Friday, October 07, 2016

A Recent Uptrend In Unemployment Is Signaling The Start Of Another Recession

This is not a good sign...

We may have one more year before we begin to feel the effects of a top in the labor market, but this shift in trend has typically marked the beginning of a recession. It may not be a deep recession like in 2008, but nonetheless a slowdown. Part of me really wants to recommend staying out of US stocks... but there is no where else to invest. With such a massive book that needs to be filled, central banks around the world don't seem to care about traditional fundamentals, and so they keep buying US assets denominated in a strong dollar.

That said, I think Gold may be a good investment starting in November, according to long term cycles.

Sunday, September 25, 2016

S&P 500 Could Likely Break Out Of This Sideways Range As First Proposed In August 2015

Remember this chart?

First, I would like to bring some attention to this earlier post. Where I specifically called for a drop in equities a few weeks before the major selloffs in August/September of 2015. More importantly, I also said prices wouldn't stay down there. I did turn out to be right about the sideways movement we've seen since then, but wrong about why. Because as the Fed raised the funds rate one time last December by 25 basis points (causing the early 2016 selloff), central banks around the world were doubling down on their stimulus programs -- much to the benefit of US markets.

20% of the SNB's foreign currency reserves are in equities 
up from 17% last year and 10% in 2010

Last year in August I proposed that the SP 500 could move sideways throughout 2015 into 2016, and depending on what the Fed would do, could move lower towards the end of this 2016 year. So far, the Fed hasn't given much of an indication that another rate hike is nearing, even as T-note yields have risen. All the while, central banks around the world continue (most recently the BoE) to buy large amounts of corporate debt and other foreign securities (including US equities) under their respective asset purchase and investment programs; US stock buybacks remain a common practice and haven't been slowing down; Long term bond prices have dipped from their highs, but not enough to suggest any abnormal pessimism; Returns in high-yield and emerging markets continue to rise; And the unemployment rate in the US is at long term lows, but is something to keep an eye on (a quick 10-13% rise could indicate a recession is imminent).

So as of now, I don't see much downward pressure on equities from the Fed (neutral), or foreign central banks (neutral/positive).

With that being said, I would actually have to recommend buying US equities for the year 2017. More specifically the SP 500 at around the 2180-2100 level, over the next few weeks, with a current upside target of 2250-2270 into the year 2017 (and beyond).

Could the ECB start buying stocks?
The only downside risk I can see is if Donald Trump wins, as he brings a more uncertain political landscape to the US. But I don't think he will beat Hillary Clinton. Of course, anything could happen (Brexit?), so I would highly recommend tracking voter sentiment with

As of right now, Hillary has a 60% chance of winning, but this Tuesday's debates could move things. Getting into a position now before the election could prove a good risk/reward, considering the likely outcome. But don't forget, since this an event with a known date, you can always hedge your positions with an appropriate options strategy.

Lastly, as a side note, I really like bitcoin's technicals right now. Best, riskiest investment you can make for the long term. I would own a few, as the upside potential is huge (especially when you consider that NIRP will likely make its way to the US, sooner than most think).

Wednesday, April 13, 2016

"Obama to forgive the student debt of permanently disabled people"
Why was this process made to be so "complicated" to begin with? Did we not want people actually getting these benefits? And why all of a sudden are we making it "easier" for these benefits to be acquired? One day after Obama held a closed meeting at the White House with Fed Chair, Janet Yellen (the only other private meeting they've ever had was when she was inaugurated)... and on the same day stock markets were technically set to begin a dramatic fall... Because I'm fairly certain this wasn't something Obama has been talking a lot about in the press lately.

If this were a scene in House of Cards it would go down something like this:
Fed Chair: "Mr. President, my analysts are warning me that market prices are about to fall considerably, tomorrow, if we don't intervene. This small drop tomorrow could be what irreversibly sets the market to fall for the rest of the year."
President: "OK, what can we do to make sure this doesn't happen? It's an election year with Donald Trump doing well and we need Clinton to become the first woman president. We don't want republicans using a market crash as political fodder."
Fed Chair: "We need the government to issue an emergency spending program. Like a small QE."
Adviser: "Mr. President, how about we spend $7 billion as debt relief for disabled Americans, using a program that was already signed off by Republicans but with certain clauses that made it very difficult for the program to actually work well. We can just remove those barriers and enroll everyone automatically."
Fed Chair: "That's perfect. That should buy the FOMC enough time so that at our next 'scheduled' meeting we can sound more dovish by holding off a rate increase even further. We don't want any of this coming off as an emergency, so we'll cover this meeting as one about general economic matters."
President: "Great. Perfect. The only people who will notice are technical analysts like Paul Sproge who also carefully read the news and correlate the two."
Fed Chair: "OK great. We don't like that guy anyway."
--End meeting--
The conspiracy is rife with this one, but when your fingers are as close as mine to the pulse, you can notice the difference between what is natural, and what is controlled. If you want truth, follow the money.

Sunday, April 10, 2016

Static Projections Made By Economists Will Lead To Economic Crisis

Flexible spinal cord implants will let paralyzed people walk

“It’s the first neuronal surface implant designed from the start for long-term application. In order to build it, we had to combine expertise from a considerable number of areas,” explains Courtine, co-author and holder of EPFL’s IRP Chair in Spinal Cord Repair. “These include materials science, electronics, neuroscience, medicine, and algorithm programming. I don’t think there are many places in the world where one finds the level of interdisciplinary cooperation that exists in our Center for Neuroprosthetics.”
It's this sort of integrated research which will accelerate and compound productivity and technological growth that Kurzweil & others are always talking about. It's also the thing most economists who project out into the future seem to forget to take into consideration when making projections. I think this is why we rarely see things like technological unemployment being written about by think tanks or policy institutes as a pressing socioeconomic issue.
I've read a report by one think tank which expects 5 million jobs to be lost by 2020 due to technology, but that same report expects a similar number of "new jobs" to be created (a supporting argument of most economists), which I think is ridiculous. Even David Autor agrees these "new jobs" are dependent on much education and training.
Page 27 of "Why Are There Still So Many Jobs?" by David H. Autor (referenced by the ERP report),
This prediction has one obvious catch: the ability of the US education and job training system (both public and private) to produce the kinds of workers who will thrive in these middle-skill jobs of the future can be called into question.
This is my favorite argument, that "new jobs" will be created to replace the old jobs lost, just like they always "have in the past". Which is true, we will have new jobs in the future and displacement has been overcome in the past with new types of work, but this work will be mostly be specialized or highly skilled, not the mundane, somewhat simple tasks that so many workers still do today and are becoming easier to automate. I don't mean to be demeaning, but imagine teaching middle-aged and older truck drivers how to maintain a database or become fluent in a programming language; this sort of skill takes decades to develop and often years of experience using technology. I think we ought to be realistic about our expectations, not simply looking at historical data of flexible re-entry from training.
I think this issue will end up catching policy makers off guard and ill-prepared, and will cause a lot of unrest within society. We need to start basic income trials in the United States now if we are going reduce this seismic risk, as opposed to 5 or 10 years down the road when this issue will likely have already caused a crisis in the economy.
The service and retail sectors, already packed to the brim with part-timers working 2 or three jobs, can only support so many more unskilled workers. Just imagine when the transportation industry becomes increasingly automated - one of many industries - how many people will be affected... it's scary that we're not doing more to address this.
These think tanks fail to imagine a world where computers can learn, and robotic systems can perform more complex tasks at an exponential rate. Even David Autor, author of 'Why Are There Still So Many Jobs?', who actually addresses machine learning, fails to think about the interdisciplinary growth of machine learning technology as it matures over the next decade, as he argues that "Machine-learning algorithms may have fundamental problems with reasoning about “purposiveness” and intended uses, even given an arbitrarily large training database of images". This sort of static thinking leads to static projections, which ultimately leads us to economic crisis, as these projections made by people like David Autor are literally sourced by the White House and morphed into policy (pg 363 of the 2016 ERP).
So it makes sense when we hear about a future economy with low unemployment, even as a massive jobs crisis potentially looms, since the minds of these policy-makers are full of incomprehensive projections.
From page 236 of the Economic Report of the President from Feb 2016,
While industrial robots have the potential to drive productivity growth in the United States, it is less clear how this growth will affect workers. One view is that robots will take substantial numbers of jobs away from humans, leaving them technologically unemployed—either in blissful leisure or, in many popular accounts, suffering from the lack of a job. Most economists consider either scenario unlikely because several centuries of innovation have shown that, even as machines have been able to increasingly do tasks humans used to do, this leads humans to have higher incomes, consume more, and creates jobs for almost everyone who wants them. In other words, as workers have historically been displaced by technological innovations, they have moved into new jobs, often requiring more complex tasks or greater levels of independent judgment. A critical question, however, is the pace at which this happens and the labor market institutions facilitate the shifting of people to new jobs.

Thursday, December 24, 2015

Quanergy: Autonomous Vehicles a Reality with Solid State LiDAR

One of the biggest hurdles for "Level 4" type driverless cars (complete automation from portal-to-portal) is the sensor gap in bad weather conditions; these cars are known to fail in bad weather conditions like heavy rain or snow.
LIDAR technology will change that, and this company (Quanergy) is bringing the cost down from a $70k sensor (on the google car), to just four $200 sensors. This is a key competent towards making these cars a reality.
Legislation will most likely be the last hurdle, as usual, but testing has proven and will continue to affirm that these cars are much safer than humans, which will probably hasten the legalization process.
Taking into consideration that these self-driving features are predominately software-driven (quickly implemented), can accumulate millions of shared-hours in simultaneous driving data, and are advancing in parallel with deep learning systems, these vehicles are truly coming sooner than we probably care to think about -- yet the socioeconomic implications remain colossal.

Delphi Automotive Systems, working with a Silicon Valley startup, says it plans to bring a new, solid-state lidar system for self-driving cars to market for less than $1,000 per car.