Guest User

April 16, 2026

Episode 405: Timothy Edwards - Inside S&P DJ Indices

Guest User

April 16, 2026

Tim Edwards is Managing Director and Global Head of Index Investment Strategy at S&P Dow Jones Indices (S&P DJI). The group provides research and commentary on S&P DJI’s entire product set, including U.S. and global equities, commodities, fixed income, and economic indices. Prior to joining S&P DJI in 2013, Tim worked for Barclays Capital, initially within fund-linked derivatives and subsequently in exchange-traded products and index-linked derivatives. Prior to that, he worked at

the Royal Institution of Great Britain. Tim holds a Ph.D in pure mathematics from University College London.

What if the decades-long debate between active and passive investing wasn’t really a debate—but a data problem?

In this episode, Ben Felix and Cameron Passmore are joined by Tim Edwards, Managing Director and Global Head of Index Investment Strategy at S&P Dow Jones Indices, for a deep dive into the SPIVA Scorecard—the industry’s most enduring and data-driven comparison of active versus passive investing.

Tim explains how SPIVA has evolved over 25 years, why survivorship bias matters more than most investors realize, and what the data consistently shows across markets: most active funds underperform their benchmarks—especially over longer time horizons.

The conversation goes beyond the headline results, exploring persistence (or lack thereof) in manager performance, why bond funds don’t escape the same fate, and whether combining active funds improves outcomes (spoiler: not really). They also tackle common critiques of indexing, including index rebalancing costs, IPO inclusion concerns, and the role of index funds in market concentration.

Key Points From This Episode:

(0:00:17) Introduction to the SPIVA report and its long-standing role in the indexing vs. active debate
(0:01:18) Overview of the episode: SPIVA, index behavior, IPOs, and market concentration
(0:03:30) What SPIVA is and how it measures active fund performance versus benchmarks
(0:04:14) Why SPIVA was created: to inform—not settle—the active vs. passive debate
(0:05:20) How SPIVA has evolved across regions, asset classes, and research dimensions
(0:06:59) Controlling for survivorship bias and why it materially affects results
(0:08:57) Real-world survivorship rates: ~50–60% of funds survive over 10 years
(0:10:12) Core finding: most active funds underperform, especially over longer horizons
(0:10:57) Comparison of equity vs. bond funds: slightly better outcomes in bonds, but still mostly underperformance
(0:13:44) Structural differences in equity vs. bond markets (e.g., skewness, dispersion)
(0:15:06) Typical survivorship rates across markets and how crises affect fund closures
(0:16:02) Persistence analysis: past winners rarely remain winners
(0:18:16) Global variation: some markets (e.g., international small caps) show slightly better active results
(0:20:41) “Better” doesn’t mean good: even in stronger categories, most funds still underperform
(0:21:31) Do active funds perform better in down markets? Not consistently
(0:23:37) Multi-asset portfolios of active funds: 97% underperform over 10 years
(0:25:10) Selecting top-quartile funds improves outcomes slightly—but not meaningfully
(0:26:46) Surprising findings in SPIVA and how market dynamics shape results
(0:27:45) Impact of SPIVA on industry behavior and investor education
(0:29:03) Ben shares how SPIVA influenced his own career path toward indexing
(0:30:08) The “index effect” and whether index rebalancing creates performance drag
(0:31:30) Why the index effect has largely diminished due to market competition and liquidity
(0:34:05) Research on IPO inclusion and whether index rules create systematic return drag
(0:36:57) How S&P handles IPO inclusion (e.g., 12-month seasoning rule for S&P 500)
(0:39:58) Whether index methodology could evolve due to larger modern IPOs
(0:42:36) Addressing concerns about large IPOs entering index funds
(0:43:52) Historical perspective on market concentration and today’s top-heavy indices
(0:45:29) What happened to past top-10 companies: many declined, but markets still thrived
(0:47:10) Creative destruction: why markets can succeed even when leaders fail
(0:49:15) Weak relationship between market concentration and future returns
(0:50:55) None of today’s top companies were top companies in the 1960s
(0:52:16) Key takeaway: markets evolve, and cap-weighted indices adapt automatically
(0:53:58) Concerns about index fund growth and its impact on market function
(0:54:30) Benefits of indexing: lower fees and often better investor outcomes
(0:56:15) Timing the market: why waiting for a bigger drop tends to hurt returns
(0:58:52) “Time in the market” vs. “timing the market”
(0:59:09) Tim’s favorite index: the DSPX dispersion index
(1:00:53) Defining success: why happiness is the ultimate metric

Read The Transcript:

Ben Felix: This is the Rational Reminder Podcast, a weekly reality check on sensible investing and financial decision-making from two Canadians. We're hosted by me, Benjamin Felix, Chief Investment Officer, and Cameron Passmore, Chief Executive Officer at PWL Capital.

Cameron Passmore: Welcome to episode 405, incredible number, 405. Today's episode, Ben, is all about the SPIVA report and so many listeners know exactly what we're talking about when we say SPIVA report, but this report has been, it's kind of the iconic report that's been kicking around the industry for so long, especially for people interested in the benefits of indexing. I can tell you, this is a report that I think back to reports, what, 25 years old now?

The SPIVA report was such an influential part of our thinking way back when we really embraced the benefits of indexing. Today, we got a chance to talk with Tim Edwards, who's the Managing Director of Index Investment Strategy at SIP Dow Jones Indices about the SPIVA, which is Standard & Poor's indexing versus active scorecard. Really cool conversation about something that's been part of the discussion literally for 25 years.

Ben Felix: The first segment of the episode is about the SPIVA report, but then we get into some pretty interesting topics about whether indices and therefore index funds time the market. We basically asked about Marco Salmon's research, had a neat discussion there. We talked about the potential large private company IPOs and how that will affect indices and index funds.

Some other really interesting discussion points there. We also talked about market concentration, current levels of market concentration in the context of a broader historical perspective and just how that has played out in the past. A little bit of discussion on whether index funds may or may not be contributing to that concentration.

Then Tim also shared some interesting analysis he's done, he did in the past on whether it makes sense to wait for a further market decline after an initial market decline before investing in the S&P 500. Tim also tells us what his favorite index is, which is kind of a fun question for someone who's deeply embedded in the world of index creation and management. Tim, as you mentioned Cameron, is the Managing Director and Global Head of Index Investment Strategy at S&P DJI.

His group provides research and commentary on S&P DJI's entire product set, including US and global equities, commodities, fixed income and economic indices. Prior to joining S&P DJI in 2013, Tim worked for Barclays Capital, initially within fund-linked derivatives and subsequently in exchange-traded products and index-linked derivatives. Prior to that, he worked at the Royal Institution of Great Britain.

Tim has a PhD in pure mathematics from University College London. Smart fella.

Cameron Passmore: He is indeed. Pretty good setup, I think, to a great conversation. You ready to go?

Ben Felix: Let's go to our conversation with Tim Edwards. Tim Edwards, welcome to the Rational Reminder Podcast.

Tim Edwards: Hi, thanks for having me.

Ben Felix: Very excited to be talking to you.

Cameron Passmore: Indeed.

Ben Felix: To kick this off, let's ask a question that some of our listeners may already know the answer to, but it's worth discussing.

What is the SPIVA report?

Tim Edwards: First of all, thank you for asking. For those who don't already know, SPIVA is an acronym. It stands for S&P Index Versus Active.

It's the brand name for a series of reports that my company produces covering fund markets around the world. It's actually 10 different regions where we publish the report every six months. It does a lot of things, but it's probably most famous for regularly providing updates across different kinds of fixed income and equity categories on what proportion of actively managed funds are beating the benchmark and what proportion are falling behind.

Cameron Passmore: Why did S&P Dow Jones Indices start publishing the SPIVA report?

Tim Edwards: It actually started publishing a long time ago. The first report covered active performance came out about a quarter of a century ago. And the reason we started doing this report was a really simple one. There was then, there is now, and I suspect there will be a long time into the future, a very interested, engaged debate around the relative merits of active investing and passive investing in different markets.

And we didn't want to settle that debate, but what we wanted to do was to inform it with data. So we could look at different segments, different time horizons, and people talking about whether it was better to have an active fund or a passive fund could continue their conversation in the light of the prospects or the chances of picking outperforming funds in different market segments. That's why we did it essentially, just to help people have better informed conversations.

Ben Felix: When we get into some of the data, people may argue that you have in fact settled the debate, but we'll get to that in a second. How has the SPIVA report evolved over time?

Tim Edwards: In some ways, not much actually. You go and dig out some of the reports from 20, 25 years ago. There are a lot of similarities in terms of what do we actually report?

How do we do it? Where it has evolved is in a few different dimensions. So the first thing we did is we've extended over time the number of markets that we cover.

So the original, the first report was essentially a style box, large, mid, small, growth, blend value, then adding international equities, then adding more categories, then adding fixed income. That's for the U.S. report, but we also extended our coverage around the world. There's now a SPIVA scorecard for the Canadian fund market, for the European fund market, UK, Japan, Australia, New Zealand, and so on.

And we also added research that helped to analyze the question of, and why are we seeing what we're seeing, and what can you do about it? So we looked at our persistence reports were launched a little less than 20 years ago, looking at persistence in active performance. And we've also done a range of different analyses, some of which we might talk about, looking at things like net of tax, or portfolio, or an institutional gross-of-fee performance.

So we built up a rich library that helps answer or address all sorts of different questions. But interestingly, the basic SPIVA, you look at it from 10, 20 years ago, the basic concept of a disciplined sampling of actively managed funds and looking at how easy it was to pick funds that beat the benchmark. There's a consistency in our statistics that means that we can compare the figures that we're seeing today to figures in previous years.

Cameron Passmore: And how do you make sure that the SPIVA data are not biased in favor of indexing?

Tim Edwards: This is a really important question. A few things that we do to control for biases. The first one is actually a really important bias implicit in the way that the fund industry works.

And that is the following. If you were to go out to a fund data provider, and you asked the question, okay, show me all the, why not stick with Canada, all the Canadian active equity funds, and I want to look at the 20 year track records of all those funds. And you looked at those 20 year track records, what you would find is that many of them had very admirable performance.

And the missing piece of the puzzle is that those are the ones that survived to post a 20 year track record. And many of the funds that were available at the start of the period, if they underperformed are no longer in the sample set today. So there's a decent amount of survivorship bias that we have to take account for.

So the first thing we do is we look at not the funds that are available today, but the funds that were available for sale, whether it's one year ago, five years ago, 20 years ago, and so on. We have a very robust methodology that we share it all in detail in the reports. And over 20 years, we've had it checked, verified, criticized, analyzed by the industry.

And I think that's something super important. These are public documents. They have been independently replicated by academics and similar.

And that helps us, keeps us honest. The other thing, which is a subtle point, is we don't just publish the numbers when they suit us or when they suit indexing. Sometimes, some markets, some years, and in fact, just about every time we issue the reports, we'll find some market where a majority of active funds outperform.

It's really important that we report that too; regular, consistent methodologies applied over time, subject to public scrutiny, but also dealing with potential biases in a sample. That's how we try and make sure that we allow our data to serve that real purpose of just informing conversations rather than pushing them.

Ben Felix: I don't think I have a question here about survivorship, but just looking at this SPIVA Canada year-end 2025 report at the 10-year horizon, survivorship is just over 60%. It's a lot of funds that are shutting down over time.

Tim Edwards: Yeah, it's really important to take that into account actually. And one of the things that we sometimes write in the reports or have done over the past is if the fund industry hopes to improve the long-term statistics, one of the things that might help is greater patience with underperforming funds. Because what happens with underperforming funds is it's not that they've got a bad process or a bad manager, but they're attracted to a particular style, which has gone through three or worse year underperformance regime.

In order to outperform, they need to have the chance to, which requires potentially a greater degree of patience.

Ben Felix: There is some data I've seen that poor performing funds tend to go on to do a little bit better and well-performing funds tend to go on to do a little bit worse.

Tim Edwards: No, absolutely. There's a degree of mean reversion in relative performance, which is surprising for those who would hope to see evidence for skill and to hope that skill was identifiable in history.

Ben Felix: If we think about the SPIVA reports, what are the main points that consistently come out of this research?

Tim Edwards: There are a few things that really come through. The first is that most of the time in most markets, most actively managed funds underperform benchmarks. And that becomes more and more true the longer the time horizon you apply.

I use the word most three times there. In every report, there are always funds who do beat their index. That's one of the more interesting aspects of this report.

But I think the most, you say, what's the main point? It is hard for active funds in most markets to beat benchmarks is one of the main points that comes out globally consistently across asset classes, across different kinds of fund categories.

Cameron Passmore: How do active bond funds compare to indices in the SPIVA analysis?

Tim Edwards: No matter what our scorecards say, I think there is a perception generally in the marketplace. The bond markets are different. There are, I should say, opportunities, both idiosyncratic and systematic that bond managers can take advantage of.

And there are different dynamics to the bond markets that give support to an intuition that maybe they're better favored. What we found in the SPIVA scorecards globally, which has kind of simplified the results in the US and globally and in major markets, two things are true, which sound contradictory, but they're not, I promise. First is that bond funds tend to do a little bit better, but not better enough.

And what I mean by that is, so in equities over a one-year time horizon, if you take an average across all the major markets that we covered for last year, we saw 67% on average across category underperformance in equities. And the number for bonds was closer to 63%. So, it is true that the record is better in fixed income, but it's not true that it's sufficiently good to turn it into majority outperformance.

You still see a majority of funds underperform. Something else that's interesting about the bond markets and different from the equity markets, shown in our institutional version of our scorecards, it's called the institutional SPIVA scorecard, that looks at gross-of-fee and net-of-fee underperformance rates. And what we find is that over the long-term, there are many active bond funds that are outperforming before fees, but they are outperforming by not an awful lot.

Majority outperformance turns into majority underperformance after fees in the bond markets. In the equity markets, that is less true. Fees don't make so much of a difference as they do in bond markets, which kind of makes sense from a sort of intuitive basis.

If you look at international equities or go anywhere, do anything, multi-cap, US manager, the difference between a winning stock and a losing stock can be quite big. Last year in the S&P world, global large cap, large mid cap, half of all the stocks had a performance which differed from the benchmark by 20% or more, half of them. Whereas if you are a manager operating in the, we'll go Canadian again, Canadian intermediate sovereign bonds, you're going to buy government bonds with a maturity ranging between three and seven years.

Even if you get every bet right, you're not going to justify a very large fee again and again and again over time, even if you have insight. It's quite intuitive, but we do see it in the data. The fees make a bigger difference in bond funds than they do in equities.

Ben Felix: My mind went to skewness when you were talking about that, where in equities because of the skewness, you're just less likely to pick the winning stocks, but in fixed income, you're not going to have that same kind of skewness.

Tim Edwards: This is one of those fascinating things that create real nuance. The skewness argument in equities is historically, very, very few stocks outperform the average. You get a load that do okay, and some that go up 10,000X, 20,000X, and they really push up the benchmark returns.

Certainly in credit, it's the opposite case. Most bonds deliver their yield to maturity. Some don't.

If you take the view that, let's say we had a default rate of 5% in high yield over the next year, suppose we did, then I'll give you a strategy that will outperform with 95% probability, and you just pick a bond at random. 95% chance you don't have one that defaults. Benchmark has 5% that will default.

The reality is that that's something which would drive, first of all, would drive pure outperformance, but as soon as you start thinking about risk, it looks completely different. It does emphasize the importance of survivorship bias in some sense, because maybe the ones who disappeared blew up. It's a possibility.

Ben Felix: I did mention this earlier. I mentioned some data for Canada, but what portion of active funds typically survive over long horizons?

Tim Edwards: The Canadian statistic that you referenced was about 60% of funds surviving over a 10-year period. That's a very representative statistic, actually. If you look across different markets, some better, some worse, but around 50% to 60% is a really typical survivorship rate over the last 10 years.

Of course, the advantage of having these scorecards that go back over the years is that we can also say that's a fairly typical survivorship rate historically. There are exceptions. However, if you have periods like the financial crisis 2008, 2009, there you saw really high dispersion, really bigger difference between winners and losers, and those who underperformed were far more likely to be liquidated.

That number is to some extent affected by market conditions, but 50%, 60% survivorship is very typical, actually.

Cameron Passmore: How persistent do past winners tend to be in the future?

Tim Edwards: This is a very important question for the following reason. When we started producing SPIVA, or when I introduced folks to SPIVA, particularly those who use active funds, some will counter that, well, I really don't care how the average active fund does. I don't care if 70% underperform, because I don't own those funds, and I'm sure there's a lot of dogs out there, and maybe they're high fee, and maybe they're just awful fund managers.

I have a process, and that process should hopefully identify managers who are skilled, who have some sort of a repeatable process that will allow them to outperform. What many market participants do, fund selectors do, is they'll look at trailing performance in order to identify winners. If you believe that skill is persistent, this should work.

The challenge is that the data doesn't confirm the intuition. We do these persistent scorecards. There's lots of ways to skin a cat.

We look at how many funds that outperformed in any given year, repeated that outperformance the next year, or the year after, or three years in a row. Those that were in the top quartile over three years, did they stay in the top quartile over the next three years, or similarly for five years? This is a slightly longer report in terms of the number of different ways that we look at this, because there are lots of different ways that people measure past performance, but the conclusions are near unanimous.

They show you the following. First off, statistically, there is almost no evidence of persistence in performance. A winning fund is just as likely to become a losing fund, as vice versa.

In fact, it's slightly worse than 50-50. There's a slight mean reversion dynamic. We also look at survivorship.

I think it won't surprise you or your listeners to hear that funds that were in the lowest quartile of historical performance were more likely to be liquidated or removed from the sample size than any other quartile. We provide that data as well in order to help people understand what's going on and how an approach of just identifying funds that had a track record would help you navigate the challenge of picking outperforming funds.

Ben Felix: You mentioned that SPIVA exists in a bunch of different markets. I'm curious how the results vary across the countries or regions that you guys look at.

Tim Edwards: They do vary. That's one of the pressures of my team's role is to ask ourselves, okay, check it out. The Chinese market has hosted a large number of outperforming managers.

Why do we think that is? There is much more variability in the short-term numbers than in the long-term numbers because there's all sorts of market dynamics that can affect this. In most markets, most funds underperform most of the time.

That remains true, but there are nuances and there are interesting stories. I'll give you a couple of observations. First off is international small caps is a space where we have seen a pretty decent, a much better record of active funds than other segments.

Part of the reason for that is because, I shouldn't say because, part of the reason maybe because there is really high dispersion in those markets. That means that the impact of fees is relatively smaller and it gets a little bit fairer in that sense. That may be one of the reasons, or it may be that these are relatively under-covered markets.

There are opportunities there that a discipline process can identify. International small caps does tend to be a space where active funds do a little bit better. There are some where it's always zero or 100.

There is a Danish active equity fund market. It's one of these more curious ones where actually it's about understanding the market dynamics. Every year, we tend to report either no active fund outperformed or all of them did.

The reason is a company called Novo Nordisk, which is around or was around half of the Danish cap-weighted benchmark. When Novo Nordisk does well, then no active fund outperforms the benchmark. When it does badly, the opposite occurs.

Sometimes there are little local dynamics that really drive this. For you folks back in history, similar things happened to a less dramatic extreme with BlackBerry back in the day and with Shopify more recently, where it can really be driven by the large names at the top of the benchmark.

Ben Felix: I was thinking Nortel, but Nortel predates, I believe SPIVA. Nortel was like 33% of the index, I think at one point. Just on the international small caps thing, just to add some color to it for listeners.

When you say that active funds do a little bit better in that space, does that mean like we should be buying active funds in that space or does it mean like they're doing a little bit less badly than other markets?

Tim Edwards: That's an important question. I would encourage anybody who would like to go and dig into the actual report themselves. What does a little bit better mean?

For purposes of comparison, you look at US international small cap funds over 10 years, 74% of actively managed funds underperformed the appropriate benchmark. Three quarters behind. As many of your readers may know, in large cap US, the equivalent statistic, it's in 80s or 90s typically, as of the latest report, 86%.

Better, but not such as to change the headlines perhaps.

Cameron Passmore: A common argument, Tim, we've heard for years is sure, indexing makes sense when markets to go up, but what about the bad years in stock markets? Do active funds perform in bad years for the stock market?

Tim Edwards: That's obviously something we've heard as well and it's something we've looked at over time. In every report, we'll also give you a year by year statistic so you can compare them. Summarizing the results of the various analyses we've done, the observation I would make is that there are things that help the outperformance rates and they do include high dispersion, noisy markets, but you don't necessarily want a bear market.

The reason you don't necessarily want a bear market is because in a bear market, correlations tend to be high, so things kind of swim together and the punishment for mistakes can be such as to take you out of gain. If we stick with US large cap where there's the longest history, 2008 is of course a year that stands out in history, 56% underperformance rate. That's better than you might then is common, but the year before 2007, which was a very calm year in practice, was one of the few years where we saw majority outperformance, 45% underperformed.

Statistically, there's not a lot of correlation. What you do find is in really low volatility, low dispersion, high correlation years, the doldrums of 2015, 2016 when the markets are slowly ground up when everyone's just watching the US Federal Reserve. Those are really hard years and the other hard years are those when the market is really driven up by its largest stocks, which tend to be, not always, but tend to be systematically underweighted somewhat by many active funds.

Ben Felix: We've got some questions about market concentration with respect to index funds in a bit. In one of the reports you guys looked at, instead of just individual funds against indices, you looked at multi-asset portfolios, which I thought was really interesting because it's another one of those counter arguments you hear. Well, active might not make sense in isolation relative to the index, but when you combine active funds together in a portfolio, they can perform better.

What portion of hypothetical multi-asset portfolios that you constructed using active funds outperform similarly constructed index benchmarks?

Tim Edwards: Let me first explain why this is not a trivial question. You might think if I'm disadvantaged flipping a coin once, then flipping a coin 100 times did sort of guarantee me a bad outcome, but it's not necessarily as simple as that. The reason is because it could be that one outperforming active fund more than compensates for a load of underperformers.

That certainly doesn't feel from intuition impossible, especially when you think about in the equity markets, if you make a concentrated allocation to something that turns out to be a really successful position, that could compensate for many years of missing out or hitting out on the pot. It was a question that was genuinely worth looking at and worth answering, so we did. Last year, we looked at different allocations, including and excluding different categories.

The central point was we built a typical cap-weighted equity plus fixed income portfolio, looked at different equity fixed income allocations. I'll give you the number for 60-40. What we found was that over 10 years, randomly selected active fund portfolios that ran the 60-40 allocation underperformed with a rate of 97% over 10 years.

The first intuition was correct. Essentially, combining portfolios of active funds reduced the chance of having outperformance and the probability of picking underperformers in several categories outweighed that chance of picking a hero in one of them.

Ben Felix: What if you constrain building those active portfolios to only containing top quartile active funds?

Tim Edwards: Well, that we had an intuition what we would find because of our analysis of persistence, and the intuition there was confirmed, but it was interesting. If you built multi-asset portfolios constructed from active funds and on different equity and fixed income categories, what we found was that you did improve your probability of outperformance. Bear in mind, this is going from 97% underperformance to, I think, 93% underperformance, so you're not changing the story, but you're improving it.

The way that you're improving it is you did have a higher chance of avoiding the very worst funds, and so it was cutting off the left-hand tail of it. One thing that surprised us, perhaps it shouldn't have done, but it did surprise us, but you did seem to end up with a bit more volatility. We found that these building portfolio from top quartile funds increased the portfolio volatility of the results.

We thought about this a lot, that there are a lot of different reasons that this might be true. I don't have a conclusive answer for you because we didn't look at the holdings, but my suspicion is that we were analyzing a 10-year period which was overall a bull market for bonds, a bull market for equities, and I suspect that prior good-performing funds had some sort of a beta effect, especially taking on, say, if you're an investment-grade fund but you're tilting towards more credit exposure, that'll give you better performance, but at the cost of giving a higher correlation to the equity markets, and so a cost on the portfolio diversification. That's my suspicion, but as I say, that's only a suspicion.

Cameron Passmore: What has surprised you in a past SPIVA report?

Tim Edwards: There are always surprises, I think, in every season of these SPIVA scorecards. There are segments and there are periods.

We'll do 15 different kinds of analysis, and we'll come to the conclusion that, you know what, the active community, and I think sometimes there is a community, right? There are themes or strategies which become popular among the active fund community, and sometimes they get them right. I think it's really important that our scorecards share those observations when we find them to help understand where performance was generated from and also explain what might be the risks going forward.

I always find it interesting to dig in that there are always surprises. There are always interesting stories because it's really telling you about how markets are behaving and how the industry is reacting to that behavior.

Ben Felix: You mentioned earlier that you guys did not set out to settle the debate on active versus passive. What impact do you think the SPIVA report has had on the financial services industry and maybe even on academia as well?

Tim Edwards: I think SPIVA has made a difference. I think it has helped inform a debate, and it hasn't just helped investors. It's also helped the industry to think about where time is well spent and what kinds of things need to be done in order to create better outcomes.

I think it also helps set expectations. If you are an underperforming active fund, knowing the context that that year, 87 percent underperformed is helpful to you, right? Maybe you're not a terrible manager.

Maybe the winds were blowing against you. One of the great honors of my position as leading the team that produces these reports is I get to talk to people who read it. I get to talk to people who use it.

Some of the feedback that we've had over the years has been really inspiring for what we do. I've met with founders of firms who one of the reasons they set up their firm was because they came across a SPIVA report written by perhaps one of my predecessors in the role. It was transformational for them.

They said, okay, well, this is information that I can use to help me build a business that services the market in a different way.

Ben Felix: Wow. I don't know if I've ever told you this story, even Cameron, but my first job in financial services was at a place that was selling actively managed mutual funds. I was pretty green.

I was studying finance at the time, but my background was in engineering. I didn't know a ton and I was being fed all this information about active funds and why this manager is going to outperform and all that kind of stuff. A friend of mine gave me a copy of a SPIVA report and was like, you need to read this if you want to stick around this firm.

That was one of the things that got me to educate myself about index investing, which eventually led me to PWL.

Tim Edwards: Thank you for sharing that, Ben, but exactly. That's lovely to hear.

Ben Felix: We just spent a bunch of time talking about why indexing can make sense relative to active funds. We try to be balanced though, but why index funds could have some problems. I want to ask you some questions about that.

There was a recent paper in the Journal of Financial Economics that suggests that when indexes rebalance in response to stock market composition changes, they impose an implicit performance drag. What do you and S&P DJI more generally think about this kind of research?

Tim Edwards: People sometimes talk about something that they call the index effect, right? The index effect, probably more popularly or better associated to the stock market. The idea is an index selects a stock to add to the index or a stock to drop from the index.

Then you see a change in the price of that stock associated either to the announcement or the capital flows that might be associated from people buying or selling that stock as they seek to track the index. First off, the most important thing perhaps for me to acknowledge working for an index provider is this is not something that is unimportant. This is real.

We have policies and procedures at S&P Dow Jones Indices that treat index adds and drops as material non-public information before we announce them because we anticipate that they may well be market moving news. Now here's what also happens. There's a couple of things that are worth bearing in mind here. There are academic studies that will look at this and I would encourage you to check what is the time period that they looked over.

We published, it's 2021 but the numbers haven't changed but there's something that's available for free called What Happened to The Index Effect. And the reason it's called What Happened to The Index Effect is in the mid-90s, if you had advance information about which stock was going to go in or out of the S&P 500, you could have made rather a lot of money. I mean, I think it's an 8% impact from that insight.

2010, so 2011 to 2021, the impact was not zero but almost de minimis. It went from, you know, percents down to figures of the order of a basis point or 0.01 of a percent. Now why did that happen and how did that happen?

And there were a few sort of structural things about how we communicated changes. It used to be the case that, and it's not just S&P in this case, it's true for many other index providers, we would sort of tell people how the index had changed after it had happened. If you were tracking in the index, then you had to scramble because you didn't know what you were supposed to have bought until you bought it.

It now tends to be data is shared on a wide basis before it happens and it gives people time to prepare for it. The other thing is there is money that's tracking the S&P 500 but that is not a secret. Everybody knows that.

And so what you have is market participants who are seeking to harvest that outperformance by identifying, you know, what's going to come in, what's going to go out, and then what do you do if you think something's going to join the S&P 500 and you want to take advantage? Well, you buy that stock and you wait for the announcement. After the announcement, you hope to sell it to someone who is going to buy it but it's joining the index.

And the reason I sort of belabor the mechanics of this is because the mechanism of front-running index changes is identical to the mechanism of providing liquidity to people tracking those indices. I.e., the fact that there are people seeking to own the stock that's going to join the index with the hope of selling it to those people who are going to buy it creates liquidity, creates the mechanism by which that index effect diminishes. And what you have today is essentially an incredibly competitive marketplace of, you know, high-frequency shops, high-frequency market participants, and, you know, more medium-term speculators who are arbitraging out those advantages from kind of having that information in advance.

So it is super important, it's definitely something to watch, but its impact is relatively small in the context of an investment. It's relatively small in the case of even individual stocks. When you think each one of those is perhaps 500 to the index, you only change a handful of them each year, the effect on the overall index is quite small.

But I think it's a super important dynamic because it's not – I would never say, you know, it's not something you don't need to be – as an index provider, certainly it's something we need to be alert to, aware of, and to understand.

Ben Felix: The author of this paper, Marco Salmon, he's been on this podcast. He does have a paper on the disappearing index effect as well. This paper in the Journal of Financial Economics is looking at basically buying into new issue – or well, indices including new issuance and IPOs and then kicking out buybacks.

So this is separate from the index effect is what he's suggesting. I have more questions about IPOs in a second. But the authors, Marco and his co-author in this paper, they suggest rebalancing less frequently and delaying responding to compositional changes to things like buybacks and new issuance and IPOs to reduce the implied cost of that consistent sort of – because they basically argue that buybacks tend to have higher expected returns, issuance and IPOs tend to have lower expected returns and indices are kind of always rebalancing into the lower expected return side of that and out of the higher expected return.

Tim Edwards: One of the things that are broadly true about the indexing world is it's not too difficult to create an index. This is one example of a quote-unquote "strategy" that uses some kind of metric of valuations or historical analysis to say if you did these sorts of things in response to these kinds of corporate behaviors, you might perform a little bit better. And there are many, many such indices and some of them do perform better and some of them have a lot of academic evidence that supports it.

And they may well be a good idea but they don't, in extremis, fully represent the market opportunity set. You could do that and still may well ask the question, did it outperform the market? It would be quite handy to have the S&P 500 there continuing doing what it always did to say, well, was this a good idea or a bad idea?

These sorts of things are useful. They're helpful. Identifying ways that people can take advantage of systemic factors is helpful and useful.

It tends to mean that they diminish after publication. I encourage it. But I think you have to be careful on anything that fundamentally changes the design or the purpose of an index.

Ben Felix: There's lots of stuff you can do that looks good in a backtest and some of them may have great theoretical support. But at the end of the day, doing that thing is no longer representative of the market, which is kind of the point of an index. On the topic of indices including recent IPOs, something that I've been hearing from people in our podcast community who are dedicated index investors, I've been hearing that they're concerned about the inclusion of some of these big potential IPOs that are on the horizon.

There's a few private companies that are just massive in terms of their market cap that are potentially going public in the near term, which for the reasons that we just talked about, some investors are concerned about having these things shoved into their indices and therefore index funds. How does S&P DJI handle the inclusion of recent IPO shares in its indices?

Tim Edwards: Well, first is what do we do right now? Once you've heard that answer, might that change at any point in the future? Because certainly this is something that the market is thinking about right now.

We do monitor private companies as well as public companies. And if you took the 10 largest venture backed US companies, including the names you mentioned, Databricks, SpaceX, and so on, based on data in early March, if they joined the S&P 500, assuming a full IPO of all their stock, so the entire market capitalization, they'd be big. They'd be around 4.5% of the S&P 500. That is more than the weight of the energy sector. Although on balance, it's considerably less than that of Microsoft. And so quite naturally, people have been asking us, people have been asking themselves, should they come into the index?

First, the rules of the S&P 500 are public information. There's an amount of discretion involved in parts of it, but there are some hard rules. And one of the hard rules is a so-called "seasoning" for IPOs.

And that requires that any newly listed company must be trading for 12 months before it's considered for inclusion in the S&P 500. That's for the S&P 500. There are other indices, total market indices, for example, where IPOs can join the index faster.

I'd say additionally for the S&P 500, you need at least 10% of the shares of the float available in public. There are liquidity conditions, and there are also financial viability conditions. This is not a new thing for the S&P 500.

And really, the sentiment there is to ensure that it's replicable, because sometimes there are conditions around IPOs, around how much founders are required or early holders are required to keep hold of. So it needs to be replicable. You need the shares actually out there so people can get hold of them.

And to some extent, it is to manage a known problem where you can get IPOs with very elevated valuations that are short-lived and somewhat driven more by market dynamics. So as of today, if those companies did IPO, the rules require at least a 12-month period before they can join the S&P 500. However, rules can and do change, and there is a degree of transparency on that too.

This is such a significant change that I would expect it to be subject to public consultation, which is when we make an announcement on our website, we'll state what the current rules are, we'll state what the new rules are going to be, and then we will hear from the market as to what they think is the best way for that index to continue to represent the market that it's supposed to represent, which is, you know, the US equity market.

So it could change, never say never, but those are the current rules. And I think the history and the holistic approach to those rules is there because that has been long the view that that is the best way to continue to kind of track the market and to give IPOs a bit of time to get out there, get trading, be liquid, be available before they join popular indices like the S&P 500.

Ben Felix: Just to make sure I understand on this one, you have not suggested that the S&P 500 is going to change its methodology, which would be non-public information. Are we saying that it could potentially make sense for an index like the S&P 500 to change its methodology because the market has changed? So for example, because these IPOs are just much larger companies than IPOs have typically been in the past, if the goal of the index is to represent the market, well, hey, maybe it's time to change methodology a little bit.

Is that kind of the thinking?

Tim Edwards: I want it to be as definitive as possible. I want to see, you know, those are the rules, right? But also the rules do change and there's been a lot of discussion, not all of it anti, you know, the potential public listing in these companies, the fact that they will almost immediately have the potential to be significant parts of the US public markets.

And should indices include them to reflect that? I think the important component there is, you know, for an index provider is to continue to represent the needs of a broad marketplace. Everyone from people using the index as a benchmark, those who are potentially using your trading vehicles, those are using it as research components and those who are using it for index funds.

And that's the process that we have.

Cameron Passmore: When might an index provider delay inclusion?

Tim Edwards: There are a few reasons why a new IPO might be excluded from inclusion in an index.

I mean, we've talked about some of them. S&P 500 has a seasoning requirement. Some indices, including the S&P 500, also have a fairly simple profitability filter.

At the point that you join the S&P 500, you need to be boasting a profit in the most recent quarter and over the last year. And so, you know, several companies have become large before they joined the S&P 500 because they were not able to boast a profit. One in recent memory for many listers was Tesla, which joined when it was a very large, it was one of the largest ever joiners to the S&P 500 in terms of the weight that it joined at, because it had not reported a profit.

Ben Felix: Tangential, but the Tesla has underperformed the index since its inclusion in the index.

Tim Edwards: Yes, it has. Although, since joining, there have been periods when it's outperformed and periods when it's underperformed. Compared to most stocks, it's a relatively volatile performer.

And so, yeah, that story does depend on the time period that you look at.

Ben Felix: True today, but maybe not when this episode is released. We'll see. You did mention this a little bit, but what effect could the inclusion of some of these big, massive upcoming IPOs have on composition of indices?

Tim Edwards: They are certainly some large companies.

Ben Felix: What would you say to people who are concerned about the potential inclusion of these large IPOs in their index funds?

Tim Edwards: If we see some of the IPOs that the market is anticipating, it is important. And we already mentioned, you know, top 10 collectively four and a half percent weight in the S&P 500. It'll also change the opportunity set potentially in spaces like artificial intelligence or space exploration that are segments where people are very keen to get exposure or to manage risk.

In terms of the S&P range of indices, as I mentioned, at present, the S&P 500 doesn't allow for new IPOs to come in straight away. The large amount of media coverage around it would suggest that if that even has the potential of changing, the formal potential of changing, that you might hope to be alerted to it. On the flip side, there are other indices out there, including total market indices, that will look to include them earlier.

To that extent, there is something about choice aspects, but the S&P 500, as of its current rule set, will not include them until they've had that seasoning period.

Ben Felix: Interesting times for index funds, for sure. Now, potentially related or not, and then you can give commentary on that, lack of a relationship, if you like. How does the current US market concentration in the top stocks compare to US market history?

Tim Edwards: Yeah. We're speaking in almost the end of first quarter in 2026. There has been something of a reversal.

It's a bit early to say, but this is really structurally a reversal. But if you zoom out from around 2015 or so, you can go a bit earlier if you pick the right stocks, but about 2015 or so, we have seen a trend for increasing concentration in the US equity market. And that increasing concentration has occurred because many of the companies that were already among the largest outperformed considerably and grew to represent a larger and larger stake.

There are lots of different ways that you can measure this. A simple one is to look at what are the top 10 weights. By the end of 2025, we were reporting close to 40% weight in just the top 10 stocks.

That is not quite unprecedented. There was an occasion around 60 years ago, go back to 1965, there were 10 stocks that also made up around 40% of the index. And that gave us, I think, the perfect excuse to look at what happened last time and ask ourselves the question, could something similar happen again?

We published that as a short research paper, In the Shadows of Giants, essentially investigating the dynamics of individual companies, but also overall concentration and broad market performance.

Cameron Passmore: And what has historically come of the top 10 largest companies in the S&P 500 following these periods of market concentration?

Tim Edwards: It's somewhat humbling to look at what happened to the prior top 10. It's also somewhat complicated to analyze it. What we did is we identified those top 10, one of which was AT&T.

The subsequent spinoffs and recombinations, we had something that ended up looking rather like an electronic wiring diagram just to track what would have happened if you started off with a position in AT&T. Overall, it was something of a sad story. Among the top 10, you had Eastman Kodak, which famously went bankrupt.

Sears and Roebuck famously went bankrupt. Companies like General Motors, some survivors, Standard Oil of New Jersey, which is nowadays known as Exxon, IBM, which is still a member of the S&P 500. But overall, the collective weight, which began at 40% declined almost in a straight line down.

So those individual companies, the prior leaders, which once were widely viewed as perfect examples of US corporate strength, they all did really badly. But the overall market performance was not entirely bothered. I suspect many of our listeners will know that the period in US equities from 1965 to today is not a disappointing one.

That shows you what can happen to the overall market and to its largest companies. It's connected in the short term, but in the long term, it's a really different story.

Ben Felix: Can you give more color to that idea? Why is it possible for those top 10 firms to have, in many cases, disastrous outcomes while the index as a whole has an incredible period of performance?

Tim Edwards: It's connected to notions of things like creative destruction. And it's by allowing companies to fail that the index survives, essentially. But what can happen is concentration can change in different ways, right?

Or you can think of it in two different ways. You can have concentration decreasing because the largest companies do badly. But you can also have concentration decreasing because the other 490, more importantly, some others among the 490 do well.

And so it's that changing of a guard mechanic. And one of the interesting things we kind of found in our research, and this may not necessarily be representative, but that entire 60-year period represented more or less one changing of the guard. The previous top 10 declined gradually over 60 years.

The current top 10 started appearing in the index various points through the season and then came and took up larger and larger components and larger and larger shares themselves of the index. And it's that dynamic of it doesn't have to be so important if one company does badly if the other 490 do well. And within that 490, there are perhaps one or some that represent the next generation of giants and the returns that they will generate if they go from, say, typical on average, you have 500 stocks, the average weight is 0.2 of a percent. If they go from 0.2 to 2%, that kind of tells you they've done 10 times better than the overall market, ignoring all the other effects that you'll get in there, like dividends and rebalancing and so on. So it's that dynamic of creative destruction and the emergence of new cohorts that really comes through in history and is obviously, you know, past is no guide to the future and so on. But I suspect may be informative in terms of understanding what risks or what opportunities there may be in the higher concentration that we've been seeing today.

Cameron Passmore: So just to put a finer point on this, generally speaking, what is the historical relationship between the S&P 500 concentration and returns?

Tim Edwards: Two things I'd highlight. First of all, there's not really a strong relationship between concentration and returns. There is a mildly positive one. Generally speaking, in bull markets, they're often driven up by companies that, you know, go into the lead and really pull out the lead.

But if you go, if you zoom out a little bit, you go decade by decade over that six-decade period, most of the decades had positive equity markets and it was a coin flip where the concentration increased or decreased in any 10-year period. There is something I would add to that though. Sorry, just to emphasize a bit.

Mildly positive association with concentration market performance, but really driven by a few periods of increasing concentration and strong equity performance, late 1990s, past couple of years. But, you know, correlation does not mean mildly positives. Correlation does not mean, you know, that it's explained everything.

But there is something else which I would encourage as a useful way to think about things or think about managing concentration risk, which is if you look at the relative performance of an equal weight index and a cap weight index, that almost precisely tracks changes in concentration. If you had a view on concentration, the way to express that on a relative basis might quite purely be on a, you know, how a capitalization weighted doing versus equal weighted indices doing. There the dynamics are, the correlation is extremely high, right?

Which is very intuitive.

Ben Felix: Just on the idea of current big companies declining and some other companies in the index eventually picking up the slack, how many of the biggest companies today were even in the index last time it was at its current levels of concentration back in the 1960s?

Tim Edwards: We did look at this and the answer is none of them. None of the top 10 were in the index in 1965. Actually, I should say top 10 does change.

This was when we published the research. I was looking just before we came on air and I saw that there has been a changing of the guard again in terms of the top 10. JP Morgan, which was there in the top 10 when we published, has been replaced by Walmart as of, you know, time of recording, which is unfortunate because JP Morgan is actually the earliest one or JP Morgan's predecessors.

When we did this research, we sort of would ask, okay, well, what about Chase Bank and JP Morgan prior to their combination? That one was in the longest 52 years in the S&P 500 up to the time that we published. But what might be surprising is although the names, you know, NVIDIA, Amazon, Apple, Meta, Alphabet, Microsoft, Tesla, they sound like new companies.

The average tenure was 24 years and Microsoft joined in 1994. It's been a big company for a long time. None were in at the start of the period, but over the period, they started to come in and on average, they came in at a much smaller weight as you might expect than on average had been there for a quarter century by the time they came to represent the top member of the top 10.

Cameron Passmore: Now, what would you say are the main lessons from history about market concentration for the index investors listening today?

Tim Edwards: I think there's a deep and important question. Is high concentration, I should say relatively high concentration. It's not that high compared to some other markets around the world, but compared to the US equity markets history, it's relatively more concentrated than it's been for a while. And that leads to really good questions around is capitalization weighting still appropriate for benchmarking?

Is this a risk? Is this something that people should be thinking about, should be managing? And I think these are all good questions.

I think history can be informative and useful and give you a sense of what kind of things may happen. And I think the message that comes, I would emphasize is that those companies can do, I'm not saying they will, but the entire market is not reliant on them for its future. It is just as likely to be reliant on the next cohort who may already be in the index today.

And if the current top 10 leaders, if they do poorly, what will happen is their weights will decrease as they do. And if competitors come to dethrone them, that'll be because they have outperformed and they have taken an increasing weight in the index. And it's this process of evolving with the market that means that capitalization weighted benchmarks are unlikely to go away anytime in the future.

And they are not necessarily over-reliant on just a few names at the top.

Ben Felix: How do you and S&P DJI think about the potential for continued index fund adoption to adversely affect the way that financial markets function? I've alluded to this when we started talking about this general idea of market concentration, but one of the things I'm getting at there is something that I know you've heard, which is that, hey, maybe index funds are actually the cause of market concentration. Anyway, how do you guys think about that?

Tim Edwards: I think it's interesting. One thing to acknowledge is that people have been worrying about the adoption of index funds for 50 years. The concept is not one that hasn't been tested.

We've been through bull markets and bear markets. We've been through high inflation, low inflation, high rates and low rates, market crises of all different stripes and flavors. What tends to happen, not always, but what tends to happen is in periods of disruption, in periods of dislocation, in periods of crisis, folks realize the, or folks have realized, I shouldn't make this predictive, but folks have historically seen a real liquidity and transparency advantage from index funds during periods.

And then subsequently, not always, but we've tended to see more people see the clear advantage of an index based approach after periods of stress. So I think the question of how index funds affect markets and index based products affects market is a really important one. There's all sorts of different topics we might discuss, but let's not forget the benefits.

Compared to the average actively managed mutual fund, index funds based on S&P's main US indices are currently saving investors something like $50 billion a year in fees. And the SPIVA scorecards illustrate that the outcomes that these investors are getting are likely, not necessarily, but are likely to be better on a poster fee basis to be a better outcome than it would have been if they bought actively managed mutual funds. And I think there's a point there that market participants, you know, higher frequency, lower frequency investors have overall, there's plenty of evidence to say continued index fund adoption has been largely to the benefit of an awful lot of people.

So it's important to ask and test and examine what else might happen, but let's not forget that the large amount of evidence, this has been benefiting a lot of individual people and investors.

Cameron Passmore: The S&P 500 recently declined at the time of this recording. Historically, have investors benefited from waiting for a further drop in the S&P 500 before entering the market?

Tim Edwards: So first of all, I love this question. This is sort of fun question that an index nerd like me, just roll your sleeves up. You've got, you know, more than a century of history in the Dow.

You've got back to 1957 and the S&P 500. So what a fun question. Let's ask ourselves.

And I should say, this is actually something that I looked at a year ago. It's a bit anecdotal, but someone in the office was saying we were in a similar position heading up to the Liberation Day tariffs. The market was down a bit, but not a lot.

And someone said, yeah, I'm thinking of making a personal trade and buying the market, but I'm going to wait until there's a bear market. I'm going to wait until it's 20% down because I like to go shopping and when the sale's on. And I thought, well, yeah, okay, but you might not get that opportunity.

I ran the analysis, looked at various different points. If you are at an all time high, how long did you wait for a bear market? If you're two, five, 10% down, how long did you wait on average before got a, you know, 20% drawdown?

And then importantly, what happened on average while you waited? Because what may happen, it's not guaranteed, of course, but what may happen is it's 19% down. You think I'm just going to wait until I hit 20% down and then I'm going to buy.

What might happen is it doesn't do another 20% drawdown for three years or more, by which time it's risen so much that your entry point is actually much higher than where you started. So here are the results. If you say, I'm going to wait for a 20% drawdown on average, you wait three years.

The median time is two and a bit years. If you wait until you're, you know, 5% down or 10% down, you're still disadvantaged. Essentially, the notion of waiting for a bigger discount, what the historical data in the S&P 500 shows you is not actually a good idea to wait.

Timing of the market is hard. And by the way, the reason this is true, I've sort of hinted at it. The reason you get these terrible numbers on an average, because a lot of the time, if you say, well, I'm just going to wait for it to fall a bit more and then I'll buy some, a lot, most of the time, that's a profitable decision.

Most of the time, the market falls a bit more. Some of the time, it goes up from there and it goes up an awful, awful lot before you've got another chance for a sale to be on. And it's missing out over a super long period while you're waiting for the perfect opportunity that drives that average down and suggests that doing such things, or at least doing such things in such a simple way and historically appears to be disadvantaged.

Ben Felix: I love that. We've nerded out on similar analysis in the past using a bunch of different indices and it's pretty much the same everywhere you look. Because basically stock returns have been positive in a lot of places.

Tim Edwards: Right. As the expression goes, timing the market is hard. Time in the market is quite easy.

Ben Felix: Yeah, that's right. All right, Tim, we have two more questions for you. I don't know if you're going to be able to answer at least one of these questions, so we'll see.

If you had to pick one, what is your favorite S&P DJI index and why?

Tim Edwards: Obviously, we have an awful lot of indices and I love all my children equally. There are a few that are really, truly iconic, right? S&P 500, the Dow.

When I was getting into markets, I was always a fan of VIX as this sort of fear gauge. It was just giving me different kinds of information. And I think there's a lot of information out there.

If I pick a personal favorite, a couple of years ago, we started writing on the concept of dispersion and measuring how much dispersion, how differently stocks were performing in the context of helping write our SPIVA scorecards. But we actually had a conceptual idea and worked with Cboe, who uses options to calculate VIX. We actually worked with them to develop something that used the price of individual S&P 500 stock options as compared to index options to get this measure of implied dispersion.

It's not a very well-known index, but for selfish reasons, because we did a lot of research on dispersion and we had this notion, we could actually build implied dispersion, kind of a forward-looking measure, how differently the market expects stocks to perform. So that launched in 2023. It's DSPX, the dispersion index.

It's a very sophisticated index. I will admit to a soft spot for it because it's something that I had a little role in helping create. And I think it's super interesting that you can read out from the options market.

It's not predicting the future, but it's telling you about the price of insurance. And I think that's often super interesting in summarizing an awful lot of data in one data point that tells you about sentiment and where we are.

Cameron Passmore: Well, you answered that one, Tim. Let's take a crack at the last one here. How do you define success in your life?

Tim Edwards: There's a lot to be said for happiness, and that can sound a little complacent. You know, I want to be happy. I'm successful if I'm happy.

But what makes me happy includes a lot of different things, some of which are about ambition, some of which are not lazy, some of which are aspirational, some of which are about the people around me and my family. But the question I ask myself more often is not do I feel successful, but do I feel happy? And I think happiness is not a terrible goal.

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