Refusal to acknowledge the existence of risk has become a pandemic,” Richter writes. “This of course has been the explicit strategy of the Fed since the Financial Crisis — to push investors out ever farther toward the thin end of the risk branch.”

The meteoric rise of passive strategies — unbeholden to price discovery, endowed with the biases of their creators — has further encouraged investors to ignore risk. Jonathan Jacobson, founder of Highfields Capital Management, wrote in a recent letter to clients about why the increasing influence of quants is obfuscating market risk:

“We are convinced that “quant’ funds”, which have attracted hundreds of billions of dollars in the last few years and a significant portion of which use leverage, and whose models and various strategies are largely based on price action and correlations extracted from the reasonably-recent past when volatility has been low (largely of their own making), have contributed mightily to the illusion that market risk is low. As the money continues to flow into these strategies, this dynamic becomes self-fulfilling.”

Of course, there’s a flipside to that self-fulfillment. As we wrote back in June about the systemic threat created by passive strategies: “If a key sector failure, a geopolitical crisis, or even an unknown, black box bias pulls an algorithmic risk trigger, will the herd run all at once?” This is Mooney’s point as well: volatility spiking would trigger algorithms to deleverage, thus exacerbating the volatility, leading to even more deleveraging. Compounding the threat, VIX short positioning is at record levels, which could further expedite an unwinding:

So the question is, what could drive a spike in volatility? The obvious answer is central banks normalizing monetary policy. Many assume central bankers are aware unwinding QE could end the low-volatility regime and will act to protect the “new normal”. As history attests, this faith is misguided and dangerous. Yet, even if the majority is correct, that does not mean other volatility catalysts don’t exist.

Recently, J.P. Morgan equity derivatives strategist Marko Kolanovic highlighted one such potential catalyst. Financials and tech stocks have been moving in the same direction only 30% of the time of late, in stark contrast to the longer-term norm of 80%:

As CNBC wrote last week, this seesaw dynamic between tech and bank stocks is “happening in the context of an overall market that has become quite selective and eclectic, with stocks and sectors rotating in and out of favor with unusual alacrity.” The consequence is market balance and in turn, low volatility — tech accounts for 23% of the S&P 500 and financials have a 14.5% index weight, meaning they have the power to balance the market as long as one rises as the other one falls.

Citing 1993 and 2000 as evidence — years that saw low volatility and a steep drop in inter-stock correlation eventually return to historical norms — Kolanovic does not believe this divergence-driven stability will last. CNBC recaps his analysis: “It’s generally healthy for individual stocks and sectors to respond independently to incoming fundamental information, when the variation becomes extreme and drives volatility to extreme lows, the market can become unstable and vulnerable to a swift selling storm.

Seemingly every day for the past two weeks, the VIX has set new records. In a world defined by political turbulence, a time when U.S. markets appear increasingly frothy, when the Fed has a declared intention to unwind QE, the stability appears unnatural — a menacing codependence between financial engineering and greed.

As Goldman Sachs pointed out recently, there have been 14 low-volatility regimes since 1928 and all have required a large shock — namely a war or recession — to end. However, QE and the rise of passive strategies means history may tell us nothing about what’s to come. And the longer volatility remains suppressed, the bigger the leverage bubble grows and the more costly the correction will be once the passive herd is spooked. As Hyman Minsky once said: “The more stable things become and the longer things are stable, the more unstable they will be when the crisis hits.”

Courtesy of 13DResearch

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How Big Oil Will Die

It’s 2025, and 800,000 tons of used high strength steel is coming up for auction.

The steel made up the Keystone XL pipeline, finally completed in 2019, two years after the project launched with great fanfare after approval by the Trump administration. The pipeline was built at a cost of about $7 billion, bringing oil from the Canadian tar sands to the US, with a pit stop in the town of Baker, Montana, to pick up US crude from the Bakken formation. At its peak, it carried over 500,000 barrels a day for processing at refineries in Texas and Louisiana.

But in 2025, no one wants the oil.

The Keystone XL will go down as the world’s last great fossil fuels infrastructure project. TransCanada, the pipeline’s operator, charged about $10 per barrel for the transportation services, which means the pipeline extension earned about $5 million per day, or $1.8 billion per year. But after shutting down less than four years into its expected 40 year operational life, it never paid back its costs.

The Keystone XL closed thanks to a confluence of technologies that came together faster than anyone in the oil and gas industry had ever seen. It’s hard to blame them — the transformation of the transportation sector over the last several years has been the biggest, fastest change in the history of human civilization, causing the bankruptcy of blue chip companies like Exxon Mobil and General Motors, and directly impacting over $10 trillion in economic output.

And blame for it can be traced to a beguilingly simple, yet fatal problem: the internal combustion engine has too many moving parts.

The Cummins Diesel Engine, US Patent #2,408,298, filed April 1943, awarded Sept 24, 1946

Let’s bring this back to today: Big Oil is perhaps the most feared and respected industry in history. Oil is warming the planet — cars and trucks contribute about 15% of global fossil fuels emissions — yet this fact barely dents its use. Oil fuels the most politically volatile regions in the world, yet we’ve decided to send military aid to unstable and untrustworthy dictators, because their oil is critical to our own security. For the last century, oil has dominated our economics and our politics. Oil is power.

Yet I argue here that technology is about to undo a century of political and economic dominance by oil. Big Oil will be cut down in the next decade by a combination of smartphone apps, long-life batteries, and simpler gearing. And as is always the case with new technology, the undoing will occur far faster than anyone thought possible.

To understand why Big Oil is in far weaker a position than anyone realizes, let’s take a closer look at the lynchpin of oil’s grip on our lives: the internal combustion engine, and the modern vehicle drivetrain.

BMW 8 speed automatic transmission, showing lots of fine German engineered gearing. From Euro Car News.

Cars are complicated.

Behind the hum of a running engine lies a carefully balanced dance between sheathed steel pistons, intermeshed gears, and spinning rods — a choreography that lasts for millions of revolutions. But millions is not enough, and as we all have experienced, these parts eventually wear, and fail. Oil caps leak. Belts fray. Transmissions seize.

To get a sense of what problems may occur, here is a list of the most common vehicle repairs from 2015:

  1. Replacing an oxygen sensor — $249
  2. Replacing a catalytic converter — $1,153
  3. Replacing ignition coil(s) and spark plug(s) — $390
  4. Tightening or replacing a fuel cap — $15
  5. Thermostat replacement — $210
  6. Replacing ignition coil(s) — $236
  7. Mass air flow sensor replacement — $382
  8. Replacing spark plug wire(s) and spark plug(s) — $331
  9. Replacing evaporative emissions (EVAP) purge control valve — $168
  10. Replacing evaporative emissions (EVAP) purging solenoid — $184

And this list raises an interesting observation: None of these failures exist in an electric vehicle.

The point has been most often driven home by Tony Seba, a Stanford professor and guru of “disruption”, who revels in pointing out that an internal combustion engine drivetrain contains about 2,000 parts, while an electric vehicle drivetrain contains about 20. All other things being equal, a system with fewer moving parts will be more reliable than a system with more moving parts.

And that rule of thumb appears to hold for cars. In 2006, the National Highway Transportation Safety Administration estimated that the average vehicle, built solely on internal combustion engines, lasted 150,000 miles.

Current estimates for the lifetime today’s electric vehicles are over 500,000 miles.

The ramifications of this are huge, and bear repeating. Ten years ago, when I bought my Prius, it was common for friends to ask how long the battery would last — a battery replacement at 100,000 miles would easily negate the value of improved fuel efficiency. But today there are anecdotal stories of Prius’s logging over 600,000 miles on a single battery.

The story for Teslas is unfolding similarly. Tesloop, a Tesla-centric ride-hailing company has already driven its first Model S for more 200,000 miles, and seen only an 6% loss in battery life. A battery lifetime of 1,000,000 miles may even be in reach.

This increased lifetime translates directly to a lower cost of ownership: extending an EVs life by 3–4 X means an EVs capital cost, per mile, is 1/3 or 1/4 that of a gasoline-powered vehicle. Better still, the cost of switching from gasoline to electricity delivers another savings of about 1/3 to 1/4 per mile. And electric vehicles do not need oil changes, air filters, or timing belt replacements; the 200,000 mile Tesloop never even had its brakes replaced. The most significant repair cost on an electric vehicle is from worn tires.

For emphasis: The total cost of owning an electric vehicle is, over its entire life, roughly 1/4 to 1/3 the cost of a gasoline-powered vehicle.

Of course, with a 500,000 mile life a car will last 40–50 years. And it seems absurd to expect a single person to own just one car in her life.

But of course a person won’t own just one car. The most likely scenario is that, thanks to software, a person won’t own any.


Here is the problem with electric vehicle economics: A dollar today, invested into the stock market at a 7% average annual rate of return, will be worth $15 in 40 years. Another way of saying this is the value, today, of that 40th year of vehicle use is approximately 1/15th that of the first.

The consumer simply has little incentive to care whether or not a vehicle lasts 40 years. By that point the car will have outmoded technology, inefficient operation, and probably a layer of rust. No one wants their car to outlive their marriage.

But that investment logic looks very different if you are driving a vehicle for a living.

A New York City cab driver puts in, on average, 180 miles per shift (well within the range of a modern EV battery), or perhaps 50,000 miles per work year. At that usage rate, the same vehicle will last roughly 10 years. The economics, and the social acceptance, get better.

And if the vehicle was owned by a cab company, and shared by drivers, the miles per year can perhaps double again. Now the capital is depreciated in 5 years, not 10. This is, from a company’s perspective, a perfectly normal investment horizon.

A fleet can profit from an electric vehicle in a way that an individual owner cannot.

Here is a quick, top-down analysis on what it’s worth to switch to EVs: The IRS allows charges of 53.5¢ per mile in 2017, a number clearly derived for gasoline vehicles. At 1/4 the price, a fleet electric vehicle should cost only 13¢ per mile, a savings of 40¢ per mile.

40¢ per mile is not chump change — if you are a NYC cab driver putting 50,000 miles a year onto a vehicle, that’s $20,000 in savings each year. But a taxi ride in NYC today costs $2/mile; that same ride, priced at $1.60 per mile, will still cost significantly more than the 53.5¢ for driving the vehicle you already own. The most significant cost of driving is still the driver.

But that, too, is about to change. Self-driving taxis are being tested this year in Pittsburgh, Phoenix, and Boston, as well as Singapore, Dubai, and Wuzhen, China.

And here is what is disruptive for Big Oil: Self-driving vehicles get to combine the capital savings from the improved lifetime of EVs, with the savings from eliminating the driver.

The costs of electric self-driving cars will be so low, it will be cheaper to hail a ride than to drive the car you already own.


Today we view automobiles not merely as transportation, but as potent symbols of money, sex, and power. Yet cars are also fundamentally a technology. And history has told us that technologies can be disrupted in the blink of an eye.

Take as an example my own 1999 job interview with the Eastman Kodak company. It did not go well.

At the end of 1998, my father had gotten me a digital camera as a present to celebrate completion of my PhD. The camera took VGA resolution pictures — about 0.3 megapixels — and saved them to floppy disks. By comparison, a conventional film camera had a nominal resolution of about 6 megapixels. When printed, my photos looked more like impressionist art than reality.

However, that awful, awful camera was really easy to use. I never had to go to the store to buy film. I never had to get pictures printed. I never had to sort through a shoebox full of crappy photos. Looking at pictures became fun.

Wife, with mildly uncooperative cat, January 1999. Photo is at the camera’s original resolution.

I asked my interviewer what Kodak thought of the rise of digital; she replied it was not a concern, that film would be around for decades. I looked at her like she was nuts. But she wasn’t nuts, she was just deep in the Kodak culture, a world where film had always been dominant, and always would be.

This graph plots the total units sold of film cameras (grey) versus digital (blue, bars cut off). In 1998, when I got my camera, the market share of digital wasn’t even measured. It was a rounding error.

By 2005, the market share of film cameras were a rounding error.

A plot of the rise of digital cameras (blue) and the fall of analog (grey). Original from Mayflower via mirrorlessrumors, slightly modified for use here.

In seven years, the camera industry had flipped. The film cameras went from residing on our desks, to a sale on Craigslist, to a landfill. Kodak, a company who reached a peak market value of $30 billion in 1997, declared bankruptcy in 2012. An insurmountable giant was gone.

That was fast. But industries can turn even faster: In 2007, Nokia had 50% of the mobile phone market, and its market cap reached $150 billion. But that was also the year Apple introduced the first smartphone. By the summer of 2012, Nokia’s market share had dipped below 5%, and its market cap fell to just $6 billion.

In less than five years, another company went from dominance to afterthought.

A quarter-by-quarter summary of Nokia’s market share in cell phones. From Statista.

Big Oil believes it is different. I am less optimistic for them.

An autonomous vehicle will cost about $0.13 per mile to operate, and even less as battery life improves. By comparison, your 20 miles per gallon automobile costs $0.10 per mile to refuel if gasoline is $2/gallon, and that is before paying for insurance, repairs, or parking. Add those, and the price of operating a vehicle you have already paid off shoots to $0.20 per mile, or more.

And this is what will kill oil: It will cost less to hail an autonomous electric vehicle than to drive the car that you already own.

If you think this reasoning is too coarse, consider the recent analysis from the consulting company RethinkX (run by the aforementioned Tony Seba), which built a much more detailed, sophisticated model to explicitly analyze the future costs of autonomous vehicles. Here is a sampling of what they predict:

  • Self-driving cars will launch around 2021
  • A private ride will be priced at 16¢ per mile, falling to 10¢ over time.
  • A shared ride will be priced at 5¢ per mile, falling to 3¢ over time.
  • By 2022, oil use will have peaked
  • By 2023, used car prices will crash as people give up their vehicles. New car sales for individuals will drop to nearly zero.
  • By 2030, gasoline use for cars will have dropped to near zero, and total crude oil use will have dropped by 30% compared to today.

The driver behind all this is simple: Given a choice, people will select the cheaper option.

Your initial reaction may be to believe that cars are somehow different — they are built into the fabric of our culture. But consider how people have proven more than happy to sell seemingly unyielding parts of their culture for far less money. Think about how long a beloved mom and pop store lasts after Walmart moves into town, or how hard we try to “Buy American” when a cheaper option from China emerges.

And autonomous vehicles will not only be cheaper, but more convenient as well — there is no need to focus on driving, there will be fewer accidents, and no need to circle the lot for parking. And your garage suddenly becomes a sunroom.

For the moment, let’s make the assumption that the RethinkX team has their analysis right (and I broadly agree[1]): Self-driving EVs will be approved worldwide starting around 2021, and adoption will occur in less than a decade.

How screwed is Big Oil?


Perhaps the metaphors with film camera or cell phones are stretched. Perhaps the better way to analyze oil is to consider the fate of another fossil fuel: coal.

The coal market is experiencing a shock today similar to what oil will experience in the 2020s. Below is a plot of total coal production and consumption in the US, from 2001 to today. As inexpensive natural gas has pushed coal out of the market, coal consumption has dropped roughly 25%, similar to the 30% drop that RethinkX anticipates for oil. And it happened in just a decade.

Coal consumption has dropped 25% from its peak. From the Kleinman Center for Energy Policy.

The result is not pretty. The major coal companies, who all borrowed to finance capital improvements while times were good, were caught unaware. As coal prices crashed, their loan payments became a larger and larger part of their balance sheets; while the coal companies could continue to pay for operations, they could not pay their creditors.

The four largest coal producers lost 99.9% of their market value over the last 6 years. Today, over half of coal is being mined by companies in some form of bankruptcy.

The four largest coal companies had a combined market value of approximately zero in 2016. This image is one element of a larger graphic on the collapse of coal from Visual Capitalist.

When self-driving cars are released, consumption of oil will similarly collapse.

Oil drilling will cease, as existing fields become sufficient to meet demand. Refiners, whose huge capital investments are dedicated to producing gasoline for automobiles, will write off their loans, and many will go under entirely. Even some pipeline operators, historically the most profitable portion of the oil business, will be challenged as high cost supply such as the Canadian tar sands stop producing.

A decade from now, many investors in oil may be wiped out. Oil will still be in widespread use, even under this scenario — applications such as road tarring are not as amenable to disruption by software. But much of today’s oil drilling, transport, and refining infrastructure will be redundant, or ill-fit to handle the heavier oils needed for powering ships, heating buildings, or making asphalt. And like today’s coal companies, oil companies like TransCanada may have no money left to clean up the mess they’ve left.


Of course, it would be better for the environment, investors, and society if oil companies curtailed their investing today, in preparation for the long winter ahead. Belief in global warming or the risks of oil spills is no longer needed to oppose oil projects — oil infrastructure like the Keystone XL will become a stranded asset before it can ever return its investment.

Unless we have the wisdom not to build it.

The battle over oil has historically been a personal battle — a skirmish between tribes over politics and morality, over how we define ourselves and our future. But the battle over self-driving cars will be fought on a different front. It will be about reliability, efficiency, and cost. And for the first time, Big Oil will be on the weaker side.

Within just a few years, Big Oil will stagger and start to fall. For anyone who feels uneasy about this, I want to emphasize that this prediction isn’t driven by environmental righteousness or some left-leaning fantasy. It’s nothing personal. It’s just business.

HatTip to Member GT for this article.  Thank you buddy! 

Courtesy of NewCoShift

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It's All About Advertising

When people think of Facebook as a company, they mostly think of it synonymously with Facebook the social network. However, Facebook Inc. is much more than that, as today’s chart nicely illustrates. With WhatsApp, Instagram and of course the namesake Facebook and Messenger, the company owns four of the world’s largest social media / messaging services. Facebook alone reaches more than 2 billion people per month and both WhatsApp and Messenger also passed the billion-user milestone recently. Tencent, the Chinese company behind WeChat and Qzone might also boast a billion users in total, but still doesn’t come close to Facebook’s global footprint.

What all of the services mentioned below have in common, is their immense attractiveness to advertisers. Not only do they all boast hundreds of millions of users, but they also have the ability to target specific groups based on likes, dislikes and past behavior. That is why social media advertising has grown immensely over the past few years. In the U.S. alone, social media ad revenue is expected to reach $17.8 billion this year, with more growth to come in 2018 and beyond. For more information on social media advertising, including revenue forecasts for major markets, download our free report: “Digital Advertising: Social Media”.

Infographic: Facebook Inc. Dominates the Social Media Landscape | Statista
Courtesy of Statista

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Are Investors Getting Too Bulled Up?

Ran across this post and found it interesting although anything that's only been around 7-1/2 years is truly untested but only time will tell.  All eyes are on Congress for a break in taxes for the wealthy, as well as 'stumbles' from our leader and chief, Mr. Trump.  Between the Russia investigation and foreign relations (yikes!) the tension is building, or at least being applied by the left.  Will they reach the proportions where firms hit the 'sell' button? I have to say that September is coming -  the worst month for the market thanks to Mutual Fund profit taking at end of fiscal year.  Anything is possible.  Enjoy the ride.  From LyonsShare:

Sentiment indicators can be useful tools for investors, mainly on a contrarian basis. That is, generally when readings get overly bullish, it may signal a lack of remaining buyers in the market and vulnerability to a decline in prices. Conversely, when sentiment is extremely bearish, it is often a sign that selling has been overdone and prices are due for a bounce.

In general, there are two types of sentiment indicators: survey-based and real money gauges. We have found surveys to be less reliable than they once were. This may be due to the fact that sentiment is now widely known as a contrarian tool and survey respondents may be hesitant to look like the “dumb money”.

For that reason, we prefer real money sentiment indicators which show what investors are actually doing with their money. Folks can respond however they’d like in a survey, but at the end of the day they vote with their money. Therefore, these types of measures are typically better barometers of true investor sentiment.

One relatively new real money sentiment indicator is the subject of today’s Chart Of The Day. TD Ameritrade launched their Investor Movement Index® (IMX) the back in 2010 as a way of tracking investor sentiment based upon TDA customers’ money flows. In their words:

“The Investor Movement Index, or the IMX, is a proprietary, behavior-based index created by TD Ameritrade designed to indicate the sentiment of individual investors’ portfolios. It measures what investors are actually doing, and how they are actually positioned in the markets.

The IMX does this by using data including holdings/positions, trading activity, and other data from a sample of our 6 million funded client accounts.”

The reason we chose to make the IMX our Chart Of The Day today is because the latest reading (6.58), as of the end of June 2017, marked the highest reading in the 7-year history of the indicator. Additionally, it exhibited its 3rd largest month-over-month jump ever (+0.45), behind May and August 2016.

Now, before you go selling your entire portfolio, there are few factors that may mitigate one’s concern over this high reading. First off, the indicator is only 7 ½ years old.  In market indicator years, that makes the IMX but an infant. It has not even been through a complete market cycle yet. Therefore, we cannot be sure what the indicator is or is not capable of, outside of its very brief history.

Secondly, while the indicator is at an all-time high, the stock market is as well. And if ever there is a reasonable time for sentiment to be at all-time highs, it is when stocks are also at highs. It would be more concerning if the IMX was hitting new highs when it “wasn’t supposed to”, e.g., while the stock market was either declining or at least making lower highs.

For example, one of the larger jumps (+0.41) in the IMX’s history occurred in June 2015 — despite the fact that the S&P 500 lost more than 2% for the month. Of course, stocks were undergoing a significant intermediate-term top at the time and a sharp correction followed soon afterward.

We are not saying that an all-time high in this sentiment indicator is a welcomed data point. It is just that the conditions surrounding the latest reading do somewhat justify it — or at least reasonably explain it. However, we will certainly monitor this new sentiment tool closely in the months to come.

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A Timeline Of Future Technology

A Timeline of Future Technology

Making predictions about future technology is both fun and notoriously difficult.

However, such predictions also serve a very practical purpose for investors and business leaders, since failing to adapt to changing industry paradigms can completely decimate a business venture, turning it into the next Blockbuster, Kodak, or Sears.

Today’s infographic from Futurism rounds up some of the most interesting predictions about the future, from trusted sources such as Scientific American and The National Academy of Sciences.

Machines,Big and Small

The confluence of robotics, artificial intelligence, and increasing levels of automation is a prevailing trend throughout the projected timeline of future technology.

In less than 10 years, we will be able to control machines based on eye movements, while ingesting nano-sized robots to repair injuries from within our bodies. Later on, it’s also expected that the next wave of AI will be a reality: by 2036, predictive AI will be able to predict the near-future with impressive precision. Elections, weather, geopolitical events, and other dynamic systems will be analyzed in real-time using thousands or millions of data streams.

Even further down the line, human brains and machines will be continue to become closer to interfacing directly, creating all kinds of possibilities.

The Energy Revolution Continues

If you think the current progress in clean energy is exciting – wait until you see the technologies in the queue. The future of battery technology will include carbon-breathing batteries that turn CO2 into generate electricity, as well as diamond-based “nuclear batteries” that run off of nuclear waste. Meanwhile, solar power will be even cheaper as cells operate at near 100% efficiency, and commercial fusion power will be available by 2044. Climate change will also be tackled by interesting techniques, such as geoengineering with calcite aerosols, and carbon sequestration.

Timeline of Future Technology

More on Future Technology

Want to see more bold predictions about the future of technology?

Check out the future of alternative energy, the military, or the futuristic tech that could be inside your home.

Lastly, check out some very speculative predictions about what the world could look like, 100 years from now.

Courtesy of VisualCapitalist

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Growth in the global electric-vehicle market

With the recent announcement from Volvo that all vehicles will have electric engines in 2019 and phase out combustion engines, it becomes shockingly clear that electric is growing.................and faster than we have previously believed. Clearly Tesla (TSLA) has more competition than ever before so I bring you this piece from McKinsey to give you the breakdown. By the way, what does this mean for crude oil?  Just tossng it out there.

New research on electric mobility reveals Chinese OEMs produced 43 percent of EVs worldwide in 2016 and highlights other trends in supply and demand.

China has increased its lead in electric-vehicle (EV) production, according to new McKinsey research (Exhibit 1). Chinese OEMs produced 43 percent of the 873,000 EVs built worldwide in 2016. And the country now has the largest fleet of EVs on the road, overtaking the US market for the first time (see sidebar, “Our methodology”).

Exhibit 1
Electric Vehicle Index, ranking 10 countries based on market and industry performance

China extends EV industry leadership

China extended its industry leadership by making gains across all dimensions of the supply side of EVs, including current and projected production of EVs and their components, such as lithium-ion battery cells and electric motors. One important factor is that the Chinese government provides subsidies to the sector in an effort to reduce fuel imports, improve air quality, and foster local champions. Whereas Chinese OEMs accounted for 40 percent of EV production in 2015, this increased to 43 percent in 2016. Leading Chinese EV manufacturers all ranked among the top ten global EV producers in 2016. Given the rapid increase in production capacity by domestic suppliers, China’s lithium-ion battery-cell players increased their global supply share, reaching about 25 percent in 2016. This is mainly at the expense of Japanese companies, which lost significant market share year on year—though they still accounted for the greatest share in 2016, with around 48 percent. South Korean suppliers expanded their position and now hold 27 percent of the light-vehicle battery-cell market.

Overall, Germany and the United States also perform well in the industry, with no major changes in EV production share (23 percent and 17 percent, respectively). However, these countries saw slight losses with respect to electric-motor production due to China’s expansion.

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China’s domestic EV demand grows, while Europe stagnates

In addition to its leading role in EV supply, the market for EVs in China held steady in 2016. For the first time, China has overtaken the US market in the total number of EVs on the road. Cumulative EV sales reached 650,000 units in 2016, and the country increased new registrations for EVs by 70 percent year on year, to around 350,000 units (Exhibit 2). In comparison, Europe saw a sales increase of only 7 percent during the same period, after doubling them the prior year. The stagnation of the European market largely stems from a big drop in new registrations in the Netherlands, attributable to changes in the incentive scheme for plug-in hybrid vehicles. In the United States, EV sales were at 160,000 in 2016, a 37 percent increase.

Exhibit 2
growth in electric vehicles in China, Europe, and United States for 2014-16

The sales dynamic in China has been supported by a launch of many new EV models. Roughly 25 new EV models were introduced to the market in 2016. Overall, Chinese customers can now choose from around 75 EV models—the most of any market.

While China outperforms in absolute terms, the country does less well if considered in relative terms: in 2016, EV penetration in the overall light-vehicle market was only 1.4 percent. Norway outperforms here; about one in four cars sold in the country in 2016 was electric. Generous incentives are provided to EV customers in Norway, making EVs more affordable than cars with internal combustion engines. The Netherlands also has relatively high penetration, with an EV share of 5 percent, though sales decreased in 2016 (falling by 48 percent year on year). Sales dropped in 2016 after the country announced it would increase the company car tax for plug-in hybrids. Most other markets still do not exceed the 2 percent threshold. Japan was also affected by very low sales in the second half of 2016. These examples show that e-mobility development varies significantly by country.

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What Happens To Trading During a Market Crash?

It’s hard to predict when a stock market crash will occur, so the best defense is to be prepared.

Today’s infographic comes to us from StocksToTrade.com, and it explains what happens when a large enough drop in the market triggers a “circuit breaker”, or a temporary halt in trading.

What Happens To Trading in a Market Crash?

These temporary halts in trading, or “circuit breakers”, are measures approved by the SEC to calm down markets in the event of extreme volatility. The rules apply to NYSE, Nasdaq, and OTC markets, and were put in place following the events of Black Monday in 1987.

Circuit Breaker Rules

Previously, the Dow Jones Industrial Average (DJIA) was the bellwether for such market interventions.

However, the most recent rules apply to the whole market when a precipitous drop in the S&P 500 occurs:

  Before Feb 2013 After Feb 2013
Index Tracked DJIA S&P 500
Level 1 Threshold -10% -7%
Level 2 Threshold -20% -13%
Level 3 Threshold -30% -20%

Upon reaching each of the two first thresholds, a 15-minute halt in trading is prompted. This is the case unless the drop happens in the last 35 minutes of trading.

Upon reaching the third threshold (-20% drop in S&P 500), the day’s trading is stopped altogether.

Can Circuit Breakers Stop a Market Crash?

In theory, the use of circuit breakers can help curb panic-selling, as well as limit opportunities for massive gains (or losses) within a short time frame. Further, by creating a window where trading is paused, circuit breakers help make time for market makers and institutional traders to make rational decisions.

Regulators and exchanges hope that all of this together will give investors a chance to calm down, preventing the next market crash.

But do circuit breakers actually work? While they make logical sense, recent evidence from China paints a murkier picture.

The Illusion of Safety

In Paul Kedrosky’s piece from The New Yorker, titled The Dubious Logic of Stock Market Circuit Breakers, he makes some interesting points on the series of market crashes in China from late-2015 to early-2016.

To understand why circuit breakers can make markets less ‘safe,’ imagine that you’re a Chinese trader on a day when markets are approaching a five-per-cent decline. What do you do?

– Paul Kedrosky, The New Yorker

Kedrosky continues by explaining that a market participant in that situation would try to get as many sell orders in as possible, before the circuit breaker is triggered.

Further, when the markets re-open, the same trader would again sell immediately to avoid the second breaker (which triggers an end in trading for the day). Each time the breakers get triggered, it creates a market memory of the events, and traders try to avoid future shutdowns by selling faster.

Preparation is Key

Whether they work or not, it is essential for investors to understand the rules behind circuit breakers, as well as how markets think and react after these pauses in action.

In the event of a market crash, this preparation could help to make a difference.

Courtesy of VisualCapitlist

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The FANG Fantasy

With the “FANG” trade getting long in the tooth, so to speak, Wall Street analysts are now scrambling to formulate new acronyms to accommodate the most robust names in Big Tech today. FAANG, FAAA, FAAMG and now FANTASY have been brought forward adding companies like Microsoft, Tesla and Nvidia to the original FANG Fab-Four of Facebook, Amazon, Netflix and Google.

As market warning signs so, they don’t get better than this. Widely accepted market acronyms don’t evolve gracefully. They pop. Remember the BRICS (Brazil, Russia, India and China) and NINJA loans – (No income, no job)?

What most investors miss is that universally understood and enthusiastically embraced acronyms reflect peak sentiment. They are a market narrative boiled down to its most simplistic and easiest to grasp form. Repeated over and over and appearing everywhere, they are cognitive ease at its best. Like pieces of sea glass, all of the rough edges have been worn away over time and everyone can hold them.

In my book “Moods and Markets” I noted that “Big Truths” – like the simplistic market narrative “Homes are a great investment” – always materialize at peaks in sentiment.  At the top, everyone believes a very simple story. 

Market acronyms, though, are that simple story on steroids. Who needs a full five word phrase when four simple letters will do? Acronyms are a special breed of narrative found only at an extreme in mood.

What is so interesting at this particular juncture is that we don’t have just one acronym in full froth today, but two:  FANG and VIX – the latter being short-hand for the stock market’s volatility index. Investors, including now many retail investors, have been betting that the VIX is going to continue to fall – expecting that market fluctuations are going to get smaller and smaller over time. 

To these eyes, both acronyms appear to be peaking simultaneously, suggesting a very turbulent time ahead; not only for Big Tech, but for the markets more broadly. Again, acronyms pop, they don’t evolve. With two bursting at once, the sound may be deafening.

To be clear, nothing exceeds like excess and even the most simplistic market narrative can go on longer than you ever imagined. At the same time, the current scrambling for a successor to FANG suggests that time is quickly running out.

Courtesy of Peter Atwater via LinkenIn

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Y Combinator, one of best-known Silicon Valley accelerators, has an impressive track record of success. With well-timed investments in Dropbox, Stripe, and Airbnb, the startups in the company’s portfolio are now worth an aggregate of $600 billion in market capitalization.

While Y Combinator has made a clear impact on the tech sector, the company also launched an internal side project in 2007 that would end up becoming highly influential in a different and surprising way.

Its user-powered news aggregator called Hacker News, which is now visited by 20 million people per month, has become a mainstay for entrepreneurs, tech professionals, and venture capitalists around the world. Using a Reddit-like interface, users can upvote and downvote articles that they think have the most relevance to trends and issues affecting the tech sector.

Data Mining For Trends

Today’s charts come to us from Variance Explained, and they help to paint a picture of what topics have been trending on Hacker News over the last 3.5 years.

Using data from over 1 million subject lines, we can see which topics are being mentioned with increasing frequency by the site’s community of technology influencers.

="The

As you can see, words like “AI”, “artificial”, “bot”, “deep”, “neural”, and “learning” are key terms that have growing interest within the community. It shows that the buzz around AI and deep learning is widespread and happening on multiple fronts.

Donald Trump was also a hot topic of debate in Hacker News, as evidenced by the increase in mentions.

Cooling Off

Here are some of the words in the community used with decreasing frequency over the same 3.5 year timeframe:

The fastest-declining words in Hacker News titles

Over time, as the rubber hits the road, we get to see which ideas have staying power.

Google Glass, as cool as it was, ended up not directly revolutionizing how we use augmented reality. Likewise, Edward Snowden’s revelations about the NSA and surveillance seemed to have also dropped out of discussion.

On the flipside, some of these concepts also seem to have transitioned to the mainstream. Bitcoin and other altcoins, for example, are now more popular than ever before with a market capitalization of over $100 billion. Likewise, iPads, Gmail, and Kickstarter are pretty ubiquitous, but it could be argued that discussion on these topics is now pretty staid for the idea-hungry folks that frequent Hacker News.

Blockchain vs. Bitcoin

It’s also interesting to see the contrasting popularity of two related terms among Hacker News participants.

Bitcoin-related talk, at least on Hacker News, was hot in late-2013 after the price skyrocketed for the first time. The blockchain, on the other hand, took some time to pick up steam among influencers.

The popularity of Blockchain vs. Bitcoin on Hacker News

Fast-forward to today, and the concept of the blockchain is much more fleshed out.

It took time, but the blockchain is now considered to be a foundational technology that is affecting everything from how how stock markets work, to the proof of ownership for digital assets.

Courtesy of VisualCapitalist

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The Growth Of Data Breaches Worldwide

Courtesy of: Visual Capitalist

The graphic above shows a timeline of some of the biggest data breaches on record. Each bubble represents the number of records lost in any given breach, with the most sensitive data clustered toward the right side.

This data visualization comes to us from Information is Beautiful. Go to their site to see the highly-recommended interactive format that visualizes the same data, while providing additional details on each specific hack.

Before 2009, the majority of data breaches were the fault of human errors like misplaced hard drives and stolen laptops, or the efforts of “inside men” looking to make a profit by selling data to the highest bidder. Since then, the volume of malicious hacking (shown in purple) has exploded relative to other forms of data loss.

From Millions to Billions

Increasingly sophisticated hacking has altered the scale of data loss by orders of magnitude. For example, an “inside job” breach at data broker Court Ventures was once one of the world’s largest single losses of records at 200 million.

However, it was eclipsed in size shortly thereafter by malicious hacks at Yahoo in 2013 and 2014 that compromised over 1.5 billion records, and now larger hacks are increasingly becoming the norm.

Small But Powerful

The problems caused by hacks, leaks and other data breaches are not just ones of scale. For example, the accidental 2016 leak of information from spam/email marketing service River City Media stands out at an alarming 1.37 billion records lost. However, sorting by data sensitivity paints a different picture. The River City leak – represented by the larger blue dot below – is surpassed in severity by hacks at Yahoo, at web design platform Weebly, and even at adult video provider Brazzers.

Data Breaches Ranked by Severity

Much of the data lost in the River City hack was made up of long lists of consumer email addresses to be used for spam email distribution, while the other hacks listed compromised items like account passwords, banking information, addresses, phone numbers, or health records. While having your email address become the target for spam exploitation is a serious annoyance, the hacking of much more sensitive personal data has quickly become the norm.

The fact that more and more of our data is being stored “in the cloud” and among devices on the Internet of Things means that increasingly sensitive types of data are now more vulnerable than ever to being hacked. This looks to be even more cause for concern than the rapidly rising volume of records that have been exposed, whether intentionally or by accident.

Courtesy of VisualCapitalist

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Finding High Quality Companies 'Today'

We are having a hard time finding high-quality companies at attractive valuations.

For us, this is not an academic frustration. We are constantly looking for new stocks by running stock screens, endlessly reading (blogs, research, magazines, newspapers), looking at holdings of investors we respect, talking to our large network of professional investors, attending conferences, scouring through ideas published on value investor networks, and finally, looking with frustration at our large (and growing) watch list of companies we’d like to buy at a significant margin of safety. The median stock on our watch list has to decline by about 35-40% to be an attractive buy.

But maybe we’re too subjective. Instead of just asking you to take our word for it, in this letter we’ll show you a few charts that not only demonstrate our point but also show the magnitude of the stock market’s overvaluation and, more importantly, put it into historical context.

Each chart examines stock market valuation from a slightly differently perspective, but each arrives at the same conclusion: the average stock is overvalued somewhere between tremendously and enormously. If you don’t know whether “enormously” is greater than “tremendously” or vice versa, don’t worry, we don’t know either. But this is our point exactly: When an asset class is significantly overvalued and continues to get overvalued, quantifying its overvaluation brings little value.

Let’s demonstrate this point by looking at a few charts.

The first chart shows price-to-earnings of the S&P 500 in relation to its historical average. The average stock today is trading at 73% above its historical average valuation. There are only two other times in history that stocks were more expensive than they are today: just before the Great Depression hit and in the1999 run-up to the dotcom bubble burst.


(dshort.com)

We know how the history played in both cases – consequently stocks declined, a lot. Based on over a century of history, we are fairly sure that, this time too, stock valuations will at some point mean revert and stock markets will decline. After all, price-to-earnings behaves like a pendulum that swings around the mean, and today that pendulum has swung far above the mean.

What we don’t know is how this journey will look in the interim. Before the inevitable decline, will price-to-earnings revisit the pre-Great Depression level of 95% above average, or will it maybe say hello to the pre-dotcom crash level of 164% above average? Or will another injection of QE steroids send stocks valuations to new, never-before-seen highs? Nobody knows.

One chart is not enough. Let’s take a look at another one, called the Buffett Indicator. Apparently, Warren Buffett likes to use it to take the temperature of market valuations. Think of this chart as a price-to-sales ratio for the whole economy, that is, the market value of all equities divided by GDP. The higher the price-to-sales ratio, the more expensive stocks are.

This chart tells a similar story to the first one. Though neither Mike nor Vitaliy were around in 1929, we can imagine there were a lot of bulls celebrating and cheerleading every day as the market marched higher in 1927, 1928, and the first eleven months of 1929. The cheerleaders probably made a lot of intelligent, well-reasoned arguments, which could be put into two buckets: first, “This time is different” (it never is), and second, “Yes, stocks are overvalued, but we are still in the bull market.” (And they were right about this until they lost their shirts.)

Both Mike and Vitaliy were investing during the 1999 bubble. (Mike has lived through a lot of more bubbles, but a gentleman never tells). We both vividly remember the “This time is different” argument of 1999. It was the new vs. the old economy; the internet was supposed to change or at least modify the rules of economic gravity – the economy was now supposed to grow at a new, much faster rate. But economic growth over the last twenty years has not been any different than in the previous twenty years – no, let us take this back: it has actually been lower. From 1980 to 2000 real economic growth was about 3% a year, while from 2000 to today it has been about 2% a year.

Finally, let’s look at a Tobin’s Q chart. Don’t let the name intimidate you – this chart simply shows the market value of equities in relation to their replacement cost. If you are a dentist, and dental practices are sold for a million dollars while the cost of opening a new practice (phone system, chairs, drills, x-ray equipment, etc.) is $500,000, then Tobin’s Q is 2. The higher the ratio the more expensive stocks are. Again, this one tells the same story as the other two charts: Stocks are very expensive and were more expensive only twice in the last hundred-plus years.

What will make the market roll over? It’s hard to say, though we promise you the answer will be obvious in hindsight. Expensive markets collapse by their own weight, pricked by an exogenous event. What made the dotcom bubble burst in 1999? Valuations got too high; P/Es stopped expanding. As stock prices started their decline, dotcoms that were losing money couldn’t finance their losses by issuing new stock. Did the stock market decline cause the recession, or did the recession cause the stock market decline? We are not sure of the answer, and in the practical sense the answer is not that important, because we cannot predict either a recession or a stock market decline.

In December 2007 Vitaliy was one of the speakers at the Colorado CFA Society Forecast Dinner. A large event, with a few hundred attendees. One of the questions posed was “When are we going into a recession?” Vitaliy gave his usual, unimpressive “I don’t know” answer. The rest of the panel, who were well-respected, seasoned investment professionals with impressive pedigrees, offered their well-reasoned views that foresaw a recession in anywhere from six months to eighteen months. Ironically, as we discovered a year later through revised economic data, at the time of our discussion the US economy was already in a recession.

We spend little time trying to predict the next recession, and we don’t try to figure out what prick will cause this market to roll over. Our ability to forecast is very poor and is thus not worth the effort.

An argument can be made that stocks, even at high valuations, are not expensive in context of the current incredibly low interest rates. This argument sounds so true and logical, but – and this is a huge “but” – there is a crucial embedded assumption that interest rates will stay at these levels for a decade or two.

Hopefully by this point you are convinced of our ignorance, at least when it comes to predicting the future. As you can imagine, we don’t know when interest rates will go up or by how much (nobody does). When interest rates rise, then stocks’ appearance of cheapness will dissipate as mist on the breeze.

And there is another twist: If interest rates remain where they are today, or even decline, this will be a sign that the economy has big, deflationary (Japan-like) problems. A zero interest rate did not protect the valuations of Japanese stocks from the horrors of deflation – Japanese P/Es contracted despite the decline in rates. America maybe an exceptional nation, but the laws of economic gravity work here just as effectively as in any other country.

Finally, buying overvalued stocks because bonds are even more overvalued has the feel of choosing a less painful poison. How about being patient and not taking the poison at all?

You may ask, how do we invest in an environment when the stock market is very expensive? The key word is invest. Merely buying expensive stocks hoping that they’ll go even higher is not investing, it’s gambling. We don’t do that and won’t do that.

Courtesy of Mauldin

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A Big Move Lies Ahead

Past tense; that is.  A big move is coming in the S&P 500 and it will take everyone’s breath away. Simply put: The S&P 500 has traded in a multi-year consolidation range with a high of 2134 and a low of 1810. A breakout or breakdown out of this range could result in a measured technical move of the height of the range, i.e. 2134 – 1810 = 324 handles. Consequently a break toward the upside would target 2458 (15% above all time highs) and conversely a breakdown would target 1486 and represent a 30.4% correction off of all time highs.

I’ve outlined the bear arguments in detail in Feeding the Monster, so I won’t bother rehashing them here. However, in analyzing the larger market structures an interesting duality is emerging: A fight for control between the historic precedence of earnings and technicals and a very much divergent development in money supply, one of the key drivers behind stock prices since the financial crisis.

This duality can be summarized in one chart:

Speaking for a breakdown so far is the historical similarity in structure of the monthly RSI and a decrease in GAAP earnings since 2015. Furthermore the $SPX has broken its ascending trend line in 2015 coinciding almost perfectly with the peak in GAAP earnings. These 3 developments are bearish in any historical context.

Note though something curious has happened during the same time: While price has recovered dramatically since February the continued decrease in earnings has made stocks the most expensive in years with a GAAP P/E ratio north of 24.

trends

Another key consideration: M1 money supply has continued to rise and print new record highs, not really deviating from the path it has embarked on ever since the financial crisis.

The reasons are generally well known as the Fed is a key source of influence:

Fed balance sheet

While the Fed has ended QE3 in October 2014 and is supposedly on some sort of rate hike path the evidence shows that its balance sheet has not only not decreased but it has stayed in a range and even made new highs in 2015. Just like the S&P 500. Imagine that:

FRED bal ST

And this issue highlights the battle for control here and the argument for a break higher:

A: A potential continued increase in M1 money supply which just made a new all time high in April:

M1

B: Should earnings revert higher (against current trend) then the combination of increased money supply & improved earnings would support the notion of an equity move toward the upper measured move target.

And perhaps markets are anticipating this move as evidenced by a sudden breakout in the cumulative advance/decline index:

Cum NYAD

However, and possibly a warning sign that things are not as well as they suddenly seem: The $NYSE composite index just barely managed to get back to 2007 highs, a somewhat unimpressive result considering that it took over $4.5 trillion in Fed balance sheet expansion and a $10 trillion increase in US debt to get back to the same levels. And note it too, just like the $SPX, broke a key trend line in 2015:

NYSE comp

The bottom line: This is a big battle for control. On the one hand fundamentals and technicals suggest a breakdown of size may well be in the cards, while on the other hand, continued “highly accommodative” central bank policies coupled with perhaps an incremental relative improvement in earnings to come may result in a breakout making stocks even more expensive than they are now, the classic blow-off top scenario if you will. Clarity will only emerge once the range is decisively broken in either direction.

Whoever wins this battle gets the big move. 324 handles.

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Earnings Growth Likely Peaked In Q1

Note: The following is an excerpt from this week’s Earnings Trends report. You can access the full report that contains detailed historical actuals and estimates for the current and following periods, please click here>>>

Here are the key points:

•    The Q1 earnings is effectively over now, with results from 492 S&P 500 members already out. Total earnings for these companies are up +13.5% from the same period last year on +7.2% higher revenues, with 72.6% beating EPS estimates and 65.2% beating revenue estimates.

•    These results represent a notable improvement over what we have been seeing from the same group of companies in other recent periods. While growth reached the highest level in more than 5 years, a bigger proportion of companies have been able to beat estimates, particularly revenue estimates.

•    For the Retail sector, total Q1 earnings are up +1.7% from the same period last year on +3.1% higher revenues, with 60% beating EPS estimates and 50% beating revenue estimates. The sector’s Q1 results have been below other recent periods and are also among the weakest of all sectors this reporting cycle.

•    For Q2, total earnings for the S&P 500 index are expected to be up +5.8% on +4.8% higher revenues. The Energy, Finance, Technology, Construction and Industrial Products are expected to be big growth drivers in Q2, with the quarterly earnings growth pace dropping to +3.1% on an ex-Energy basis.  

•    Estimates for Q2 came down since the quarter got underway, but the magnitude of negative revisions nevertheless compares favorably to other recent periods.

The chart below shows how estimates for Q2 have evolved since the start of the period.

This trend of negative revisions ahead of the start of each reporting cycles is not new; we have been seeing this play out quarter after quarter for more than 3 years. The revisions trend has been moving in a favorable direction over the last two quarters and that same trend is even more at play in Q2 estimates. What this means is that while estimates for Q2 have come down, they haven’t come down as much as would typically be the case by this time in other recent periods.

Estimates for 12 of the 16 Zacks sectors have come down since the start of Q2, with Consumer Discretionary and Utilities suffering the largest declines in revisions. Estimates for the Tech sector remain effectively unchanged, while estimates for Transportation, Construction and Industrial Products sectors have gone up. The positive revisions to Deere & Company (DE) and Caterpillar (CAT) are a big reason for the Industrial Product sector’s improved earnings picture.

The actual Q1 earnings growth (+13.2%) turned out to be double the growth pace that was expected at the start of the reporting cycle (+6.6%). This magnitude of outperformance was unusual and above the recent quarterly trend. We know that actual Q2 growth will be higher relative to what is currently expected. But even if actual Q2 earnings growth turns out to be as high as was expected at the start of the quarter (+7.9%), it will still be below what was achieved in Q1.

In fact, we can project with a reasonable level of confidence that the Q1 earnings growth pace will be the highest for the next few quarters. Earnings growth has undoubtedly turned positive now, but the quarterly growth pace in the coming quarters will likely stay below what we experienced in Q1.  

The chart below shows quarterly earnings growth expectations beyond Q2.

Unlike the year-over-year growth pace, the dollar amount of total earnings are expected to be in record territory in the coming quarters, particularly in the second half of the year, as the chart below shows.

Q1 Earnings Season Scorecard

Total Q1 earnings for the 492 index members that have reported results are up +13.5% from the same period last year on +7.2% higher revenues, with 72.6% beating EPS estimates and 65.2% coming ahead of top-line expectations. The proportion of companies beating both EPS and revenue estimates is currently 51.8%.

The side-by-side charts below compare the growth rates and beat ratios for the 492 index members with what we saw from the same companies in other recent periods.

The comparison charts above show that growth as well as positive beats are tracking above historical periods. The proportion of companies beating revenue estimates is particularly notable, as is the revenue growth pace.

Please note that the positive Q1 results are broad-based and not narrowly concentrated. Sectors that beat revenue estimates at a proportion higher than the average for the S&P 500 index, which itself tracked above historical periods, included Autos (90% beat revenue estimates), Conglomerates (83.3%), Industrial Products (81.8% beating revenue estimates), Technology (78.3%), Basic Materials (75%), Transportation (73.3%), Construction (69.2%), Utilities (69%), Medical (67.9%), and Finance (68.1%). The Consumer Staples operators appeared to struggle, with the proportion of Consumer Staples companies beating revenue estimates the lowest of all 16 Zacks sectors.

Courtesy of MrTopStep

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The Big Picture

First and foremost let me point out that Ray Dalio, founder of investment firm Bridgewater Associates, has joined Twitter so I encourage you to follow him here.  Secondly I suggest you grab a cup of coffee or maybe the entire pot as he gradually lays out what he sees ahead for the market.  Enjoy!

Big picture, the near term looks good and the longer term looks scary. That is because:

  1. The economy is now at or near its best, and we see no major economic risks on the horizon for the next year or two,
  2. There are significant long-term problems (e.g., high debt and non-debt obligations, limited abilities by central banks to stimulate, etc.) that are likely to create a squeeze,
  3. Social and political conflicts are near their worst for the last number of decades, and
  4. Conflicts get worse when economies worsen.

So while we have no near-term economic worries for the economy as a whole, we worry about what these conflicts will become like when the economy has its next downturn.

The next few pages go through our picture of the world as a whole, followed by a look at each of the major economies. We recommend that you read the first part on the world picture and look at the others on individual countries if you’re so inclined.

Where We Are Within Our Template

To help clarify, we will repeat our template (see www.economicprinciples.org) and put where we are within that context.

There are three big forces that drive economies: there’s the normal business/short-term debt cycle that typically takes 5 to 10 years, there’s the long-term debt cycle, and there’s productivity. There are two levers to control them: monetary policy and fiscal policy. And there are the risk premiums of assets that vary as a function of changes in monetary and fiscal policies to drive the wealth effect.

The major economies right now are in the middle of their short-term debt cycles, and growth rates are about average. In other words, the world economy is in the Goldilocks part of the cycle (i.e., neither too hot nor too cold). As a result, volatility is low now, as it typically is during such times. Regarding this cycle, we don’t see any classic storm clouds on the horizon. Unlike in 2007/08, we don’t now see big unsustainable debt flows or a lot of debts maturing that can’t be serviced, and we don’t see monetary policy as a threat. At most, there will be a little touching the brakes by the Fed to slow moderate growth a smidgen. So all looks good for the next year or two, barring some geopolitical shock.

At the same time, the longer-term picture is concerning because we have a lot of debt and a lot of non-debt obligations (pensions, healthcare entitlements, social security, etc.) coming due, which will increasingly create a “squeeze”; this squeeze will come gradually, not as a shock, and will hurt those who are now most in distress the hardest.

Central banks’ powers to rectify these problems are more limited than normal, which adds to the downside risks. Central banks’ powers to ease are less than normal because they have limited abilities to lower interest rates from where they are and because increased QE would be less effective than normal with risk premiums where they are. Similarly, effective fiscal policy help is more elusive because of political fragmentation.

So we fear that whatever the magnitude of the downturn that eventually comes, whenever it eventually comes, it will likely produce much greater social and political conflict than currently exists.

The “World” Picture in Charts

The following section fleshes out what was previously said by showing where the “world economy” is as a whole. It is followed by a section that shows the same charts for each of the major economies. These charts go back to both 1970 and 1920 in order to provide you with ample perspective.

1) Short-Term Debt/Economic Conditions Are Good

As shown below, both the amount of slack in the world economy and the rate of growth in the world economy are as close as they get to normal levels. In other words, overall, the global economy is at equilibrium.

2) Assets Are Pricing In About Average Risk Premiums (Returns Above Cash), Though They Will Provide Low Total Returns

Liquidity is abundant. Real and nominal interest rates are low—as they should be given where we are in the longterm debt cycle. At the same time, risk premiums of assets (i.e., their expected returns above cash) are normal, and there are no debt crises on the horizon.

Since all investments compete with each other, all investment assets’ projected real and nominal returns are low, though not unusually low in relation to cash rates. The charts below show our expectations for asset returns (of a global 50/50 stock/bond portfolio). While those returns are low, they’re not low relative to cash rates.

Relative to cash, the ‘risk premiums’ of assets are about normal compared to the long-term average. So, both the short-term/business cycle and the pricing of assets look about right to us.

3) The Longer Term Debt Cycle Is a Negative

Debt and non-debt obligations (e.g., for pensions, healthcare entitlements, social security, etc.) are high.

4) Productivity Growth Is Low

Over the long term, what raises living standards is productivity—the amount that is produced per person—which increases from coming up with new ideas and implementing ways of producing efficiently. Productivity evolves slowly, so it doesn’t drive big economic and market moves, though it adds up to what matters most over the long run. Here are charts of productivity as measured by real GDP per capita.

5) Economic, Political, and Social Fragmentation Is Bad and Worsening

There are big differences in wealth and opportunity that have led to social and political tensions that are significantly greater than normal, and are increasing. Since such tensions are normally correlated with overall economic conditions, it is unusual for social and political tensions to be so bad when overall economic and market conditions are so good. So we can’t help but worry what the social and political fragmentation will be like in the next downturn, which, by the way, we see no reason to happen over the next year or two.

Below we show a gauge maintained by the Federal Reserve Bank of Philadelphia that attempts to measure political conflict in the US by looking at the share of newspaper articles that cover political conflict from a few continuously running newspapers (NYT, WSJ, etc.). By this measure, conflict is now at highs and rising. The idea of conflicts getting even worse in a downturn is scary.

Downturns always come. When the next downturn comes, it’s probably going to be bad.

Below, we go through different countries/regions, one by one.

Looking at the Individual Economic Blocs

United States

As shown below, the US is around equilibrium in the mid-to-late stages of the short-term debt cycle (i.e., the “in between” years), and growth remains moderately strong. Secularly, the US is at the end of the long-term debt cycle. Debt levels are high and have leveled off after a period of deleveraging. The Fed has started to tighten gradually, but interest rates remain low, so the Fed has limited room to ease in the event of a downturn. And as we’ve covered in prior Observations (so won’t go into here), the US is in a period of exceptional politicaluncertainty as the new administration’s policies continue to take shape.

Eurozone

While there are two Europes within Europe, we will talk about the Eurozone as a whole (as we have covered the different parts in other Observations). The region is around cyclical equilibrium, but this masks significant divergences between depressed periphery countries and Germany, where the economy is running hot. In response to ECB stimulation, growth has picked up a bit, but inflation is still very weak and below the ECB target. Secularly, Europe is also at the end of the long-term debt cycle. Debt levels are high and haven’t fallen much. Nominal interest rates on both the short and the long end are around zero and are priced to stay low for years. We won’t go into detail here, but Europe also faces one of the most challenging political backdrops due to the growing support for populism.

Japan

In Japan, policy makers are trying to reverse decades of ugly deflationary deleveraging and shift to a beautiful deleveraging. As shown below, over the last several years, the BoJ’s policies have produced a cyclical upswing and eased deflation. Japan is now around its cyclical equilibrium, growth rates have picked up a bit, and inflation is still very low but the economy is no longer in deflation. Secularly, Japan is at the end of the long-term debt cycle, with the highest debt levels in the developed world (which the BoJ is monetizing at the fastest rate). Debt is still rising, driven by government borrowing. Interest rates have been around zero for two decades and are priced to stay there.

China

We’ve previously described that China faces four big economic challenges (debt restructuring; economic restructuring; capital markets restructuring; and the balance of payments/currency issue) that are being well managed. We won’t go into these challenges here other than to emphasize that they are an important backdrop for the perspective shown below. Cyclically, overall levels of activity in China are neither too high nor too low; growth has accelerated and is now strong; and while inflation has picked up some, it remains modest. Debt levels are high and growing rapidly. Interest rates remain relatively low, though these have risen some recently. Under the hood, these aggregate conditions are the net of “two economies” that look very different: a slowing, heavily indebted “old economy” with pockets of excess capacity, and a steadily expanding “new economy” driven by higher-end industries and household consumption.

Emerging Markets ex-China

Obviously, this category aggregates many countries with many different sets of circumstances, which we won’t get into here. Overall, cyclical conditions in EM ex-China are a bit weaker than in the developed world, reflecting, that several of the largest countries (e.g., Brazil, Russia) are now recovering from balance of payments adjustments. But the longer-term picture is comparatively stronger. These EM countries haven’t yet seen much of a productivity slowdown akin to what the developed world has seen, and debt burdens remain low.

Courtesy of Ray Dalio @ LinkedIn

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