“Fake it till you make it”: The Dark Side of Bro Culture In Silicon Valley

Since around the turn of the century I've been trying to decide if the emphasis should be on the 'Sili' or the 'con' in Silicon Valley.

And, as I've mentioned elsewhere you can pretty much draw a straight line from Nietzsche's "There are no truths, only interpretations" through Derrida and the deconstructionists to the normalization of making shit up by postmodernist folks in the social sciences to today.

From Fortune:

The Ugly Unethical Underside of Silicon Valley

As the list of startup scandals grows, it’s time to ask whether entrepreneurs are taking “fake it till you make it” too far.

Vinod Khosla did not show up at TechCrunch Disrupt to be harangued by some smartass, know-nothing journalist. The venture capitalist came to talk about disruption and revolutions to an audience of 1,000 potential disrupters and revolutionaries, laptop glow illuminating their faces in a San Francisco warehouse.

But of course the journalist had to bring up Hampton Creek, the vegan-food company that had fashioned itself—and more important, valued itself—like a tech company. Khosla, a legend in Silicon Valley, was a Hampton Creek investor, alongside Peter Thiel’s Founders Fund and Salesforce CRM -0.44% CEO Marc Benioff. Despite media reports of shoddy science at the company on things like shelf-life testing, and an FDA battle over misleading labeling, Khosla declared Hampton Creek was “doing awesome.”

“Debatable,” the journalist, TechCrunch’s Jonathan Shieber, needled before beginning his next question.

Khosla cut him off with a “talk to the hand” motion and turned to the audience with a wide, this guy amirite? grin. “Here’s a journalist,” he said, “who doesn’t know what’s going on, has an opinion, just like he does, to make interesting stories.” He turned back to Shieber: “I know a lot more about how they’re doing, excuse me, than you do.”

This was in September 2015. And what Khosla didn’t know was that Hampton Creek’s employees and contractors had been covertly buying its jars of eggless mayo from grocery stores for more than a year, allegedly as a way to make the product appear more popular to its retail partners. It would be another year before Bloomberg Businessweek revealed the scheme, in an article featuring an animated GIF of founder Josh Tetrick’s face covered in squirts of mayonnaise. (Hampton Creek has denied wrongdoing, describing the buybacks as quality-control testing. Khosla declined to comment.)

 

RULE BREAKER: Parker Conrad’s startup Zenefits admitted violating state insurance rules. He’s now starting a new, similar company. 

Photo: Jim Willson—The New York Times/Redux

The startup community has a set response to this kind of news, and it sounds a lot like Khosla’s sniping. Blindly defend; it’s us against them. After the Wall Street Journal first exposed problems at blood-testing startup Theranos in 2015, for example, venture investors like Greylock’s Josh Elman and Y Combinator’s Sam Altman tweeted defenses against the one-sided “slam piece.”

But as scandals have piled up—and other negative stories have proved to be true—the defensive strategy hasn’t aged well. While some investors are standing by their tainted companies, others are taking pains to distance the bad actors from the rest of the startup pack. Theranos, which has since voided two years of its test results and faces a criminal investigation, is now described as an exception. Just one bad apple. (“Theranos doesn’t represent us, we are better,” a group of startup founders sang in the annual holiday video created by VC firm First Round Capital.) Likewise Zenefits, the human resources startup that admitted its employees had cheated on mandatory compliance training: a freak occurrence. #NotAllStartups.

Lending Club’s loan doctoring? That’s not what startups are about. Same for WrkRiot, the startup that abruptly shut down after an employee accused it of forging wire-transfer documents. Or Skully, the failed maker of smart motorcycle helmets, being sued for “fraudulent bookkeeping.” Or ScoreBig, the struggling ticketing site being sued by brokers. Or Rothenberg Ventures, the firm under investigation after using investors’ money to finance founder Mike Rothenberg’s side startup. (The firm says it informed investors.) Or Faraday Future and Hyperloop One, ambitious, well-funded companies now tainted by lawsuits and accusations of, respectively, overhype and of mismanagement. (Faraday has not commented on its suits; Hyperloop denies the accusation and had settled its suit.) Or any of the dozens of smaller shady accounting shortcuts, growth hacks gone awry, and other implosions too minor to make headlines....MUCH MORE

Yuck.

For a little palate cleanser let's head south about 350 miles: "Money, Murder and Sadomasochism: A Look At the L.A. Tech Scene".

Corn Futures In 2017: Analysts Weigh In

We're posting two of the seven analyst comments, Goldman because it's always good to know what they're telling the world and Rabobank because over the years they have shown some actual forecasting 'skill', in the forecast modeler's sense of the word.
Follow the link for the other five.

From Agrimoney:

Corn futures - will they ditch their losing streak in 2017?

Chicago corn futures look poised to record a further (if small) loss in 2016 – making it a third successive year of decline.

Indeed, futures look set to record their weakest finish to a calendar year since 2005, with prices weighed by the boost to supplies from another record US crop, which more than offset support to values from a weaker-than-expected Brazilian safrinha corn harvest.

Still, after 2005, corn prices went on quite a rally, rising in five of the six following years.

Will low prices be the cure for low prices this time, in persuading farmers to cut corn acreage? Or will the market be depressed by a, likely, improved Brazilian safrinha crop?

Experts give their views on the prospects for corn prices in 2017....

...Goldman Sachs

Despite concerns late last spring that La Nina weather conditions would weigh on growing conditions, the US 2016-17 harvest ended up record large for both corn and soybeans.

Further, with only weak La Nina weather conditions currently, the beginning of the South American growing season is so far taking place under favourable conditions.

As a result, we expect that under normal weather conditions going forward corn and soybeans prices will decline back to their marginal costs of production over the coming year to limit further inventory builds.

Continued strong soybean demand from China leaves us, however, forecasting that soybeans prices will continue to trade at a historically elevated premium over corn prices to continue to incentivize acreage allocation....

...Rabobank

The ongoing global stockbuilding of corn is forecast to come to a halt in 2016-17, and 2017-18, we expect the first worldwide stock decline since 2009, moving the stocks-to-use ratio to 19%, the lowest in four years.

We need to add clarity to one fact in this equation – China. Due to changes to the corn subsidy policy, the country is expected to cut its stocks by about 10m tonnes n 2016-17 and by about twice as much the year after.

While the overall stocks in the world, excluding China, will remain at a comfortable level, they are expected to shrink 6% year on year in 2017-18.

Assuming normal weather conditions in South America… this should result in an increase of the combined corn crop in Brazil and Argentina of about 26%, or 25m tonnes.

Our base case price forecast leaves Chicago corn prices in a quarterly average $3.40-3.65 a bushel range, pressured by large supplies, and supported by record large demand and continued large-scale farmer storing in the US....

...MORE

  
http://www.agrimoney.com/feature/corn-futures---will-they-ditch-their-losing-streak-in-2017--482.html

Appeals Court Holds That SEC Administrative Law Judges Are Unconstitutional

From the Volokh Conspiracy at the Washington Post:

The Volokh Conspiracy by Jonathan H. Adler 9:12 am

The U.S. Court of Appeals for the 10th Circuit has bestowed a holiday gift on all of us administrative law nerds (especially for those who should be grading exams). Today, in Bandimere v. SEC, a divided panel held that the Securities and Exchange Commission’s administrative law judges (ALJs) are unconstitutional. Judge Matheson wrote for the court, joined by Judge Briscoe (who also wrote a concurring opinion). Senior judge McKay dissented. This decision is potentially quite significant and creates a circuit split on the underlying Appointments Clause question.
Here’s Judge Matheson’s summary of the opinion:

When the Framers drafted the Appointments Clause of the United States Constitution in 1787, the notion of administrative law judges (“ALJs”) presiding at securities law enforcement hearings could not have been contemplated. Nor could an executive branch made up of more than 4 million people, most of them employees. Some of them are “Officers of the United States,” including principal and inferior
officers, who must be appointed under the Appointments Clause. U.S. Const. art. II, § 2, cl. 2. In this case we consider whether the five ALJs working for the Securities and Exchange Commission (“SEC”) are employees or inferior officers.
Based on Freytag v. Commissioner of Internal Revenue, 501 U.S. 868 (1991), we conclude the SEC ALJ who presided over an administrative enforcement action against Petitioner David Bandimere was an inferior officer. Because the SEC ALJ was not constitutionally appointed, he held his office in violation of the Appointments Clause.

For those who forget, the Appointments Clause, in Article II, section 2 of the Constitution, provides, in relevant part:

[The President] shall nominate, and by and with the Advice and Consent of the Senate, shall appoint . . . Officers of the United States, whose Appointments are not herein otherwise provided for, and which shall be established by Law: but the Congress may by Law vest the Appointment of such inferior Officers as they think proper, in the President alone, in the Courts of Law, or in the Heads of Departments.

At issue in Bandimere is whether the SEC’s ALJs are “officers” for the purposes of this clause, and in particular “inferior” officers who may be appointed by heads of departments, such as the chair of the SEC. This matters because SEC ALJs are not so appointed. Rather, they are selected through an internal administrative process.

The panel majority concluded that the ALJs are constitutional officers because, among other things, they exercise significant discretion in carrying out “important functions” delegated by statute, including the imposition of liability and sanctions on those found to have violated relevant SEC rules....MORE

Société Générale's Albert Edwards Not His Usual Jolly Self (II)

Still, all in all, doing better than that time we posted "Société Générale's Albert Edwards Descends Into A Nightmare World of Dream Demons and Market Depravity".

From Bloomberg Gadfly:

Dec 28, 2016 1:00 AM EST

The great bond selloff is no match for Albert Edwards.

Societe Generale's top-rated global strategist and perennial doom monger is hanging on to his long-held view for yields to turn substantially negative. Never mind all the chatter about the end of the 35-year bull market in bonds and the Great Rotation back into stocks, and that President Trump's spending means inflation is back for good.

Trumpled Underfoot

U.S. bonds hardest hit by prospects for rising inflation under Trump...

...The herd has spoken, and Edwards doesn't buy it. And for those of us who remember that ignoring outliers is what got us into the financial crisis in the first place, he's worth listening to.

Don't Stop Me Now I'm Having Such a Good Time

And we're off to the races as equities are lovin' The Donald...

 

To be fair, he's not completely off piste. Near term, he sees U.S. inflation picking up to about 2.5 percent to 3 percent and the 10-year yield headed to 3.25 percent, same as a lot of people.

 

The similarities end there. For Edwards, this is merely the natural end of the growth phase of the business cycle, and in the normal order of things should be swiftly followed by a recession.

But this won't be just any recession. Wage growth is now pretty close to its pre-crisis average and he says it should accelerate in the early part of 2017. That will force the the Fed to raise rates at the wrong time, as growth sags, and for the wrong reasons, focusing on pay rather than the underlying economic weakness.

Got Yourself a Wages Problem?

The Fed's preferred survey diverges from the one favored by SG's Albert Edwards, with different implications for the growth and inflation outlook...MUCH MORE

News You Can Use: "How To Invest In The New World Order"

Putting aside the NWO jokes, there are some profound implications if this thesis is correct.
From Bawerk.net:

In our latest Toward a New World Order, Part III we ended by promising to look closer at investment implications from the political and economic shift we currently find ourselves in; and that story must begin with the dollar. While known to the investing public for years, the Bank of International Settlements (BIS) recently acknowledge that the real risk-off / risk-on metric in global markets is the dollar and nothing else.

In the chart below, which we recreated from an absolute brilliant presentation by Macro Intelligence 2 Partners via RealVision-TV, we see the potential scale of the coming “dollar-problem”.  The dollar moves in cycles as most things. The lower extreme around 84, only broken when Bernanke pushed through QE2, means financial conditions for emerging markets and other commodity producing economies have gotten so out of hand that conventional risk-metrics finally lead investors to pull back. The trigger, as can be seen in the chart, is often policy driven, but the underlying structural imbalance has been building for years, if not decades, prior.

Before we move on it is of utmost importance to understand that many of the dollar liabilities accumulated outside the United States are not backed by actual dollars, but are rather claims to dollar proper. This is the infamous Eurodollar market whereby banks, mostly international European ones, fund various economic activities by issuing claims to dollars, but for which no such dollars exists.  Think of it as another layer of fractional reserve lending on top of fractionally created money in the first place.

When risk metrics stray too far from what is considered prudent, investors start to pull money out from emerging markets, and obviously demand that their investments are paid out in dollars. To comply, international banks scramble to get hold of as many dollars as they can in the shortest time possible in order to fulfil their part of the bargain. The value of the dollar jumps as demand suddenly outstrips supply. Financial conditions in emerging markets tighten significantly and it becomes impossible to fund further expansion. Emerging market banks, with dollar liabilities and LCU assets are particularly vulnerable. The boom turns to bust as the Eurodollar market breaks. If the cycle gets out of hand, as it did from 2008 onwards, banking solvency is not only limited to local emerging market banks, but to the international banking community at large.

Taking a closer look at the previous dollar cycles, as represented by the real broad based dollar index we find that the initial shock pushes the dollar 20 – 25% higher from its low. It then pauses, drops 5% before starting a second leg higher (we outlined this process back in October). This is exactly where we are at now and if history repeats itself, which we believe it will, a new financial crisis is brewing just under the surface as the dollar moves into its second leg.

There are also other compelling arguments for the strong dollar case. If President-Elect Trump moves forward with his policy promises, such as changing the tax-system in accordance with the principle of destination based taxation; exports will be tax exempt, while imports will fully taxed at the corporate rate. The dollar may strengthen as much as 10 – 15% on this tax alone. Furthermore, if American companies repatriate some of their trillions held abroad it will put additional pressure on the price of dollars. Some may argue that dollars held in Wall Street are just as fungible as those held in Tokyo, Hong Kong or London, but given new money market regulations that may no longer be the case. Prime funds are starved of cash, while those investing in government bills are flush. It is therefore highly likely that repatriated cash will be stuck in New York money markets and create additional pressure on Eurodollar markets....MORE 

HT: ZeroHedge (don't buy gold)

As NVIDIA Notches Its 10th Straight Daily Gain, Lots Of People Say Nice Things...HOWEVER (NVDA)

Ten days in a row, 30%.
NVIDIA is far and away the best performing stock in the S&P 500, leading #2 ONEOK by something like 90 percentage points.

On Dec. 19th Yahoo Finance named NVDA their "Stock of the Year" in a longform article.

On Dec. 23 Quartz declared "In the race to build the best AI, there’s already one clear winner".

Today the Wall Street Journal's Moneybeat blog posted:

The New Kings of the S&P 500: Semiconductor Stocks
Move over FANG. There are new kings of the S&P 500 this year.

Semiconductor stocks have been all the rage in 2016, with the PHLX Semiconductor Index jumping more than 41%. As the sector surged, a $709 million iShares ETF tracking the index attracted $140.1 million in net new money in 2016, according to Morningstar.

The broader market has been no match for the chip-makers, even though the S&P 500 is up more than 11% this year, and the index’s technology firms are up 14%.

Sure, semiconductor firms may not have the same household recognition as Facebook, Amazon, Netflix, and Google-owner Alphabet, which all provided much-needed support to the market in 2015, and collectively earned the acronym FANG.

But chip-maker Nvidia is up over 250% in 2016, including 5.7% on Monday, making it the best performer in the S&P so far this year. What’s more, it’s already topped the 134% rise last year in Netflix, which was the best performer in 2015. (For the record, Nvidia was the fifth-best performer last year, up 64%.)

Nvidia has been benefiting from strong earnings, driven by its gaming segment which offers graphics processors used in the PCs meant for hardcore video-gamers. After its third-quarter results in November, the stock jumped nearly 30%.

The company’s also been a pioneer in developing deep learning and artificial intelligence technologies, which has excited investors, according to William Stein, technology equity-research analyst at SunTrust Robinson Humphrey. That’s been helped along by its use of software that makes it easy to develop applications with the technology.

“Right now, it seems pretty clear [Nvidia] is taking the lead, and I think it’s because of its development toolkit,” Mr. Stein said.

It’s not just Nvidia that’s getting a boost, even if it is outperforming based on its own unique circumstances.....MORE

Just to be clear, NVIDIA created those 'unique circumstances' by investing $2 billion into chip R&D for their P100 offering:

Sunday May 15, 2016
NVIDIA: A $2 Billion Chip to Accelerate Artificial Intelligence (NVDA)

First a heads-up. The technical trading gurus at Investor's Business Daily are saying take profits after Friday's big move, now 20% above their buy point. I don't think so but it all depends on your time frame.

And whether you have the discipline to buy back in should the stock not pull back.
(see links below for some of the things driving the stock)

On the other hand it's not like the stock is unknown and there are hordes of naïfs who have yet to discover it. NVDA was the fourth-best performer on NASDAQ in 2015 and through Friday is up 95% in 52 weeks and 60% since the overall market bottomed on Feb. 11.

FinViz

Here's some background from MIT's Technology Review, April 5:...

The stock had closed the prior Friday the 13th at $40.98 on a big earnings gap up.
And we were disagreeing with Investor's Business Daily, usually not a good thing to do.
Now however....at 116.49 up $6.71 (+6.11%) after daily and all-time top-ticks at $116.80....From IBD, Dec. 27:

Nasdaq Leads Gains, Apple Up; Did Nvidia Just Signal A Correction Is Near? 

Stocks added to recent gains with four trading days remaining in the year as a key survey on U.S. consumer confidence hit its highest level since August 2001.

Meanwhile, Nvidia (NVDA) marked its 10th straight gain Tuesday, rising more than 29% over that long stretch. On Tuesday, shares rose more than 5% to 115.93 and hit a new all-time high of 116.65.

Such a robust advance over a narrow period of time, on top of strong gains over the past nine months, is equivalent to the traditional climax run, a key IBD sell signal that carries the most weight during a market that has reached bubblelike conditions.

It's very hard to call the current equities market "bubblelike," even if so-called price-to-earnings valuations of the S&P 500 are above historical averages. Despite a quarter-point hike in interest rates earlier this month, and plans by the Federal Reserve to possibly raise rates three more times in 2017, the speed in which the money supply will tighten does not appear to be affecting the yield curve lately.

Nonetheless, Nvidia holders can decide to sell at least a portion of their position and get prepared for the inevitable correction and new base building that follows.

Normal cup bases range from a decline of 12% from high to low to as much as 33% to 35%. However, in the case of a stock as strong as Nvidia, corrections in the range of 40% to 50% or more are not uncommon. Cisco Systems (CSCO) presented such a precedent during the 1994-to-1995 market pullback; after a huge from its initial IPO base breakout in October 1990, the internet gear maker fell from 40.75 to 18.75 from March 1994 to July that year, a 54% decline....MORE

We agree and start to lighten up right here, right now.
And any weakness in the overall market means lighten up some more.

"The Future of Driving Is Now a Gold Rush"

Just keep in mind who actually makes money in gold rushes.
From Backchannel: 

A crowded field of car companies, tech giants, and startups is racing to get self-driving cars into the hands of drivers ASAP.
 

Blink and you might miss the moment automated vehicles go mainstream. At some point in 2017, a fully autonomous Tesla will blast across the country en route from Los Angeles to New York. The person sitting in the front left seat — let’s no longer call her the driver — will be free to watch a movie, drink a latte, or wave to locals as she zips past. If Elon Musk has his way, the tech will then roll out to drivers in 2018.

That timeline might be optimistic, but at least one thing is clear: 2017 is the year in which self-driving cars of numerous makes will embark on ambitious rounds of testing. Both Ford and BMW will send their autonomous cars through their paces in Europe. VW just launched its smart mobility brand Moia, with a focus on self-driving shuttles, and Volvo is pushing ahead with plans to give 100 self-driving XC90 crossovers to consumers in Gothenburg, Sweden.

Not to be outdone, the big technology firms are also sending their cars out into the world. Baidu has started offering public rides along a two-mile stretch of road in China, while Uber will likely expand its passenger trials beyond Pittsburgh and San Francisco. Lyft and even Apple are likely to make self-driving news in the coming year, as well.

This rush to deployment has caught some industry watchers by surprise. For years, a single company — Google — had hogged the headlines for tinkering with robotic vehicles and quietly wooing regulators. Then, in 2015, a horde of startups and newcomers burst onto the scene, eager to explore the boundaries of self-driving technologies—and the rules surrounding them.

“2017 will show us that limited deployments are technically, legally, and socially possible, even under today’s laws,” says Bryant Walker Smith, a professor at the University of South Carolina.

The cars themselves, with their distinctive sensor rigs mounted onto their rooftops, will be most visible as they putter down our roads. Behind the scenes, their makers are hurrying to iron out the technical, regulatory, and economic details needed so that one day somewhat soon, most of us will get to take our stupendously fallible meat gloves off the wheel.

From the tech side, this reality seems imminent. The prices of these cars’ most important sensors are plummeting. Laser-ranging lidar units — the things that build up a 3D image of the car’s surroundings — used to cost multiples of the cars on which they were mounted. Now they are priced in the thousands or even hundreds of dollars. Radars, which help pinpoint other road users, are also getting smaller and cheaper, and today’s high-definition video cameras are so cheap they are almost free.

New approaches are around the corner, too. Israeli startup Oryx Vision is working on what it calls coherent optical radar, a system that uses a terahertz infrared laser and clever microscopic antennas to scan the roadway further ahead and in more detail than lidar — and without the danger of being blinded by sunlight or fog. It hopes to build a demo unit by the end of 2017 with thousands of tiny nanoantennas on a chip, eventually costing just a few dollars.

The price drops and gains in performance amount to “a continuous stream of significant advancements in all perception-related technologies,” says Bobby Hambrick, CEO of AutonomouStuff, a supplier of automotive technologies.

The computing power to handle this firehose of sensor data is also becoming more widely accessible. Nvidia now offers an off-the-shelf Drive PX 2 self-driving computing platform, which is likely to feature in robocars from Tesla, Baidu, and others. But it faces stiff competition from automotive suppliers Bosch and Delphi, as well as two Bay Area startups founded by ex-Googlers — Nuro.ai and an as-yet-unnamed company being run by the company’s well-respected former self-driving car lead, Chris Urmson.

And then of course there is Google itself, which has finally spun out its 58 autonomous vehicles, two million miles of self-driving experience, and legion of engineers into a standalone company called Waymo. Waymo seems to be focusing on partnerships with car makers rather than developing its own self-driving prototype.

For this is 2017’s real prize: to develop an operating system that can scale beyond a few experimental autonomous cars to power tomorrow’s mass-produced self-driving fleets. Waymo’s first step in that direction is a partnership with Fiat Chrysler that will evolve next year into a ridesharing scheme using 100 Pacifica minivans.

Waymo has so far shown no inclination to hand over its platform for free, as Google did with its Android smartphone software. But there are others who believe that collaboration and even open sourcing are the future of autonomous transportation.

The notoriously secretive Apple recently suggested to the National Highway Traffic Safety Administration that companies should share de-identified data from crashes and near misses, while Comma.ai founder George Hotz has released open-source software and hardware for lane keeping assist and adaptive cruise control.

Hotz thinks that Comma.ai’s software could become the Android of self-driving cars, used by a network of car makers to which it can later provide profitable services. At the very least, making code and data freely available should prime the next generation of autonomous engineers.

Udacity, an online education provider that offers rapid qualifications in high-tech subjects, has released 238GB of driving data to self-driving self-starters, while the Japanese Autoware project offers a full autonomous software stack for free. “We’ll continue to see more momentum around the open-sourcing of self-driving car tech, and more releases of open driving datasets,” says Oliver Cameron, head of Udacity’s self-driving program.

The first to benefit from cheaper, turnkey self-driving solutions could be the youngest car makers. Startups Lucid Motors, LeEco, and NextEV have recently unveiled luxury cars with self-driving hardware, to be followed at January’s CES show by Faraday Future. All are controlled by or have significant investment from Chinese firms, and all have been subject to questions about funding their prototype vehicles through to production....MUCH MORE

"Brent curve signals oil tanks will start emptying in second half of 2017"

John Kemp at Reuters, Dec. 21:

OPEC and non-OPEC oil producers have agreed to reduce their combined output by more than 1.7 million barrels per day for six months from January 2017.

But the agreement contains a provision that it can be extended for a further six months, subject to market conditions.

Oil traders are betting on an extension, with most of the rebalancing of the oil market expected to occur in the second half of 2017.

Storage tanks are expected to remain fairly full throughout the first six months of the year and only start emptying from June (tmsnrt.rs/2hcnjbu).

Brent time spreads, the difference between futures prices for different months, provide an insight into how traders expect stocks to behave.

Brent futures prices remain in a contango through the first half of 2017, reflecting the need to cover the costs of storing and financing large volumes of crude (tmsnrt.rs/2i0JU7A).

But the contango starts to narrow significantly around June and disappears entirely by the end of the northern hemisphere summer (tmsnrt.rs/2i0Jiia).

The current structure of futures prices implies it will no longer be necessary or financially viable to store such large volumes of crude from the third quarter onwards.
The futures price curve contains an expectation about the state of supply, demand and the demand for storing oil.

Like any other forecast, the curve can be wrong. The oil market could rebalance faster or slower than currently expected.

For example, traders expected stocks to start drawing down from the middle of 2016, and instead they continued to increase.

But the curve does provide the best indication that we have about the expected timescale for rebalancing and stock draws.

The curve implies a modest drawdown in stocks is expected during the first half and then a much faster drawdown in the second. The expectations appear reasonable.

The oil market will start 2017 with a high level of inventories inherited from 2016 thanks to recent increases in production by both OPEC and non-OPEC countries....MORE

Oops, Missed One: Tesla Had Another $241 Million Cash Infusion We Didn't Mention (TSLA)

Following up on ""Panasonic to invest over $256 million in Tesla's U.S. plant for solar cells" (TSLA)", this would increase the cash immediately available to Tesla to around a billion. Still short of our estimate of their need but getting closer.

I'm assuming this had something to do with Renewable Energy Certificates but didn't see an SEC filing from Tesla/SolarCity that would provide more details. We'd also want to know the capitalization rates applied to the underlying residential leases to know if this was a fire sale or not but again, nada.

From Business Wire, Dec. 22:

Sammons Renewable Energy (SRE), a Sammons Enterprises, Inc. company, announced today that it led the equity portion of a $241 million cash equity transaction with SolarCity (SCTY). Franklin Park Investments manages SRE. As part of the deal, SRE is investing in a portfolio of solar projects in 16 states, including 26,000 home residential systems and 19 commercial and industrial solar projects. The financing is non-recourse to SolarCity.

“Solar City represents the caliber of company Sammons Renewable Energy looks to partner with,” said Heather Kreager, Chief Executive Officer of Sammons Enterprises, the parent company of Sammons Renewable Energy. “As Sammons Renewable Energy continues to grow in the renewable energy market, we will pursue partners that have the potential demonstrated by SolarCity in its ten-year history.”

“We are pleased to close this transaction with SolarCity and look forward to additional investments in the North American renewable energy market,” commented Tom Tribone, the Chief Executive Officer of Franklin Park, SRE’s management partner. “Our objective is to partner with strong development companies and to acquire solar, wind and hydroelectric projects either at commencement of construction or project completion.”

Alfa Business Advisers provided tax equity advice to Franklin Park and Orrick, Herrington & Sutcliffe provided legal advice to Franklin Park....

Asness vs. Arnott: Factor Rotation Research

From Newfound Research:

Factor Rotation: Possible, but Worth It?

Summary­­

• With significant research into factor rotation in 2016, we expect to see more factor rotation strategies in the market in 2017.
• Using six popular factors (Value, Size, Reinvestment, Operating Profitability, Momentum and Beta), we explore both switching and rotation based strategies.
• We find switching strategies to be largely unimpressive compared to simple buy-and-hold.
• We find factor rotation to have outperformed a passive multi-factor portfolio by 1.32% per year. However, we believe that after fees (i.e. manager fees and transaction costs), the added performance may not be worth the headaches of multi-year drawdowns relative to the simpler approach.If 2016 was the year of multi-factor products, we expect that 2017 will be the year of factor rotation products.

In many ways, 2016 was a year of heavy factor rotation research.  Rob Arnott (Research Affiliates) and Cliff Asness (AQR) sparred all year on the topic.  To summarize their views:

• The research from Rob and his team at Research Affiliates shows that valuation spreads within factors are important and can provide guidance on potential factor return premiums, if not flash a warning sign about outright factor crashes.For example, Research Affiliates would say that if low volatility stocks are significantly overvalued compared to historical levels (e.g. aggregate price-to-book versus historical average), it may not make sense to hold them.
• Cliff took exception to both the applicability of the research as well as the theory. Largely, his argument hinged on the fact that valuation provides long-term guidance on returns, and therefore says little about high turnover factors.For example, if we know that a small-cap index is trading at a 25 P/E today and our crystal ball tells us that it will be trading at a 15 P/E in five years, that would likely provide us very important information about drag created by valuation contraction.On the other hand, if we know that a momentum index is trading at a 25 P/E today and our crystal ball tells that it will be trading at a 15 P/E in five years, it tells us very little, because it is very unlikely that the portfolio will hold the same stocks a year from today, much less five years.  So the contraction in portfolio P/E may be due to changes in holdings and not a contraction in valuation of those holdings.

So who is right?  Who is wrong?  What is the expected efficacy of factor rotation strategies?  Let’s dive in. 

Our Hypothesis
Evidence-based research requires having a hypothesis before we do the research.  Otherwise, we risk poking around in the dark, finding positive results, and creating a narrative to match those results.
So what is our general hypothesis about factor timing?

Well, if we believe that the factors exist for behavioral reasons (which we largely do), then those same behavioral biases should likely apply to the factors themselves. Therefore we expect that valuation-based timing should be effective for low-turnover factors (e.g. value and size) and momentum-based timing should be effective for all factors.

Well, at least these were our hypotheses when we first started investigating the topic early last year.  At this point, we’ve already done a fair amount of research into the topic.  In fact, we wrote a paper and submitted it to NAAIM for their annual Founders/Wagner Award competition....

...MUCH MORE

"Panasonic to invest over $256 million in Tesla's U.S. plant for solar cells" (TSLA)--UPDATED

UPDATE below.
Original post:
Combined with the expansion of their credit lines the company has now raised 3/4 billion of the estimated $3 billion immediate need and $6-12 billion 5-year need.
From Reuters:

Panasonic Corp (6752.T) will invest more than 30 billion yen ($256 million) in a New York production facility of Elon Musk's Tesla Motors (TSLA.O) to make photovoltaic (PV) cells and modules, deepening a partnership of the two companies.

Japan's Panasonic, which has been retreating from low-margin consumer electronics to focus more on automotive components and other businesses targeting corporate clients, will make the investment in Tesla's factory in Buffalo, New York.

The U.S. electric car maker is making a long-term purchase commitment from Panasonic as part of the deal, besides providing factory buildings and infrastructure....MORE

There are a few mentions of the New York plant in relation to Tesla's financing needs on the blog, here's the most recent, Dec. 21:

Tesla Increases Available Credit Lines After Saying No Fundraising Needed In Q4 (TSLA)

We've done a lot of thinking about Tesla's cash requirements and between the initial production at the Nevada Gigafactory commencing next month, the build-out of that space over the next three years, the New York SolarCity plant, the expected 2017 groundbreaking for a second Gigafactory somewhere in Europe and funding the operating losses at both SolarCity and Tesla, we figure a near term need for $3 billion and an ultimate requirement of $6 to $12 billion over five years....

UPDATE: "Oops, Missed One: Tesla Had Another $241 Million Cash Infusion We Didn't Mention (TSLA)"

The stock seems to like the financing, up $6.45 (+3.02%) at $219.79. It has been a good December for longs, we have no interest:

FinViz

"2016: The year in heists and capers"

From Quartz:

It’s been a year of smash-and-grabs, get-aways, infiltrations, intrusions, master schemes, and mad dashes. The heist economy was alive and well in 2016, and our dedicated caper correspondents have kept tabs on the most ambitious acts of larceny and loose morals in the global economy. To wit, here’s your year in heists and capers:

The Million-Dollar Eel Endeavor
With its vast immigrant population, New York City is home to a stunning variety of cuisines, some of which are legal and others are not. This sometimes leads smugglers to sneak invasive or endangered species past animal-trafficking cops. In this case, a $1 million shipment of frozen BBQ eels arrived in a New Jersey warehouse legally, but three cooks used falsified papers to receive the eels before their rightful owners could pick them up. Working with the police, the rightful owner managed to spring a sting on the crooks when he found several men looking to offload a large volume of eel at cut rates. After being led to the warehouse where his goods were found, police arrested the crooks and seized the eel-vidence.

The Japanese Cash-Machine Junket
It’s a classic of the modern heist genre: Convince ATMs to spit out cash at the exact time your accomplices are in place to collect it. A 2013 version of this heist inspired the original edition of this post. This year, the scene is set in Japan, where thieves used spoofed credit cards to steal more than $13 million from Standard Bank of South Africa in just three hours. A team of one hundred criminals pulled the money out at banks across the country before the banks could be alerted to stop them. Two men were arrested shortly after the heist, but Japanese authorities have yet to reveal further details; reportedly, a Chinese criminal organization is suspected of having taken advantage of Japan’s lax cybersercurity.

The Queens Rooftop Rumble
Tunneling into a bank vault is a classic move. The 2016 twist? Go in through the roof. A group of thieves in New York City found an opportunity to do just that, cutting through the roof of Maspeth Federal Savings Bank over a May weekend to ransack clients’ safe-deposit boxes and snatch free cash. A neighbor of the bank called police to report the suspicious appearance of a black-painted ladder in his backyard and a box on the roof of the bank. According to the New York Times, police declined to investigate, telling the the man that he was the proud owner of a new ladder. The robbery was discovered two days later when the bank re-opened, and the box the neighbor spotted turned out to be one of many empty safe-deposit boxes left on the roof. The thieves are linked to nine other rooftop bank robberies, and are still at large....

...MORE

Some of our 2016 posts on such things:

A Burgler's Guide To The City--How a Criminal Sees the World
ISIS Earns Millions Skimming Forex, Trading Equities
"A gang of idiots somehow managed to steal $80 million of rare artifacts from English museums"
Jackpot: "Why We All Dream of Being Jewel Thieves"
Ummm...Gary Grant, Grace Kelly, French Riviera, directed by Hitchcock?
No?
I'm going with yes. 
"The great global avocado trade flow chart"
Money, Murder and Sadomasochism: A Look At the L.A. Tech Scene
Climateer Line of the Day: "...The Only Risk Was Theft By Lawyers" Edition
Ethereum Found the $53 Million
It's always in the last place you look.  
"Forget malware, crooks are cracking ATMs the old-fashioned way – with explosives"
NYC Bank Burglars Stole $5 Million in Cash, Diamonds Hollywood Style
Fires, Thefts: The Scandals of 740 Park, the World’s Richest Building (Koch, Merkin, Schwarzman,Thain, Mnuchin, Tisch, Lauder et al)
"How to Fake It So No One Notices" (the Ivy League, the Holy Foreskin, the Amazon, the usual)
"...have you seen these seven missing Warhols?"
How to Spot a Hedge Fund Fraudster
Bombast. In my experience they are all bombastic.
And stripper poles.
You would not believe the number of stripper poles that crooks collect.
Author's Book Doesn't Sell, He Sues The Internet
40% of Econ Experiments Can't be Replicated
Crime Headlines From 2025
Ransomware: In Which Izabella Goes All 14th Century Condottieri

And many more. These are just some of the 2016 vintage, and not including Theranos, JustMayo and other finance doings where the real money is to be found.
Collecting these things is sort of a hobby.  

Artificial Intelligence and the Role Of the Literary Critic

First they came for the literary theorists and I did not speak out because--well, you know the drill.* 

From Aeon:

The author is a computational linguist based in Thailand. He is a retired former associate professor of linguistics at Georgetown University, and also formerly a principal scientist at Yahoo Labs. His books include The Imagined Moment (2010) and Computational Modeling of Narrative (2012), and he has also published numerous papers and short stories.

When robots read books
 Artificial intelligence sheds new light on classic texts. Literary theorists who don’t embrace it face obsolescence

Where do witches come from, and what do those places have in common? While browsing a large collection of traditional Danish folktales, the folklorist Timothy Tangherlini and his colleague Peter Broadwell, both at the University of California, Los Angeles, decided to find out. Armed with a geographical index and some 30,000 stories, they developed WitchHunter, an interactive ‘geo-semantic’ map of Denmark that highlights the hotspots for witchcraft.

The system used artificial intelligence (AI) techniques to unearth a trove of surprising insights. For example, they found that evil sorcery often took place close to Catholic monasteries. This made a certain amount of sense, since Catholic sites in Denmark were tarred with diabolical associations after the Protestant Reformation in the 16th century. By plotting the distance and direction of witchcraft relative to the storyteller’s location, WitchHunter also showed that enchantresses tend to be found within the local community, much closer to home than other kinds of threats. ‘Witches and robbers are human threats to the economic stability of the community,’ the researchers write. ‘Yet, while witches threaten from within, robbers are generally situated at a remove from the well-described village, often living in woods, forests, or the heath … it seems that no matter how far one goes, nor where one turns, one is in danger of encountering a witch.’

Such ‘computational folkloristics’ raise a big question: what can algorithms tell us about the stories we love to read? Any proposed answer seems to point to as many uncertainties as it resolves, especially as AI technologies grow in power. Can literature really be sliced up into computable bits of ‘information’, or is there something about the experience of reading that is irreducible? Could AI enhance literary interpretation, or will it alter the field of literary criticism beyond recognition? And could algorithms ever derive meaning from books in the way humans do, or even produce literature themselves?

Computer science isn’t as far removed from the study of literature as you might think. Most contemporary applications of AI consist of sophisticated methods for learning patterns, often through the creation of labels for large, unwieldy data-sets based on structures that emerge from within the data itself. Similarly, not so long ago, examining the form and structure of a work was a central focus of literary scholarship. The ‘structuralist’ strand of literary theory tends to deploy close – sometimes microscopic – readings of a text to see how it functions, almost like a closed system. This is broadly known as a ‘formal’ mode of literary interpretation, in contrast to more historical or contextual ways of reading.

The so-called ‘cultural’ turn in literary studies since the 1970s, with its debt to postmodern understandings of the relationship between power and narrative, has pushed the field away from such systematic, semi-mechanistic ways of analysing texts. AI remains concerned with formal patterns, but can nonetheless illuminate key aspects of narrative, including time, space, characters and plot.

Consider the opening sentence of Gabriel García Márquez’s One Hundred Years of Solitude (1967): ‘Many years later, as he faced the firing squad, Colonel Aureliano Buendía was to remember that distant afternoon when his father took him to discover ice.’ The complex way in which Márquez represents the passage of time is a staple of modern fiction. The time corresponding to ‘Many years later’ includes the fateful time of ‘facing’ the firing squad, which in turn is simultaneous with that final ‘remember’-ing, which is years after ‘that distant afternoon’. In a single sentence, Márquez paints a picture of events in the fleeting present, memories of the past and visions for the future.

According to numerous psychological studies, when we read such stories, we construct timelines. We represent to ourselves whether events are mentioned before, after or simultaneous with each other, and how far apart they are in time. Likewise, AI systems have also been able to learn timelines for a variety of narrative texts in different languages, including news, fables, short stories and clinical narratives.

In most cases, this analysis involves what’s known as ‘supervised’ machine learning, in which algorithms train themselves from collections of texts that a human has laboriously labelled. Timeframes in narratives can be represented using a widely used annotation standard called TimeML (which I helped to develop). Once a collection (or ‘corpus’) of texts is annotated and fed into an AI program, the system can learn rules that let it accurately identify the timeline in other new texts, including the passage from Márquez. TimeML can also measure the tempo or pace of the narrative, by analysing the relationship between events in the text and the time intervals between them.

AI annotation schemes are versatile and expressive, but they’re not foolproof
The presence of narrative ‘zigzag’ movements in fiction is one of the intriguing insights to emerge from this kind of analysis. It’s evident in this passage from Marcel Proust’s posthumously published novel Jean Santeuil (1952), the precursor to his magnum opus In Search of Lost Time (1913-27):

Sometimes passing in front of the hotel he remembered the rainy days when he used to bring his nursemaid that far, on a pilgrimage. But he remembered them without the melancholy that he then thought he would surely some day savour on feeling that he no longer loved her.

The narrative here oscillates between two poles, as the French structuralist critic Gérard Genette observed in Narrative Discourse (1983): the ‘now’ of the recurring events of remembering while passing in front of the hotel, and the ‘once’ or ‘then’ of the thoughts remembered, involving those rainy days with his nursemaid.
Even though AI annotation schemes are versatile and expressive, they’re not foolproof. Longer, book-length texts are prohibitively expensive to annotate, so the power of the algorithms is restricted by the quantity of data available for training them. Even if this tagging were more economical, machine-learning systems tend to fare better on simpler narratives and on relating events that are mentioned closer together in the text. The algorithms can be foxed by scene-setting descriptive prose, as in this sentence from Honoré de Balzac’s novella Sarrasine (1831), in which the four states being described should (arguably) overlap with each other:

The trees, being partly covered with snow, were outlined indistinctly against the greyish background formed by a cloudy sky, barely whitened by the moon.

AI criticism is also limited by the accuracy of human labellers, who must carry out a close reading of the ‘training’ texts before the AI can kick in. Experiments show that readers tend to take longer to process events that are distant in time or separated by a time shift (such as ‘a day later’). Such processing creates room for error, although distributing standard annotation guidelines to users can reduce it. People also have a hard time imagining temporally complex situations, such as the mind-bending ones described in Alan Lightman’s novel Einstein’s Dreams (1992):

For in this world, time has three dimensions, like space. … Each future moves in a different direction of time. Each future is real. At every point of decision, whether to visit a woman in Fribourg or to buy a new coat, the world splits into three worlds, each with the same people, but different fates for those people. In time, there are an infinity of worlds.

Spotting temporal patterns might be fun and informative, but isn’t literature more than the sum of the information lurking in its patterns? Of course, there might be phenomenological aspects of storytelling that remain ineffable, including the totality of the work itself. Even so, literary interpretation is often an inferential process. It requires sifting through and comparing chunks of information about literature’s form and context – from the text itself, from its historical and cultural background, from authorial biographies, critiques and social-media reactions, and from the reader’s prior experience. All of this is data, and eminently minable....MUCH MORE

*First they came for the journalists and I did not speak out-
Because I was not a journalist.

Then they came for the ad agency creatives and I did not speak out-
Because I was not an ad agency creative. (see below)

Then they came for the financial analysts and I
said 'hang on one effin minute'.

Possibly related:
A Novel Co-Authored By An Artificial Intelligence Program Longlisted For Japanese SciFi Literary Prize
Artificial Intelligence Algos To Read, Understand and Comment On News Stories
This seems efficient.
Combine the story-writing programs* with the commenting programs and just cut the humans out completely.

Bessemer Venture Partners Anti-Portfolio

For the last eight or so years we've visited one of the best finance pages on the internet.
From Bessemer Venture Partners:

HONORING THOSE WE MISSED

The Anti-Portfolio

Bessemer Venture Partners is perhaps the nation's oldest venture capital firm, tracing our roots back to the Carnegie Steel empire. This long and storied history has afforded our firm an unparalleled number of opportunities to completely screw up.

Over the course of our history, we did invest in a wig company, a french-fry company, and the Lahaina, Ka'anapali & Pacific Railroad. However, we chose to decline these investments, each of which we had the opportunity to invest in, and each of which later blossomed into a tremendously successful company.

Our reasons for passing on these investments varied. In some cases, we were making a conscious act of generosity to another, younger venture firm, down on their luck, who we felt could really use a billion dollars in gains. In other cases, our partners had already run out of spaces on the year's Schedule D and feared that another entry would require them to attach a separate sheet.

Whatever the reason, we would like to honor these companies -- our "anti-portfolio" -- whose phenomenal success inspires us in our ongoing endeavors to build growing businesses. Or, to put it another way: if we had invested in any of these companies, we might not still be working.

	(acquired by Hewlett Packard) BVP's Felda Hardymon was offered a position in Apollo Computer and passed.  Within a year it was trading publically for 17x the price that he was offered.  Apollo was subsequently acquired by HP for an even greater value.
	BVP had the opportunity to invest in pre-IPO secondary stock in Apple at a $60M valuation. BVP's Neill Brownstein called it "outrageously expensive."
	In 1994, Gil Schwed pitched his idea to BVP's David Cowan, who said that Gil would never get distribution in the US. The next year, Check Point got a huge Sun OEM deal and sold $25M of firewall software.
	(acquired by Unilever) Shortly after the first viral video* Ethan Kurzweil passed on investing in the company. He figured Gillette was bound to launch a competing subscription that would extinguish Dollar Shave’s momentum.  He was half right:  Gilette did launch a subscription, although it mostly served to drive awareness of Dollar Shave Club.  A few years later Unilever bought Dollar Shave club for $1 billion.
	"Stamps? Coins? Comic books? You've GOT to be kidding," thought Cowan. "No-brainer pass."
	Jeremy Levine spent a weekend at a corporate retreat in the summer of 2004 dodging persistent Harvard undergrad Eduardo Saverin's rabid pitch. Finally, cornered in a lunch line, Jeremy delivered some sage advice "Kid, haven't you heard of Friendster? Move on. It's over!"
	Incredibly, BVP passed on Federal Express seven times....

...MUCH MORE

*Here's the Dollar Shave Club ad:

Boxing Day Update: "Family Receives 38-Piece AstraZeneca Assorted Pill Sampler"

From AFNS:

ALPHARETTA, GA—Gathering around the kitchen table to pick out their favorites, all four members of the Johnson household eagerly dug into a 38-piece AstraZeneca pill sampler that they received as a holiday gift, sources confirmed Friday. “I like the blue-and-red ones a lot, but I’ll pretty much eat any of them except for the yellows; I always leave those for Dad,” said 12-year-old Evan Johnson, who added that out of the box’s assorted painkillers, decongestants, estrogen supplements, and antipsychotic medications, he enjoys the ones with a codeine-based gel filling the best. “It’s also kind of fun to grab one without knowing what’s inside and try to guess what you’ve taken...MORE

The Geographic Development Of American Suburbia

Although varying in the details (more emphasis on railroad lines, etc.), the 1850-1930 experience of the English suburbs and the French banlieues developed similarly to the American version.
Then the trajectories really, really diverged.

From McMansion Hell, Dec. 18:

A Pictorial History of Suburbia

Hello friends! Sorry for all the delays this week- exams were brutal and so was the stomach flu. Now that I am feeling better, I want to present the last Sunday post of the year - the remaining weeks will be devoted to the McMansionHell 2016 cluster-you-know-what retrospective, which should be very exciting. By the New Year, McMansion Hell will have a new logo, and a fresh dossier of topics, so stay tuned!

On to business!

Introduction
We are all familiar with exurbia - the sleeper cities in which our beloved McMansions loom over the non-existent sidewalks. However, this way of living is very recent in the grand scheme of history, even in America whose history is very short.

Dallas, TX and Suburbs by Andreas Praefcke (CC-BY-SA 3.0)

The suburb is as old as the English language itself - the word dates back to Chaucer - but the exurb, and other contemporary ways of ordering our lives is very recent, its origins begin around 1945. By 1970, the exurb had reached its final from: the SLUG (Spread-out, Low-density, Unguided Growth.)

But to know the present, we must first, of course, understand the past.

A Visual History of Neighborhood Shapes (1750-1940)
Before there were suburban areas, there were, of course, urban areas. Until around the 1850s, most people in America either lived in the urban cores of cities or in rural towns. The rural towns remained pretty much unchanged until around 1940 when many of them were absorbed into the sprawling cities.

The Early Urban Core (1750-1850)
From around 1750-1850, the urban core was pretty simple. A city would usually form around some sort of natural resource, usually a body of water, and was usually planned in a grid formation. The houses were narrow, almost always attached or semi-detached, and had no front yard. (1)

Chicago in 1836. (Open in new tab for full res)

The Urban Expansion (c.1830-1900)
In the 1850s, the cities began to expand, thanks to help of inventions like the horse-drawn streetcar, ferries, and cable cars. These expansions adopted the attached house format of the inner city, but detached housing also existed, especially in the Midwest. (2)

Allentown, PA in 1855

The Railroad Suburbs (1850-1930)
In the 1860s, the first true suburbs were born, thanks to the steam railroad. These neighborhoods were a bit more sprawled out: detached houses became the norm, along with small front yards and detached garages. Houses tended to congregate around rail stops, with the fanciest houses being the closest to the railroad.

Louisville, KY in 1873. Note railway suburbs in the top left corner.

The Streetcar Suburbs (1890-1930)...

...MUCH MORE 

Predictions 2017

Via Stock Cats' twitter feed:

2017 predictions pic.twitter.com/wSpSC9YnYf

— StockCats (@StockCats) December 23, 2016

"Malls Are Dead. Long Live Online Shopping"

First up, the headline story from Bankers Anonymous Dec. 25:

At Christmas 2016, the twenty-year battle is over. One side won, one side lost. I mean the twenty-year war between bricks-and-mortar stores and online venders.

This one-sided thrashing has been worse than that suffered by those perennial losers, the Washington Generals. (Note: I’m referring to basketball team that lost more than 16,000 games to the Harlem Globetrotters, not casting aspersions on all of those Trump cabinet nominees.)

I remember the exact moment I realized this war between online stores and bricks-and-mortar stores was on like Donkey Kong.

In December 1996, a pioneering technology journalist from The Economist announced that he had attempted to purchase all of his Christmas gifts online. 

Whoa! That seemed crazy and cool. Reading that article in my little cramped studio apartment in Manhattan, I was fascinated by the idea that with a few clicks, Christmas shopping could come to me. No paper catalogues, no phone calls, just clicks. I hate shopping, and this experiment in 1996 seemed awesome, and very science fiction-y.

Of course, the joke is that the journalist at The Economist couldn’t do it. He was able to buy one Christmas gift only. Although many big companies had built websites by 1996, they were essentially non-interactive company brochures, with undeveloped and insecure methods of payment.

Much changed in 20 years. A consumer survey by a subsidiary of accounting firm Deloitte found that shoppers will spend equal amounts online as in-store in the 2016 holiday season, a new milestone for web sales.

That continues the upward trend begun two decades ago. And nobody thinks 50 percent will be the stopping point. The next retail frontier is how much shopping will be done on mobile devices, which the same Deloitte survey already pegs at 10 percent of all holiday sales in 2016, and growing.

I wish there was a way to efficiently invest in the idea that retail stores in malls will continue to get crushed by online stores. I mean, I’m sure there’s some ETF for this, but you shouldn’t take investment advice from a blogger, so I’m not going to look it up for you.

Just as I remember the launch of the 20 year war during Christmas 1996, I also remember the exact moment I decided brick-and-mortar stores were officially dead to me. In fact, it happened this past Summer....MUCH MORE

And from Pew Research Dec. 19:

Online Shopping and E-Commerce
New technologies are impacting a wide range of Americans’ commercial behaviors, from the way they evaluate products and services to the way they pay for the things they buy

Americans are incorporating a wide range of digital tools and platforms into their purchasing decisions and buying habits, according to a Pew Research Center survey of U.S. adults. The survey finds that roughly eight-in-ten Americans are now online shoppers: 79% have made an online purchase of any type, while 51% have bought something using a cellphone and 15% have made purchases by following a link from social media sites. When the Center first asked about online shopping in a June 2000 survey, just 22% of Americans had made a purchase online. In other words, today nearly as many Americans have made purchases directly through social media platforms as had engaged in any type of online purchasing behavior 16 years ago.

But even as a sizeable majority of Americans have joined the world of e-commerce, many still appreciate the benefits of brick-and-mortar stores. Overall, 64% of Americans indicate that, all things being equal, they prefer buying from physical stores to buying online. Of course, all things are often not equal – and a substantial share of the public says that price is often a far more important consideration than whether their purchases happen online or in physical stores. Fully 65% of Americans indicate that when they need to make purchases they typically compare the price they can get in stores with the price they can get online and choose whichever option is cheapest. Roughly one-in-five (21%) say they would buy from stores without checking prices online, while 14% would typically buy online without checking prices at physical locations first.

Although cost is often key, today’s consumers come to their purchasing decisions with a broad range of expectations on a number of different fronts. When buying something for the first time, more than eight-in-ten Americans say it is important to be able to compare prices from different sellers (86%), to be able to ask questions about what they are buying (84%), or to buy from sellers they are familiar with (84%). In addition, more than seven-in-ten think it is important to be able to try the product out in person (78%), to get advice from people they know (77%), or to be able to read reviews posted online by others who have purchased the item (74%). And nearly half of Americans (45%) have used cellphones while inside a physical store to look up online reviews of products they were interested in, or to try and find better prices online.

The survey also illustrates the extent to which Americans are turning toward the collective wisdom of online reviews and ratings when making purchasing decisions. Roughly eight-in-ten Americans (82%) say they consult online ratings and reviews when buying something for the first time. In fact, 40% of Americans (and roughly half of those under the age of 50) indicate that they nearly always turn to online reviews when buying something new. Moreover, nearly half of Americans feel that customer reviews help “a lot” to make consumers feel confident about their purchases (46%) and to make companies be accountable to their customers (45%).

But even as the public relies heavily on online reviews when making purchases, many Americans express concerns over whether or not these reviews can be trusted. Roughly half of those who read online reviews (51%) say that they generally paint an accurate picture of the products or businesses in question, but a similar share (48%) say it’s often hard to tell if online reviews are truthful and unbiased.

Finally, this survey documents a pronounced shift in how Americans engage with one of the oldest elements of the modern economy: physical currency. Today nearly one-quarter (24%) of Americans indicate that none of the purchases they make in a typical week involve cash. And an even larger share – 39% – indicates that they don’t really worry about having cash on hand, since there are so many other ways of paying for things these days. Nonwhites, low-income Americans and those 50 and older are especially likely to rely on cash as a payment method....MUCH MORE