January 2018

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Preview YouTube video Ducati on the fly oil change

Ducati on the fly oil change
So, I was riding fast, circa 180kph, when I entered a dip in the road which bottomed out my suspension. Unknown to me, there is a sump, which as the bike bottomed out, sheared this off. All the oil in the bike pissed out over my rear tyre. This gave me a ‘moment’ as the bike went a bit sideways. Not realising that this was the case, I continued to ride until the oil pressure light came on. I stopped immediately, but it may be too late, the engine is damaged.

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There is and has been, plenty of inflation. This is the result of Central Bank ‘easing’ throughout the world and why Joe Average feels and is, far worse off.

We have had massive housing inflation, stock market and bond market inflation, or, asset price inflation around the world.

This chart depicts ‘consumer price’ inflation which includes your weekly grocery shop etc.

The word is that ‘inflation’ is set to rise. Commodities are setting up for the pre-2005 run-up in prices that saw oil hit $120+/barrel.

Usually that means that the Central Bankers will start to tighten interest rates, or in other words raise them. The only problem with that is that consumer credit is high and the quality dropping. Certainly here in NZ, new mortgages, say in the last 5yrs, after a massive increase in house prices cannot sustain any sort of interest rise without triggering significant defaults.

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Took a ride to Raglan, NZ’s surfers paradise. I’ve never actually been there before and the road is ultra-twisty. We made pretty good time even though the road [on the way down] was pretty bumpy, much better on the way home.




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Just picked up a 996. Today was the first day that I could take it for a spin. Lovely bike to ride. Plenty of torque and grunt in the midrange, didn’t really test the top-end too much, still on the road after-all.

Very impressive in the corners, feels very stable and confidence inspiring.

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The revolution was not, in fact, televised.  A simple press release filled the bill instead. This morning, BlackRock released its ETF Pulse Survey, a look at the pace of exchange traded fund adaptation across different demographics.  The survey of individual investors found that only 27% of baby boomers (aged 52 to 70) own ETFs, compared to 42% of millennials (21 to 35) and 37% of “silvers” (aged 71 or older). Martin Small, head of BlackRock’s iShares unit in the U.S., surmised that boomers: “May still be holding onto a stock-picking mentality. They may not realize that ETFs are as easy to trade as stocks and available in virtually every market segment imaginable. As a result, many pre-retirees and investors in their early years of retirement may be overlooking the ETF revolution.”
Much as crypto-currencies run the gamut from relatively established first movers like bitcoin to ICO’s such as “Lehman Brothers Coin” (Almost Daily Grant’sJan. 19), so does the exchange-traded fund realm range from the simple (such as the SPDR S&P 500 ETF Trust, or SPY on NYSE Arca, which today crossed the $300 billion in assets under management for the first time), to the exotic.
For a demonstration of the latter, we turn to the BMO Rex Microsectors FANG+ Index 3x Levered ETN (FNGU on NYSE Arca) and its evil twin, the FANG+ Inverse Leveraged ETN (FNGD on same), which debuted yesterday.   Bloomberg Intelligence harkened the vehicle’s debut with the apt headline: “Leveraged FANG ETNs Aim to Bring Volatility to Bored Traders.”  The ETN will charge a 95 basis point expense ratio (10 times the SPY), while the underlying FANG+ Index comprises equal weighted holdings of Facebook, Inc., Apple, Inc., Amazon.com, Inc., Netflix, Inc., and Alphabet, Inc., (nee Google), as well as Alibaba Group, Baidu, Inc., Nvidia Corporation, Tesla, Inc., and Twitter, Inc,.
Eagle-eyed readers will spot that those leveraged securities are classified as ETNs, or exchange traded notes, rather than the conventional ETFs.  The Wall Street Journalexplained the difference on Feb. 5, 2017:
Both ETFs and ETNs track the price of things like baskets of stocks, bonds or commodities, but they do so differently. ETFs own a portion of the assets they track – an S&P 500 ETF, for instance, owns stocks that are included in the index. ETNs don’t own a portfolio of assets. They are simply debt issued by banks that promise a return to the investor linked to the performance they track.
Indeed, the registration statement filed with the SEC states that: “The notes are unsecured [and] . . . do not guarantee any return of principal.”   As for the leverage factor, the document carries the following disclaimer: “The notes are riskier than securities that have intermediate- or long-term investment objectives, and may not be suitable for investors who plan to hold them for a period other than one day or who have a ‘buy and hold’ strategy . . . Investors should actively and continuously monitor their investments in the notes, even intra-day.”
The May 19, 2017 analysis in Grant’s (“Loaded for bear”) took a different tack in describing these products which evidently require a day trader’s attention (and attention span): “Take every known principal of long-term investment success, negate those precepts and multiply the negative by leverage. That would be one aspect of the 4X, 3X or 2X story.”  Why?   Biff Robillard, co-founder of Bannerstone Capital Management LLC, explained the problem:  To make money in leveraged ETF’s, one must correctly predict not only the direction of prices, but of their realized volatility as well.
Not the implied volatility, and not the VIX per se, [but] the actual volatility that the underlying entity driving valuations will experience going forward. You have to have an opinion about that. High volatility reduces, even reverses, returns on leveraged ETFs.
The piece then goes on to demonstrate a hypothetical example:
Say that you own $100 of a thrice-leveraged ETF. On day one, the underlying index moves up by 5% – your fund as gains three times $5; it’s worth $115. Next day, the index falls by 5%; oops, your fund is now worth $97.75. Repeat across 10 days – alternating up 5% and down 5% – and you would finish with $89.23, down by 10.8%. Over the same course of choppy trading days, an unlevered fund would have lost only 1.2%.
So too, does the leverage mandate pose the potential to exacerbate market volatility, should this period of historic serenity be interrupted:
In a conventional margin account, leverage ratios fall as the value of portfolio assets rise. Not so here. An ultra ETF keeps its leverage constant by boosting its indebtedness – drawing on its swap arrangements – as the value of its assets appreciates. To bulk up in a rising market and sell down in a falling one is a technique that recalls the misadventures of portfolio insurance [an aggravating factor in the 1987 stock market crash].
For its part, BlackRock has steered clear of leveraged ETFs. CEO Laurence Fink told the audience at a Deutsche Bank-hosted investor conference in 2014 that: “We’d never do one. They have a structural problem that could blow up the whole industry one day.”  That prompted a rejoinder from Trevor Hewes, spokesman for ProShares, which offers many such products: “Leveraged ETFs are well regulated, transparent products and there is no credible evidence that they have any harmful effect on the markets or our industry.”
For our part, we wonder about the soundness of ETFs as a whole, not just the plainly perilous leveraged variety.  Recall the increasingly distant (in terms of time elapsed and market environment) events of Aug. 24, 2015, a steep sell-off that left the S&P 500 lower by as much as 5.2% intraday and 3.9% by the close.  In that session, even straightforward ETFs were severely dislodged, with the SPY falling by nearly 8% intraday.  The S&P 500 equal-weighted index dropped by as much as 4.6%, while the Guggenheim S&P 500 equal-weight ETF sank by as much as 43%, before finishing in the red by just 4%.

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Predicting cryptocurrency prices is a fool’s game, yet this fool is about to try. The drivers of a single cryptocurrency’s value are currently too varied and vague to make assessments based on any one point. News is trending up on Bitcoin? Maybe there’s a hack or an API failure that is driving it down at the same time. Ethereum looking sluggish? Who knows: Maybe someone will build a new smarter DAO tomorrow that will draw in the big spenders.

So how do you invest? Or, more correctly, on which currency should you bet?

The key to understanding what to buy or sell and when to hold is to use the tools associated with assessing the value of open-source projects. This has been said again and again, but to understand the current crypto boom you have to go back to the quiet rise of Linux.

Linux appeared on most radars during the dot-com bubble. At that time, if you wanted to set up a web server, you had to physically ship a Windows server or Sun Sparc Station to a server farm where it would do the hard work of delivering Pets.com HTML. At the same time, Linux, like a freight train running on a parallel path to Microsoft and Sun, would consistently allow developers to build one-off projects very quickly and easily using an OS and toolset that were improving daily. In comparison, then, the massive hardware and software expenditures associated with the status quo solution providers were deeply inefficient, and very quickly all of the tech giants that made their money on software now made their money on services or, like Sun, folded.

From the acorn of Linux an open-source forest bloomed. But there was one clear problem: You couldn’t make money from open source. You could consult and you could sell products that used open-source components, but early builders built primarily for the betterment of humanity and not the betterment of their bank accounts.

Cryptocurrencies have followed the Linux model almost exactly, but cryptocurrencies have cash value. Therefore, when you’re working on a crypto project you’re not doing it for the common good or for the joy of writing free software. You’re writing it with the expectation of a big payout. This, therefore, clouds the value judgements of many programmers. The same folks that brought you Python, PHP, Django and Node.js are back… and now they’re programming money.

Check the codebase

This year will be the year of great reckoning in the token sale and cryptocurrency space. While many companies have been able to get away with poor or unusable codebases, I doubt developers will let future companies get away with so much smoke and mirrors. It’s safe to say we can expect posts like this one detailing Storj’s anemic codebase to become the norm and, more importantly, that these commentaries will sink many so-called ICOs. Though massive, the money trough that is flowing from ICO to ICO is finite and at some point there will be greater scrutiny paid to incomplete work.

What does this mean? It means to understand cryptocurrency you have to treat it like a startup. Does it have a good team? Does it have a good product? Does the product work? Would someone want to use it? It’s far too early to assess the value of cryptocurrency as a whole, but if we assume that tokens or coins will become the way computers pay each other in the future, this lets us hand wave away a lot of doubt. After all, not many people knew in 2000 that Apache was going to beat nearly every other web server in a crowded market or that Ubuntu instances would be so common that you’d spin them up and destroy them in an instant.

The key to understanding cryptocurrency pricing is to ignore the froth, hype and FUD and instead focus on true utility. Do you think that some day your phone will pay another phone for, say, an in-game perk? Do you expect the credit card system to fold in the face of an Internet of Value? Do you expect that one day you’ll move through life splashing out small bits of value in order to make yourself more comfortable? Then by all means, buy and hold or speculate on things that you think will make your life better. If you don’t expect the Internet of Value to improve your life the way the TCP/IP internet did (or you do not understand enough to hold an opinion), then you’re probably not cut out for this. NASDAQ is always open, at least during banker’s hours.

Still will us? Good, here are my predictions.

The rundown

Here is my assessment of what you should look at when considering an “investment” in cryptocurrencies. There are a number of caveats we must address before we begin:

  • Crypto is not a monetary investment in a real currency, but an investment in a pie-in-the-sky technofuture. That’s right: When you buy crypto you’re basically assuming that we’ll all be on the deck of the Starship Enterprise exchanging them like Galactic Credits one day. This is the only inevitable future for crypto bulls. While you can force crypto into various economic models and hope for the best, the entire platform is techno-utopianist and assumes all sorts of exciting and unlikely things will come to pass in the next few years. If you have spare cash lying around and you like Star Wars, then you’re golden. If you bought bitcoin on a credit card because your cousin told you to, then you’re probably going to have a bad time.
  • Don’t trust anyone. There is no guarantee and, in addition to offering the disclaimer that this is not investment advice and that this is in no way an endorsement of any particular cryptocurrency or even the concept in general, we must understand that everything I write here could be wrong. In fact, everything ever written about crypto could be wrong, and anyone who is trying to sell you a token with exciting upside is almost certainly wrong. In short, everyone is wrong and everyone is out to get you, so be very, very careful.
  • You might as well hold. If you bought when BTC was $18,000 you’d best just hold on. Right now you’re in Pascal’s Wager territory. Yes, maybe you’re angry at crypto for screwing you, but maybe you were just stupid and you got in too high and now you might as well keep believing because nothing is certain, or you can admit that you were a bit overeager and now you’re being punished for it but that there is some sort of bitcoin god out there watching over you. Ultimately you need to take a deep breath, agree that all of this is pretty freaking weird, and hold on.

Now on with the assessments.

Bitcoin – Expect a rise over the next year that will surpass the current low. Also expect bumps as the SEC and other federal agencies around the world begin regulating the buying and selling of cryptocurrencies in very real ways. Now that banks are in on the joke they’re going to want to reduce risk. Therefore, the bitcoin will become digital gold, a staid, boring and volatility proof safe haven for speculators. Although all but unusable as a real currency, it’s good enough for what we need it to do and we also can expect quantum computing hardware to change the face of the oldest and most familiar cryptocurrency.

Ethereum – Ethereum could sustain another few thousand dollars on its price as long as Vitalik Buterin, the creator, doesn’t throw too much cold water on it. Like a remorseful Victor Frankenstein, Buterin tends to make amazing things and then denigrate them online, a sort of self-flagellation that is actually quite useful in a space full of froth and outright lies. Ethereum is the closest we’ve come to a useful cryptocurrency, but it is still the Raspberry Pi of distributed computing — it’s a useful and clever hack that makes it easy to experiment but no one has quite replaced the old systems with new distributed data stores or applications. In short, it’s a really exciting technology, but nobody knows what to do with it.

Where will the price go? It will hover around $1,000 and possibly go as high as $1,500 this year, but this is a principled tech project and not a store of value.

Altcoins – One of the signs of a bubble is when average people make statements like “I couldn’t afford a Bitcoin so I bought a Litecoin.” This is exactly what I’ve heard multiple times from multiple people and it’s akin to saying “I couldn’t buy hamburger so I bought a pound of sawdust instead. I think the kids will eat it, right?” Play at your own risk. Altcoins are a very useful low-risk play for many, and if you create an algorithm — say to sell when the asset hits a certain level — then you could make a nice profit. Further, most altcoins will not disappear overnight. I would honestly recommend playing with Ethereum instead of altcoins, but if you’re dead set on it, then by all means, enjoy.

Tokens – This is where cryptocurrency gets interesting. Tokens require research, education and a deep understanding of technology to truly assess. Many of the tokens I’ve seen are true crapshoots and are used primarily as pump and dump vehicles. I won’t name names, but the rule of thumb is that if you’re buying a token on an open market then you’ve probably already missed out. The value of the token sale as of January 2018 is to allow crypto whales to turn a few cent per token investment into a 100X return. While many founders talk about the magic of their product and the power of their team, token sales are quite simply vehicles to turn 4 cents into 20 cents into a dollar. Multiply that by millions of tokens and you see the draw.

The answer is simple: find a few projects you like and lurk in their message boards. Assess if the team is competent and figure out how to get in very, very early. Also expect your money to disappear into a rat hole in a few months or years. There are no sure things, and tokens are far too bleeding-edge a technology to assess sanely.

You are reading this post because you are looking to maintain confirmation bias in a confusing space. That’s fine. I’ve spoken to enough crypto-heads to know that nobody knows anything right now and that collusion and dirty dealings are the rule of the day. Therefore, it’s up to folks like us to slowly buy surely begin to understand just what’s going on and, perhaps, profit from it. At the very least we’ll all get a new Linux of Value when we’re all done.

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Donald Trump poses a huge dilemma for commentators: to ignore his daily outrages is to normalize his behavior, but to constantly write about them is to stop learning. Like others, I struggle to get this balance right, which is why I pause today to point out some incredible technological changes happening while Trump has kept us focused on him — changes that will pose as big an adaptation challenge to American workers as transitioning from farms to factories once did.

Two and half years ago I was researching a book that included a section on IBM’s cognitive computer, “Watson,” which had perfected the use of artificial intelligence enough to defeat the two all-time “Jeopardy!” champions. After my IBM hosts had shown me Watson at its Yorktown Heights, N.Y., lab, they took me through a room where a small group of IBM scientists were experimenting with something futuristic called “quantum computing.” They left me thinking this was Star Wars stuff — a galaxy and many years far away.

Last week I visited the same lab, where my hosts showed me the world’s first quantum computer that can handle 50 quantum bits, or qubits, which it unveiled in November. They still may need a decade to make this computer powerful enough and reliable enough for groundbreaking industrial applications, but clearly quantum computing has gone from science fiction to nonfiction faster than most anyone expected.

Who cares? Well, if you think it’s scary what we can now do with artificial intelligence produced by classical binary digital electronic computers built with transistors — like make cars that can drive themselves and software that can write news stories or produce humanlike speech — remember this: These “old” computers still don’t have enough memory or processing power to solve what IBM calls “historically intractable problems.” Quantum computers, paired with classical computers via the cloud, have the potential to do that in minutes or seconds.

For instance, “while today’s supercomputers can simulate … simple molecules,” notes MIT Technology Review, “they quickly become overwhelmed.” So chemical modelers — who attempt to come up with new compounds for things like better batteries and lifesaving drugs — “are forced to approximate how an unknown molecule might behave, then test it in the real world to see if it works as expected. The promise of quantum computing is to vastly simplify that process by exactly predicting the structure of a new molecule, and how it will interact with other compounds.”

Quantum computers process information, using the capabilities of quantum physics, differently from traditional computers. “Whereas normal computers store information as either a 1 or a 0, quantum computers exploit two phenomena — entanglement and superposition — to process information,” explains MIT Technology Review. The result is computers that may one day “operate 100,000 times faster than they do today,” adds Wired magazine.

Talia Gershon, an IBM researcher, posted a fun video explaining the power of quantum computers to optimize and model problems with an exponential number of variables. She displayed a picture of a table at her wedding set for 10 guests, and posed this question: How many different ways can you seat 10 people? It turns out, she explained, there are “3.6 million ways to arrange 10 people for dinner.”

Classical computers don’t solve “big versions of this problem very well at all,” she said, like trying to crack sophisticated encrypted codes, where you need to try a massive number of variables, or modeling molecules where you need to account for an exponential number of interactions. Quantum computers, with their exponential processing power, will be able to crack most encryption without breaking a sweat.

It’s just another reason China, the N.S.A., IBM, Intel, Microsoft and Google are now all racing — full of sweat — to build usable quantum systems.

“If I try to map a caffeine molecule problem on a normal computer, that computer would have to be one-tenth the volume of this planet in size,” said Arvind Krishna, head of research at IBM. “A quantum computer just three or four times the size of those we’ve built today should be able to solve that problem.”

And then there are all those problems we never even imagined we could model and solve. Universities and companies are already accessing three IBM quantum systems (ranging from 5 to 16 qubits) that are online and open source at ibm.com/IBMQ, and they’ve already run two million quantum programs to prove out, and write papers on, theories that we never had the processing power before to prove.

But, again, look at where we are today thanks to artificial intelligence from digital computers — and the amount of middle-skill and even high-skill work they’re supplanting — and then factor in how all of this could be supercharged in a decade by quantum computing.

As education-to-work expert Heather McGowan (www.futureislearning.com) points out: “In October 2016, Budweiser transported a truckload of beer 120 miles with an empty driver’s seat. … In December 2016, Amazon announced plans for the Amazon Go automated grocery store, in which a combination of computer vision and deep-learning technologies track items and only charges customers when they remove the items from the store. In February 2017, Bank of America began testing three ‘employee-less’ branch locations that offer full-service banking automatically, with access to a human, when necessary, via video teleconference.”

This will be a challenge for developed countries, but even more so for countries like Egypt, Pakistan, Iran, Syria, Saudi Arabia, China and India — where huge numbers of youths are already unemployed because they lack the education for even this middle-skill work THAT’S now being automated.

It’s why IBM’s C.E.O., Ginni Rometty, remarked to me in an interview: “Every job will require some technology, and therefore we’ll need to revamp education. The K-12 curriculum is obvious, but it’s the adult retraining — lifelong learning systems — that will be even more important.”

Artificial intelligence “is the opportunity of our time, and skills are the issue of our time. Some jobs will be displaced, but 100 percent of jobs will be augmented by A.I.,” added Rometty. Technology companies “are inventing these technologies, so we have the responsibility to help people adapt to it — and I don’t mean just giving them tablets or P.C.s, but lifelong learning systems.”

To back that up, said Rometty, IBM designed Pathways in Technology (P-Tech) schools, partnering with close to 100 public high schools and community colleges to create a six-year program that serves large numbers of low-income students. P-Tech schools offer calculus and physics alongside workplace skills — problem solving, writing and job interviewing. These skills are reinforced through mentorships and internships with IBM and more than 300 other companies. Kids graduate in six years or less with both a high school diploma and an associate junior college degree.

“The graduation rates are four times the average, and those getting jobs are at two times the median salary,” said Rometty, “and many are going on to four-year colleges.”

Each time work gets outsourced or tasks get handed off to a machine, “we must reach up and learn a new skill or in some ways expand our capabilities as humans in order to fully realize our collaborative potential,” McGowan said.

Therefore, education needs to shift “from education as a content transfer to learning as a continuous process where the focused outcome is the ability to learn and adapt with agency as opposed to the transactional action of acquiring a set skill,” said McGowan. “Instructors/teachers move from guiding and accessing that transfer process to providing social and emotional support to the individual as they move into the role of driving their own continuous learning.”

Anyway, I didn’t mean to distract from the “Trump Reality Show,” but I just thought I’d mention that Star Wars technology is coming not only to a theater near you, but to a job near you. We need to be discussing and adapting to its implications as much as we do Trump’s tweets.

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