Read in 3 mins 383 viewed
Investment decision-making relies on the skilful interpretation of data. There is rarely only one perspective on a data set; usually, there is a different way to see things.
Take market price graphs. Is that dip to be feared, or is it merely a blip in an inexorable long-term ascent? Two investors may well see it quite differently. Take record bull markets. The bull market in the S&P 500 index that started on 9 March 2009 has been the longest since records began, straddling the administrations of Barack Obama and Donald Trump, and lasting 3,482 days to its all-time high on 20 September 2018. But looking at it a different way, it has returned considerably less than the shorter bull market of 11 October 1990-24 March 2000 under GHW Bush; and it was preceded by a much worse drawdown (2008), so its early years were merely the clawing back of previously lost ground.
TWO SPECIES OF VOLATILITY
One way to get a grip on the twists and turns of markets is by studying their volatility. The most familiar measure is historic volatility, which calculates the dispersion of a time series of returns in relation to their average; that is, how much the returns have been fluctuating. But there is another kind of volatility called cross-sectional volatility, which provides a different way to see things.
Historical volatility takes the returns of a single security (often an index) and compares them over many different time slices. By contrast, cross-sectional volatility compares the returns of many different stocks in a single block of time.
Over recent years, US equity market cross-sectional volatility has been low, and it stayed fairly low despite an increase in historical volatility in 2018. There is a macro explanation of the increase in historic volatility: central bank balance sheets, bloated after years of quantitative easing, are starting to contract; liquidity has reduced, the US dollar has strengthened, and some of the money thrown at risker sectors of equity markets has been pulled out. But what is the explanation for low cross-sectional volatility staying low? It is especially puzzling because the dispersion of companies’ return on equity (ROE) has increased.
Arguably, investors have become more indiscriminate, causing the shares of companies with divergent fundamentals to bunch together. Low cross-sectional volatility may be partly a by-product of the popularity of passive investing, which makes a virtue of investing indiscriminately.
HOW ARE THE MIGHTY FALLEN
Passive investing has a place, but may sometimes rest on questionable assumptions. One assumption is that a well-known index, such as the S&P 500, is a mirror held up to the market. In fact, an index is just one way of seeing the market. The S&P 500 is a great starting point, but not the only perspective.
The S&P 500 and the FTSE 100 are examples of market capitalisation- weighted indices. They weight more to stocks that have larger market capitalisations. Since those stocks’ prices have risen, investors in passives tracking such indices are adopting a momentum strategy (that is, a strategy that weights more to assets that have already risen).
Assuming five hundred stocks in the S&P 500, an equal weighting would give just 0.2% in each stock. Market cap weighted indices weight far more to leaders. At the end of 2008, the companies in the S&P 500 with the largest market cap included Exxon Mobil and Procter & Gamble. But a heavy weighting in them was a mistake. Since then to 21 November 2018, they have had had mixed fortunes. Microsoft has done well, returning 579.6%, but General Electric has a negative return (-32.5%), Exxon returned only 31.2%, and Walmart (114.4%), Procter & Gamble (103.5%) also lost their leadership positions.
The current leaders are Apple (3.6%), Microsoft (3.3%), Amazon (3.2%), Alphabet (3.0%) and Berkshire Hathaway (2.1%). (Facebook fell outside the top five during 2018).
Only time will tell how all five perform over the next decade. In the meantime, diversification may be kept in mind by those who prefer to see things a different way.