We recently undertook an analysis to try to better understand the structure and behaviour of the equity market, with a view to identifying cause and effect relationships that drive investment performance. Firstly, we organised the equity market into industry clusters based on similarity of investment performance. This is similar in concept to GICS industry groupings. A list of ASX clusters based on five years of data is set out at the end of the post.
Having identified these clusters, we can then consider how different external effects flow through into the investment performance of each. One topical example might be to ask how different clusters perform in an environment of rising short-term interest rates.
Unfortunately, there are some big challenges to properly doing this analysis. In particular, we need to look at several decades of historical data, and in the Australian equity market there aren’t a great many companies that have been listed and doing the same thing for that length of time. This is a problem we should be able to solve with further work, but for now we have supplemented the Australian analysis with an analysis of the US market, which provides a much more comprehensive data set.
Some of the early (and still preliminary) findings include the following:
You might expect that rising interest rates are bad for clusters with defensive/bond like characteristics, like utilities and staples, and you’d probably be right. Unfortunately, the market seems to get out of bed early on this one, and the performance impacts for those stocks are typically seen before the interest rate changes take effect. This is perhaps not surprising, as the market generally knows in advance which way interest rates are heading, and it is a simple mechanical exercise to adjust a valuation discount rate to adjust for this.
What is a little more surprising is that there does seem to be a lagged effect of interest rate changes for banks and for discretionary retailers: For example, where interest rates have risen in the past 12 months, the forward returns for those clusters appear to be depressed. While it may be obvious that rising interest rates should negatively impact demand for credit and for retail goods, it seems that the market may take some time to factor this in. This might be explained by the fact that it is not straightforward to forecast the ultimate impact on demand, particularly if interest rate rises occur in the context of strong economic growth.
This may be something to keep in mind if we see the RBA becoming increasingly worried about rising inflation.
Another surprising finding is that rising oil prices appear to predict future outperformance for energy companies. We would expect the market to pick up pretty quickly on this one, such that by the time you have noticed the rising oil price its too late to take advantage of it by buying energy companies, but the evidence suggests otherwise.
It’s possible that this is because producing a revised commodity price “deck” is a big exercise for investment bank economists, and so it takes some time for changes to flow through into updated price decks and then into the forecasts and valuations of the sector analysts. Nonetheless, this lag effect is a little surprising.
It’s also potentially interesting, given that oil prices have been on the rise in recent months. Energy companies generally don’t fit our quality-driven investment style, but for those with more of a trading orientation, this may be something to keep in mind.
We continue to sift through the data in search of gems of insight, but there seems to be one overarching conclusion emerging: if something is obvious to others in the equity market then it likely has no investment value – it should already be factored into prices. However, investment markets are not omnipotent; if something is difficult or time-consuming to assess, it is probably worth making the effort to understand it better than others.