By necessity, today’s topic will venture into the world of politics, so I warn you now – you might be offended. Actually, I have decided to cut jabs at all politicians, so if you feel like your team has been maligned, just read on, I will probably be even worse to the other side.
I want to speak about the recent “trade wars” that the Trump administration has set in motion. There can be no denying that America has ventured down a road of adversarial trade renegotiations not seen in decades. I am not making any judgments about this policy – it is what it is. But to think it doesn’t have profound implications for your portfolio would be naive.
What I used to think
Previously, I believed America’s trade stance was just Trump doing his “Art of the Deal” negotiations. You know – insult your opponent, be belligerent and take extreme stances right until the very end, at which point you just cut the best deal available.
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Four years ago we had a remarkably similar market price action to this year’s. And that makes no fundamental sense, since all of the factors which should matter are different.
Four years ago, the Fed was still doing QE3. That program was winding down, but in October 2014 the Federal Reserve still added another $24 billion to its balance sheet. Contrast that to October 2018, when the Fed is unwinding its balance sheet at a stated rate of $50 billion per month.
Four years ago, the U.S. was in the middle of President Obama’s second term, facing a mid-term election, and Donald Trump was not even one of the 17 declared Republican candidates yet.
There is little doubt that Federal Reserve policies have resulted in mispriced risk and massive distortions in the economy. Fed Chairs Bernanke and Yellen were masters of distortion (keeping rates too low for too long) while Fed Chair Powell (Hurricane Jerome) is raising rates rapidly in the face of little-to-no inflation. Throw in Hurricane Florence and we have “The Mist” where fear changes everything.
Housing starts for September were released yesterday and, as expected, the numbers were down across the board (except for the West where it is seemingly always sunny).
1-unit starts (aka, single family detached) are still below 2000 levels thanks, in part, to The Federal Reserve dropping their target rate like a hammer to 1%. We got a massive construction response. That blew up, so The Fed dropped their target rate like a hammer … again from which Hurricane Jerome is only recently begun raising.
Somehow, the scale of May 29 keeps getting bigger. I should clarify, meaning that the very few data series that can pick up on what happened that day have had trouble picking up on exactly what happened that day. It was, to put it simply, a global collateral call of some undetermined magnitude. We know it was substantial by the earthquake across markets in the real world.
One of my favorite things to do is discover and utilize somewhat obscure, new, misunderstood, or underutilized datasets. Or indeed, to look at an existing and well-understood set of data in a different way. In today’s post we look at a little bit of all of the above. What we’ve got here is a global composite consumer sentiment indicator I’ve calculated from the Thomson Reuters IPSOS consumer sentiment surveys (using IMF GDP data for the weightings).
I’ve shown this indicator against the key global equity benchmark (the MSCI All Countries World Index or ACWI for short), and the global manufacturing PMI (basically business confidence). The interesting thing about this chart is that up until the turn of the year, these 3 inter-related indicators were all headed in the same direction (i.e. up)… so what’s changed?
If someone had asked me to name the driving factors influencing US stock market performance return over the past year, I might have guessed the cut in the tax rate, but I would then be at loss to further explain what has been moving stocks.
Lucky for me, Bloomberg has this great function that allows us to examine how various portfolio factors have performed over different time frames. It works by taking the stock market universe, then ranking the companies by the requested factor (whether it be P/E, cash flow, etc…) into five quintiles. Using the average return of the top quintile during the requested period, minus the average return of the bottom quintile, gives a great sense of the sensitivity of that factor in individual stock market performance.
Let’s have a look at the best and worst factors during the last year: