Last week I wrote about the apparent confusion caused in some quarters by strong stock returns against a backdrop of weak macro and profits data. I argued that two important reasons behind this were the removal of rate pressure, and the unwind of the episode at the end of 2018.
However there is another observation that is seemingly obvious but easy to forget: asset prices are already incorporating forecasts of the future.
Take the role of Purchasing Managers Indices (‘PMIs’). These surveys of business have gained more attention over the last year or so since they provide a simple metric to assess both the health of manufacturing and a potential indicator on the impact of a trade slowdown:
The deterioration at a global level has been notable:
In Germany, where manufacturing weakness and trade sensitivity are significant, the disconnect between the apparent information provided by the PMI and the performance of the equity market so far this year is telling:
But this is no puzzle. Two pieces in the last few weeks have been important in explaining why such a disconnect can exist. The first, from the Bank of International Settlements made the following observations:
- “Changes in equity prices, corporate bond spreads, and US dollar indices help predict PMIs, and explain a large share of variation in PMIs and GDP.”
- “Over a one-year horizon, the shock related to equities explains more than 60% of the variance of global manufacturing PMIs.”
Earlier this month, a piece from AQR, noted the same phenomenon in fixed income: “Our internal research indicates that PMIs, while they may have some predictive value, tend to lag fixed income prices rather than lead them.”
The implication of this is that much of what we are being told by PMIs is already anticipated by the market. An alternative view, that market moves may periodically influence the reponses of those surveyed or the actions of corporations, should also not be discounted.
Leading indicators or led indicators?
Nor should we be surprised that macro data is often predicted by, rather than a predictor of, what happens in markets. In 2011, the Conference Board, which produces ‘leading indicators’ to provide a picture of cyclical dynamics around the world, noted the following:
“Financial indicators such as yield curves and stock prices have been extensively used as leading indicators of economic activity due to their forward looking content.”
Many recession indicators famously use the yield curve as an input, and other measures derived from asset markets are also frequently used. The purpose of the Conference Board piece was to introduce a new element, the ‘Leading Credit Index’ (LCI) into the range of components that make up the overall index, increasing the weight attached to market variables relative to other inputs.
Today around 25% of the components of the US leading indicator reflect some element of market pricing:
It should not be unusual therefore that the release of some of these indicators fail to move markets as we might expect, since the level of markets was to some extent already embedded in the indicators.
This is in no way a criticism of the producers of such indicators. After all, their intention is not to forecast markets but to measure the economy. However we should be wary of our own temptation to look to such metrics as a heads up on prospective investment returns.
The role of surprise
Just as the market doesn’t casually wait for each new piece of data to be released before deciding to move, nor is it infallible. The strong performance of the German equity market this year doesn’t mean that the manufacturing PMI is inevitably going to improve; and it would probably tell us little about prospective investment returns even if we knew it would. What matters is how outcomes confound what is already in the price.
Of course most of us are well aware of this, and commentary (correctly) looks to focus on how much data releases surprise relative to expectations.
Yet even assessing how much of the news is actually ‘new’ is a challenge. We have previously discussed some of the weakness of surprise indices, and it can even be the case that data that shock relative to economists’ forecasts can have limited impact, either because investor focus is elsewhere or valuations are already stretched.
All too often our desire is to draw a connection between market moves and the what is in the news right now; despite our best efforts it can still be hard to resist saying things like: ‘stocks fell on weak PMI numbers.’ But to view markets in this way is to open the door to an illusion of control. Markets are frequently confusing and uncertain, and the best investment results come from accepting this reality rather than trying to fight it.