Imagine viewing a financial market report without reference to an index? Whether it is consumer price indices (CPI) measuring inflation, stock market indices such as the S&P 500, or the Bloomberg Commodity Index (BCOM) – indices abound in financial literature.
Index time series provide a convenient way to look at relationships between developments in the economy and in markets. This is because index providers generally try to represent a market in a consistent manner.
Some providers have been doing this for a long time: for most developed financial markets, 20 years of data is available, and for some early-starters, at least 40 years of data on indices are available. This wealth of information provides fertile ground for both human- and computer-led analysis of perceived relationships between various markets.
Complacency: the cost of convenience
The convenience for analysts and market participants alike is that they do not have to worry about all the maths involved with weighting, as well as inclusions and exclusions of companies. If markets close on one day and some stocks stop trading while new ones replace them in the index, indices will not have sudden sharp movements due to reshuffling of their members and they should seamlessly continue as if nothing has happened.
As with most conveniences in life, this comes at a price – especially when using indices for longer-term financial analysis. Do indices really consistently reflect markets over time? This article aims to unveil some common challenges faced when working with indices, so that investors can better use them when making portfolio investments.
Equity indices and the evolution of economies
Much like shifts in economies (see the rise in services as a driver of US growth, measured using gross domestic product (GDP), in the following chart) the same can be seen with index constituents. In fact, sectoral shifts in indices can be much more pronounced, due to their weighting by market capitalisation.
While an index still represents the pool of investable securities even at extreme weightings, such as information-technology businesses forming more than a quarter of the S&P 500 by value – it can disconnect from the labour market and gross domestic product (GDP).
Such extreme changes, and extreme weightings, can be problematic for index users if companies in sectors that are gobbling up greater weightings in an index (as seen in the service sector in recent decades) react differently to economic shocks. In this case, past index data may be less useful in drawing conclusions for the present, given that the latest constituent companies may react differently to similar economic shocks than the earlier set of constituents.
Sectoral weights matter
A recent study explored the effects of interest rate hikes on small and large firms in services and manufacturing. Indeed, the study found rate hikes had a much worse effect on employment in large manufacturers than in similar-sized services providers. The finding was attributed to services prices being stickier than those in manufacturing.
Evolution of economy and market indices over time
Share of services in US gross domestic product and 5-year snapshots of sectoral weights in the S&P 500 index (classification estimated)