Market-cap-weighted indexes, most notably the S&P 500, have dominated investor inflows and performance since the financial crisis, yet their increasing concentration in a handful of stocks, often dubbed the ‘Magnificent Seven,’ is prompting renewed scrutiny. Critics, including Rob Arnott, founder of Research Affiliates and a long-standing challenger of these traditional indexes, contend that this approach inherently increases risks and introduces significant hidden costs for investors. Arnott, known as the ‘godfather of smart beta,’ recently unpacked these concerns, suggesting it is time for investors to consider strategies based on fundamental weightings, such as profits or revenue growth.
The Illusion of Passive Indexing
Arnott challenges the notion of market-cap indexing as purely passive, describing it as having an ‘active side.’ He illustrates this with a thought experiment: a strategy that buys companies after their market value has risen above a certain threshold, typically when they are ‘up 75% relative to the market in the last year and trading at twice the market multiple.’ The sell discipline, conversely, involves divesting when market cap falls below a threshold, often at ‘a loss of about 7,000 basis points relative to the market.’ Arnott posits that while 95% of indexing is indeed passive, the remaining 5% turnover ‘looks like a hypergrowth manager on crystal meth.’
The core issue, according to Arnott, lies in the weighting mechanism itself. He questions the logic of weighting stocks ‘proportional to their price — so the more expensive they are, the bigger its weight in your portfolio.’ This inherent bias leads to buying more of what has recently performed well and less of what has underperformed, a strategy Arnott argues is fundamentally flawed.
Hidden Trading Costs and Legal Front-Running
A significant drag on performance stems from the mechanics of index additions and deletions. Arnott highlights ‘legal front-running,’ where sophisticated investors anticipate index changes. When a stock is announced for addition to an index like the S&P 500, its price often runs up before the effective date. Conversely, deleted stocks plummet. Index funds, obsessed with matching the index and avoiding tracking error, are compelled to buy or sell at the market-on-close price on the day of the change, regardless of the price run-up or fall.
Arnott documented this pattern as far back as 1986 in an article titled ‘S&P Additions and Deletions: A Market Anomaly.’ He notes that S&P index funds collectively represent ‘roughly 25% of the total market cap of every stock that’s in the index.’ This concentration means that indexers are effectively ‘a herd of elephants trying to go through a single revolving door.’ The cost of this forced trading is substantial; Arnott estimates that indexes lose ’15 basis points per annum’ just from these trading costs, despite having an annual turnover of ‘three to 5%.’ This translates to a heavy trading cost of ‘three to 500 basis points per stock per trade.’
The Costly ‘Flip-Flop’ Phenomenon
Further exacerbating these issues is what Arnott terms the ‘flip-flop problem.’ Research indicates that approximately ‘28% within a decade’ of stocks added to an index are subsequently dropped. More dramatically, ‘almost half’ of deleted stocks rejoin the S&P within a decade. This churn incurs significant costs for investors.
- Added Stocks: On average, stocks are added after ’75 percentage points of outperformance’ and removed at a ‘7,000 basis point loss’ if they falter. Arnott points out that investors ‘didn’t participate in the 75, you did participate in the down 70,’ resulting in a net loss.
- Deleted Stocks: Stocks that are deleted and later re-added show an even more pronounced pattern. They ‘underperform by 3,500 basis points, give or take, in the year before they’re dropped,’ only to ‘outperform by 180 percentage points’ — roughly tripling relative to the market — before being added back in.
These flip-flops are ‘very, very costly,’ a problem Arnott suggests has not been widely studied until recently, highlighting a significant blind spot in traditional indexing.
A Fundamental Alternative: Economy-Weighting
To mitigate these issues, Arnott advocates for ‘economy-weighting indices rather than cap weighting or price weighting.’ This approach aims to mirror the economy’s true structure, rather than just market valuations. A fundamental economic weighting of an index would select and weight companies based on the size of their underlying business, using metrics such as:
- Sales
- Profits
- Net worth (adjusted for intangibles)
- Distributions to shareholders (dividends and buybacks)
By taking an average of these four measures, investors can create an index that reflects a company’s economic footprint. Arnott uses Nvidia as an example: while its market weight might be ‘seven or 8%’ of the total market, its economic weight, based on sales, profits, dividends, or net worth, is in the ‘2% range,’ averaging to ‘about one, one-and-a-half percent.’
The debate over market-cap-weighted indexes versus fundamentally weighted alternatives underscores a critical juncture for portfolio managers. As market concentration intensifies and the hidden costs of traditional indexing become more apparent, the call to look beyond simple market capitalization and embrace a more economically representative approach gains considerable traction among leading financial thinkers.
