Right, so if you have a fragile ego and are the type of person who is out looking for confirmatory evidence for your optimistic outlook for the US economy, you’re probably in a bad mood.
Why? Simple: all the data has been bad over the past couple of days.
Friday we got the first read on Q1 GDP and it was bad (although heading into the actual print it kinda felt like expectations had been set low enough that the market was able to take the number in stride). And then this morning, the Fed’s favorite econ indicator dipped (back) below target, spending came in light, and to top it off, the ISM and Markit prints were lackluster.
So heading into the Fed meeting (which, you’re reminded, is sure to be a non-event), there are very real questions about the extent to which the economy is on sound enough footing to warrant even cautiously optimistic projections and/or a continuation of the policy normalization trend.
Within that debate is the now ubiquitous “hard” versus “soft” data argument. No matter which side you fall on (i.e. whether you think the still relatively euphoric soft data is what matters of whether you think hard data “reality” is what counts), you should take a few minutes and consider the latest from former FX trader Richard Breslow, who was out this morning weighing in on what has become perhaps the most contentious question in the econ world.
But before we leave you in Breslow’s capable hands, do consider one chart which we think certainly seems to raise a number of questions about whether it makes sense for the ECB to be as far behind the Fed as they are in terms of normalizing policy:
I’ve really been of two minds with respect to the hard versus soft data debate. On the one hand, it can be argued that soft data, like talk, can be cheap. It may or may not have some predictive value for the future. And we can all stipulate that economic forecasting is an inexact science. Hard data, on the other hand, is something you can touch and feel. So shouldn’t it be easy to decide which data set to follow? I used to think so.
- Of course if the soft data implies increased spending and investment here and now, then it’s really hard data masquerading as soft. Otherwise, it falls more into the just one person’s opinion category
- Years ago, I worked for a very aggressive trading house. At an off-site the subject of this cool new thing called the Sharpe Ratio came up. The antithesis of our “we have deep pockets, lots of traders and it only counts when the profit or loss is realized” mentality. The trading manager scowled at the notion of rewarding people on a risk-adjusted basis and said, “I can’t eat from this ratio thing.” He and everyone else eventually learned that ignoring that soft data had real consequences
- As investors, focusing only on the tactilely satisfying data misses the point that the Fed doesn’t do so. They aren’t bound, like the ECB, to a very visible mandate. In the long run only hard data matters but not so for meeting this year’s dot plots. This is a central bank not looking for an excuse to be dovish or, more importantly, overly cautious. Listen to their speeches. And do not think the balance sheet discussion is devoid of serious monetary policy implications and intentions
- The current modus operandi is to tighten unless explicitly warned off. Spend less of your time looking for overt strength in numbers to prove the case than for signs of worrying weakness. For now ties go to the hikers
- And it shouldn’t go unnoticed that as the Fed’s reaction function has shifted, there’s growing academic pushback against the notion that the neutral real short-term interest rate has fallen as much as has been assumed. It turns out that the FOMC may no longer wish to be perceived as severely limited in their policy choices. It’s forward guidance delivered in a different way. Scholarly contributions have always been subject to the chicken or the egg controversy
- Subjective data may be open to greater interpretation but it isn’t soft in the head. And well worth being given its due as you contemplate your trading strategies