Equity markets, especially in the US, are currently highly sentiment-driven, suffer from concentration risk, and are at risk of stretching reasonable valuations, in our view. There are hidden biases and risks in global equities.
As we near the end of 2024, US stocks look expensive in a historical context. The Cyclically Adjusted PE Ratio (CAPE Ratio) for the S&P 500, as at 1 November 2024, was 38, more than double its long term average 1.
The CAPE Ratio, invented by Professor Robert Shiller of Yale University, is a good way to compare market valuations over the long term 2. It is based on average inflation-adjusted company earnings from the previous 10 years. This makes it a less volatile measure than price earnings (PE) ratios based on company earnings over shorter periods.
PE ratios can be mean reverting. Whereas companies’ revenues and profits may grow for extended periods (Apple’s net income of $1.3bn in 2005 had snowballed to $94bn in 2024 – off a peak of $99bn in 2022), PE ratios are not expected to expand indefinitely. A PE is not a measure of the size or profitability of companies, but a ratio between two different sorts of quantities that are economically related: share price, and company profits. That relationship, between investors and company fundamentals, expressed by the PE ratio, may be expected to fluctuate in the short term, and to differ for different kinds of stocks (higher for faster-growing stocks), and for different regions (higher for more economically vibrant regions), but there is a mean reverting element to it. Though elastic, the PE ratio may strain when reaching extremes and may snap back towards the mean.
The Shiller PE is well above its long-term average
The S&P 500’s CAPE Ratio’s average value of 17.5 is for the period since 1881 2. If we take a shorter time frame, 30 years, then the average is higher, at 28; but even by that comparison the current value is more than a third higher than average.
The CAPE Ratio has been higher than it is today: its highest level was 44, in December 1999, at the height of the dot com boom, also known as the dot com bubble. That bubble finally burst in 2000-2001. While we do not make any predictions about a similar fall, the dot com boom makes an intriguing comparison to the tech-dominated market of today. In the late 1990s, enthusiastic buying interest was based on the birth of the internet, whereas today it is mostly on prospects for artificial intelligence (AI). A typical behavioural bias of investors faced by a new technology, like the internet or AI, is to overestimate its short-term fruition and underestimate its long-term transformative power.
Psychological biases
Professor Shiller is also well known for his work on behavioural finance. In his book Irrational Exuberance, he gave an excellent qualitative definition of a market bubble:
“A situation in which news of price increases spurs investor enthusiasm which spreads by psychological contagion from person to person, in the process amplifying stories that might justify the price increase and bringing in a larger and larger class of investors, who, despite doubts about the real value of the investment, are drawn to it partly through envy of others’ successes and partly through a gambler’s excitement.” 3
Shiller won the Nobel Prize in 2013, alongside Eugene Fama and Lars Peter Hansen. In his lecture at the prize ceremony, he argued that Fama’s Efficient Market Hypothesis (perhaps the main justification for so many investors turning to passive index trackers) is incorrect. The Efficient Market Hypothesis (EMH) holds that all information is incorporated accurately in market prices, but, Shiller and others have argued, it is an overly rationalistic picture of how markets actually work.
Reality is less than rational. Market prices partially reflect the psychological biases of their participants, we believe. Sometimes these biases are very far from rational. For example, Brad Barber and Terrance Odean, both of the University of California, found evidence that investors tend to buy attention-grabbing stocks, such as stocks in the news, stocks experiencing high trading volumes, and stocks with extreme one-day returns 4.
Another example is from Evangelos Benos and Marek Jocheck, who found that US companies whose names contain the words “America(n)” or “USA” earned positive returns of about 6% per annum during the Second World War, the Korean War and the War of Terror (after September 2001) 5.
More generally, psychologists Amos Tversky and Daniel Kahneman have argued that when forming beliefs about uncertain events, people tend to rely on a limited number of heuristic principles which reduce the complex task of assessing probabilities, and these can lead to biases 6. One such bias is anchoring, the making of estimates by adjusting insufficiently from a familiar starting point. This can have an application in investment: there is a tendency to anchor one’s opinion of a fair price to the recent price, even when by other, perhaps more rational, criteria it is very expensive.
The S&P 500’s market cap is dominated by the top few stocks
Concentration risk
An investor buying an ETF tracking the S&P 500 is putting about a third of their money into just seven of the 500 stocks of the index. The Magnificent Seven (NVIDIA, Apple, Microsoft, Alphabet, Amazon, Meta, and Tesla) occupy almost one third 7 of the market capitalisation of that index. Such an investor is therefore taking a bet on technology stocks, as well as on a growth investment style. That is fine, if they are making an informed decision, and accept the concentration risk. We worry, however, that some investors do not fully understand that “the market” is multifaceted and capable of being sliced and diced in a multitude of ways (market cap weighted, equally weighted, value weighted, quality weighted, low volatility weighted … to name just a few). Selecting a market cap-weighted strategy, like a S&P 500 tracker, is, we suggest, an active investment decision. Investors should think carefully before walking blindly and “passively” into 2025.
Sources
1 Professor Robert Shiller, available at https://shillerdata.com/
2 For further information see http://www.econ.yale.edu/~shiller/data.htm
3 Robert Shiller, Irrational Exuberance, Princeton University Press, 2000.
4 Barber and Odean, 2008, All that Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional, Investors Review of Financial Studies, 21(2):785–818. Available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=460660
5 Benos and Jocheck, Patriotic Name Bias and Stock Returns, Journal of Financial Markets, 16(3):550–70, 2013. Available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=993289
6 Amos Tversky and Daniel Kahneman, Judgment under Uncertainty: Heuristics and Biases Science, New Series, Vol. 185, No. 4157. (Sep. 27, 1974), pp. 1124-1131.Available at https://www2.psych.ubc.ca/~schaller/Psyc590Readings/TverskyKahneman1974.pdf
7 As at 13 November 2024, 31.9% of the market cap of the S&P 500 was supplied by the Magnificent Seven.
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