The unemployment battle: structural versus cycle

The key macro battle that will impact all investors and asset allocators is between the view that unemployment is currently still a cyclical problem versus the impression that there is a structural issue that is currently affecting labor market. Now, there is a strong case for each and there are clear signs that there are structural problems but where you place more emphasis between these two views will make a huge difference in your portfolio construction. I will not go through all of the evidence and arguments but focus on the general portfolio implications. 

If you believe that current unemployment is still a cyclical problem, then you will also believe that monetary and fiscal policy can be used to push unemployment down. Keeping rates low will not be inflationary since there is still slack in the labor market. In fact, you would want or accept longer and stronger policy action to break through the output gap that still currently exists. Under this view, you will not worry about inflation or the potential for tight labor markets that will force wages up in the near-term.  You would construct your portfolio under the view that monetary policy by the Fed will continue and there will not adverse harm to bond markets or equity markets.  

The structural view is that much further increases in employment may be limited. There are structural reasons for the lower participation rate and the long-term unemployment. The Fed is pushing on a string and labor markets may be tighter for those who have skills needed by the market. Wage rates can move higher because there is a growing labor tightness. The Fed will be slow to react and there will be higher inflation. The Fed will be late to any policy change.  Wage increases could reduce profits and lead to higher inflation. 

Call it a cyclist versus structuralist fight. Chairman Yellen seems to be biased to the cycle arguments and this should raise alarm bells with structuralists. If I ask you your view on this issue, I should see a portfolio that has the same appropriate view. The underlying assumptions you have about the economy is extremely critical at this time. Just looking at the data is not enough.

What are money flows telling us?

A recent FT article focuses on global mutual fund flows. It caught me by surprise to see the significant flows into bonds. This was supposed to be the ongoing period of the Great Rotation. The flows do not show a rotation but just a grab for yield and this is the problem for the economy. This grab for yield creates the credit bubble we are currently seeing. Central banks want the movement into risk assets to boost the economy, but not just a switch to yield out the curve. 

The flows to passive equity could be investors just being wise the poor performance of active management but it is also another indication that there is a grab for risky assets and yield. 

Simple observations

The following quotes are useful for any researcher even financial modelers.

The aims of scientific thought are to see the general in the particular and the eternal in the transitory.
-Alfred North Whitehead 

The purpose of models is not to fit the data, but to sharpen the questions.
-Samuel Karlin

There are no foolish question and no man becomes a fool until he has stopped asking questions.

-Charles Steinmetz

We are trying to prove ourselves wrong as quickly as possible, because only in that way can we make progress.

-Richard Feynman

Far better an approximate answer to the right question, which is often vague than an exact answer to the wrong question, which can always be made precise.

-John Tukey

Understanding of history is critical for traders - to appreciate what will be repeated and what is unique.

History is the science of things which are never repeated.
-Paul Valery

It is always a mistake for the historian to try to predict the future. Life, unlike science, is simply too full of surprises.
-Richard Evans

Something to remember when discussing policy.

Politics is not the art of the possible. It consists in choosing between the disastrous and the unpalatable.

-John Kenneth Galbraith

All of what is interesting happens when it storms.

Economics is a discipline for quiet times. The profession, it turns out,... has no grip on understanding how the abnormal grows out of the normal and what happens next, its practitioners are like weather forecasters who don't understand storms.
-Will Hutton

The problem with quant models

I have a bias and it is with the use quantitative investing strategies. I like the idea that there is no commentary such as "I feel the market is going higher". I like the idea that back-tests can be done for any model and there is clear way to measure the success of a model. However, quant modeling has its own set of biases for which special care should be taken.

Here are three. Similar comments in the context of numbers based models have been made by Aswath Damodaran, the NYU professor, in his blog.

The illusion of precision - There is a precision with using a model and focusing on the numbers but as anyone who has worked with numbers knows, there is error with any model and with the inputs used for a model. Economic data is subject to revisions. Good models of risk premia can only explain a small portion of the variation in the data. There is a lot of imprecision with models and it takes skill to appreciate and understand those limits.

The illusion of objectivity - Some will say that you just look at the cold hard facts, but no model is truly objectivity. A model incorporates the biases of the model-builder. This cannot be helped. Every choice made by the model-builder includes his view on how markets operate.

The illusion of control - Markets change. There are structural adjustments and changes in the sensitivity between the market and variable inputs. Models are inherently backward-looking so they are never in control of the future. 

Quantitative modeling may avoid some behavioral biases, but that does not mean they are without there own set of biases.