As debate intensifies over how newly listed companies should be incorporated into equity indices, attention has focused on whether investors tracking broad market benchmarks are being disadvantaged by some index funds being forced to buy into those companies. What the discussion is missing, however, are broader questions regarding the objectives that different indices are designed to serve.
This issue has been made topical by completed or proposed mega-IPOs such as SpaceX, OpenAI and Anthropic, whose valuations are so large that their index inclusion could trigger tens of billions of dollars of mechanical buying.
And index inclusion mechanics are only part of what makes these listings unusual. These are companies with limited public trading history, evolving business models, and in some cases no established profitability record.
For an index designed to reflect the market, fast-tracked inclusion of companies of this size makes sense. But for an index designed as a long-term investment solution, different questions should apply.
IPOs are noisy events – prices can swing sharply in early trading, business models are still being stress-tested by public markets, and the profitability picture may take time to clarify. Price discovery, in other words, takes time. A disciplined investment process tends to respect that – not as a judgement on the company itself, but in relation to questions about what the index is actually trying to achieve.
The 'Shadow Tax' Issue
In a recent paper, two Harvard Business School researchers found that so-called 'fast track' IPOs outperform comparable IPOs by more than 5% around inclusion dates before much of the effect subsequently reverses.1
The paper, by Marco Sammon and Chris Murray, estimated that this mechanism creates a roughly $5.8 billion "shadow tax" borne by index investors and issuers.
Of course, hidden costs to passive investors through broad-market index funds being front-run by arbitrageurs and market makers ahead of stocks going into an index at reconstitution is already a well-documented phenomenon.
The more recent concern, however, is that as companies now remain private much longer and reach enormous valuations before going on-market in fast-tracked listings, this mechanical feedback loop is magnified.
As to ways of ameliorating the shadow tax issue, several solutions are proposed, these include longer price discovery periods, phased index inclusion, and restricting inclusion until a large percentage of shares are publicly tradeable.
Each proposed solution seeks to balance benchmark representativeness against implementation efficiency and investor outcomes.
Benchmarks Vs Solutions
Beyond the mechanics of IPO inclusion, the mega-IPO debate highlights an important distinction between indices designed primarily as market benchmarks and those designed as investment solutions.
The costs documented above – the price impact, the return reversals, the wealth transfer to intermediaries – are not an accident or a failure of market design. They are the predictable consequences of indices that prioritise representativeness above all else. That is a legitimate design choice, but it is worth naming it as such.
At Scientific Beta, we require stocks to build a meaningful trading history before entering our indices – not as an arbitrary hurdle, but because the research and our investment objectives both point in the same direction. Factor exposures need data to be reliable. That discipline sometimes means accepting short-term distance from the benchmark, and we think that is the right trade-off.
While representativeness is naturally a central objective for benchmarking indices, investment solution indices typically are designed to achieve specific portfolio objectives like improving diversification, enhancing expected risk-adjusted returns or providing exposure to systematic factor premia.
The recent public discussion, while interesting, might be more fruitful if it extended beyond the mechanics of index inclusion and towards broader questions regarding design, implementation efficiency and investor objectives.
Put another way, the cheapest way to own the market is not automatically the best way to achieve an investor’s objectives, which is more a function of effective investment design and efficient implementation.
Beyond Tracking Error
Our view is that many of the issues in the IPO debate can be more productively viewed through the trade-offs investors face between benchmark alignment, implementation efficiency and long-term investment objectives.
As an observable, widely understood and often embedded variable within risk-budgets, tracking error remains an important consideration for many institutions. But it is rarely the only one. Investors may also consider other dimensions of index design particularly when these factors can influence long-term outcomes.
Decisions about eligibility criteria, inclusion rules, weighting methodologies and rebalancing schedules, for instance, can all have meaningful implications for investor outcomes. The relevant question is how effectively these design questions support the objectives an index is intended to achieve.
To be sure, benchmarks are important tools, but ultimately, they should be judged on how well they service investors' objectives. Once again, the questions not being asked are often the most important ones in portfolio management:
Let's start there and see where the debate goes.
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1 Sammon, Marco and Murray, Chris, Primary Capital Market Transactions and Index Funds (July 21, 2025). Available at SRN: https://ssrn.com/abstract=4929872 or http://dx.doi.org/10.2139/ssrn.4929872