Can Active Managers Beat the Market? Anu Ganti of S&P Dow Jones Breaks Down the Data (EP.250)

0:02The Long Term Investor:We all need to make smart decisions with our money. The Long Term Investor podcast shows you how by distilling complex financial matters into easily digestible lessons. And now here's your host, chief investment officer at PlanCorp and the author of Making Money Simple, Peter Lazaroff. Welcome back to The Long Term Investor. This week, I'm joined by Anu Ganti, head of U.S. index investment strategy at S &P Dow Jones indices on the very day that the latest S &P active versus index scorecard was released. So we're going to get into those headline numbers from that report, but we're also going to go beyond the numbers to explore why beating the market remains so difficult and why finding managers who are able to beat the market in a given year is getting even harder and really what investors should understand before choosing any index-based fund.

0:55The Long Term Investor:As a reminder, I have a new book coming out in the fall called The Perfect Portfolio, and you can sign up for updates at theperfectportfoliobook.com. There is also a link at the top of the episode description. People who get on that list get early excerpts, previews of chapters, and invites to subscriber-only webinars. The next one is actually just coming up in a few weeks, so be sure to go to theperfectportfoliobook.com or click the link at the top of the episode description. And now here's my conversation with Anu Ganti.

1:28The Long Term Investor:Welcome back to the Long-Term Investor. Today, I'm excited to be joined by Anu Ganti, head of US Index Investment Strategy for S &P Dow Jones Indices. Anu, thank you so much for joining me here today.

1:41Anu Ganti:Thank you, Peter. It's so nice to be here.

1:43The Long Term Investor:We have talked about having this conversation for a while, and we could not have timed it better because today the SPIVA or the S &P Index vs. Active Scorecard is out to the public. So let's start there. What did the SPIVA U.S. scorecard tell us?

1:59Anu Ganti:We're very excited about SPIVA for a couple of reasons. One is we now have 25 years of annual history. So it's been so interesting to watch the evolution of this franchise over the past couple of decades. And first, just a little bit of background for you. SPIVA stands for S &P Indices Versus Active, and we've been producing it for a long time now. It started in the U.S. and it's expanded to Europe as well as now Asia. So we do it all around the world, which is pretty fascinating. Now, getting into the basics of what SPIVA shows you is we measure active manager performance versus the appropriate benchmarks.

2:43Anu Ganti:And we started doing it with equities and then we expanded it to fixed income. We also have international categories. The most important number that I would call out is the underperformance rate, particularly for our large cap equity funds versus the S &P 500. Having said that, there's a whole host of metrics to dive into, including, for example, asset-weighted average performance, equal-weighted average performance. We've got survivorship where we account for the entire opportunity set, as well as quartile breakpoints. So there's a lot of statistics in here to digest. But coming back to the question, which is how did the numbers look last year?

3:29Anu Ganti:It was very interesting. We saw that 79 % of large cap managers underperformed the S &P 500. So that's the headline number for you. It was also a very interesting year because, of course, if we think back to early April of last year in the tariff-related tumult, we were closely approaching bear market territory. And then we saw the significant rebound of the benchmark and the S &P 500 and technology. So in this kind of environment, and we're in a similar environment right now, where there's that crater of volatility, market declines, this is typically when we hear that it's a stock picker's market, right?

4:13Anu Ganti:And active managers have the potential to shine. So for us, it was a bit surprising to see the 79 percent. It was also for context, it was the fourth worst year in our 25 year history. It was the worst underperformance since 2021. So relatively bleak results from that context, just given the tailwinds that we saw last year.

4:39The Long Term Investor:That's really interesting. And you mentioned, you know, this is a data heavy report. But one of the things that I think you and your team have done a really nice job of is making it so accessible. And so I'll be sure to link to this report in the show notes at the long term investor dot com. And the exhibits, the way that the data structure just it. I don't think you have to be a financial expert to understand what you're looking at. And you mentioned, OK, the numbers that just came out, we know that 79 percent of large cap domestic equity funds underperform the S &P 500. And you mentioned in what people would have called a stock picker's market.

5:14The Long Term Investor:And you and I have joked before, I feel like we always hear that it's a stock picker's market. But can you kind of walk us through the history of some of the data and how you've seen changes over time, as well as maybe how things have not changed?

5:27Anu Ganti:Sure. It's an excellent question. And one of the points that I like to talk about is when we show the underperformance rate, we show it over a one-year period all the way out to 20 years. And if you look at the 20-year numbers, they're very stable. And there's a lot of noise in the short term. Markets change, there's declines, there's gains. But over the long term, once you get out to the 10-year, 15-year, 20-year mark, that's where things get really tough. And we roughly see more than 90 % of managers underperform the benchmark, which is an important point that really shows the challenges of beating the index and the benefits that indices offer.

6:10Anu Ganti:But I will say it was an unusual year for a couple of reasons. One is we had that higher dispersion or cross-sectional volatility. So when you think about conditions for active, we tend to think, you know, if it's a stock picker's market, if I had a crystal ball, what would I wish for? What kind of conditions would I want? And one of them would be that greater dispersion, that greater cross-sectional volatility. Because if I have the skill as a stock picker and I make the right call, there's greater value at, greater bang for your buck. And we did see that last year. We did see that higher dispersion, but we especially saw it in May of last year, post the tariff-related tumult, as the market was assessing what would be the winners of tariff-related policies, what would be the losers of tariff-related policies.

7:02Anu Ganti:So that was a really opportune time. The other element and measure that we look at is just the percentage of stocks that are beating the S &P 500. And that number was 62 % in Q1. So pretty good circumstances. Then it subsequently went down for the year. It was only 30 percent of stocks that beat the S &P 500. So still tougher times. Another potential tailwind, and I know, you know, I'm sure you've seen this as well, is just the talk of big tech, the mag seven market concentration, which which can be a headwind for more concentrated managers. And there's so many different ways to measure this. A simple way that we looked at is we just took the top five stocks in the S &P 500 and we looked at their contribution.

7:51Anu Ganti:And that contribution went roughly steadily down from Q1 to Q4, which may have been a potential tailwind for the managers that are underweight these big stocks. Now, having said that, there's another element, which is we looked at our equal weight index. And I like to look at that because that's a measure of just the average stock, right? How's the average stock doing? And we saw that that equal weight actually outperformed in Q1, and then it subsequently underperformed, although it did pick up a little bit in the latter part of the year as we saw smaller caps turn around, more domestically sensitive stocks do better.

8:31Anu Ganti:But what I like to say, it was sort of a too little, too late moment in this scenario. So you had this mixture, this amalgamation of some tailwinds, some headwinds. But overall, it was a tougher year.

8:45The Long Term Investor:That's really fascinating. And as I think and looking even at the exhibits of the year to year underperformance of both U.S. and international funds, you know, it kind of gets me thinking back, oh, I remember when this happened. Maybe that's why the number moved or maybe that's why the number jumped or fell. But then I scroll down and I look at, and you referenced this already, like the 20-year data. Or if you look at the three-year data or the five-year or 10-year data, and generally what you're going to see, and I'm generalizing here a bit. Well, here, why don't I read some numbers? So I see of all domestic funds, the three-year percentage of managers underperforming is 80.4%.

9:21The Long Term Investor:The five-year is 91.47%. The 10-year, the 15-year, the 20-year, they're all over 90%. So I guess, Anu, let me ask you this. Why do so many managers fail to beat the index over the long term?

9:36Anu Ganti:You know, that is the big question, right, Peter, when we look at the SPIVA scorecard. And I'll give you a few reasons to set the stage, because we have identified that this is tough, right? Beating the benchmark is tough business. So a few key reasons. Number one, I think, is cost, right? Because we show the net of fees under performance rates and index funds have generally had an advantage over the cost front. And at S &P, we actually estimate the cost, the fee savings that index investors have achieved. It was roughly$52 billion last year. And what we do is we take the indexed assets associated with the S &P 500, the S &P 400, and the S &P 600.

10:21Anu Ganti:So you've got large, mid and small caps. And we multiply that by the fee differential between active versus passive funds. So you get to that number, but I will say it actually understates the full amount of cost savings because we're only looking at a few of our indices. We're not looking at everything. We're not looking at the entire industry. So that is a really powerful benefit of index-based investing. The other element, and I think this is a really underappreciated element, is just the skewness of equity returns. And I think if you think back to, I don't know, high school statistics class or math class, right, and remember the bell curve, the normal distribution, stocks don't work like that, unfortunately.

11:06Anu Ganti:A stock can go down to zero, but it can appreciate by much more than that. As a result, what we tend to see, and there's been a lot of research on this side, is that equity markets tend to be positively skewed. And we talk about this, and then the next question is, so what? The important rationale from that perspective is that outperformance tends to come from a few stocks, a few winners. So if you're a more concentrated manager holding fewer stocks, you might be less likely to hold one of those precious few winners. So it really makes the case for diversification, just having more stocks, a chance of owning those likely winners.

11:48Anu Ganti:So that's an important point. And in fact, we've looked at the skewness in U.S. equity markets. We look at it all around the world. It's pretty fascinating that for most of these years, most of these equity markets have been positively skewed. The final point that I'll say on this front is just the professionalization of the industry. So I think if you and I were talking, say, in the early 1970s, things would have been very different. And we saw the market become more professionalized, more institutionalized, which has just made things more competitive, if you think about it. Because as you have these assets going to passive, it's sort of a weeding out process, right?

12:34Anu Ganti:And then you have the average ability of the survivors going up. And people are smarter. We have access to more technologies. So the game has just gotten harder. And one of my favorite words to use, I don't think it's officially in the dictionary yet, but I think we'll get it there. It's called Indecise. And basically it means to put it into passive form strategies that say 50 years ago, you would have had to go for in an active format, but now you have the passive option available. So those are a few of the reasons.

13:07The Long Term Investor:I think to me, that is one of the most, those reasons make perfect sense to me. They're probably the most important part of this study to me personally, in terms of trying to coach investors to minimize mistakes. I think a lot of investing success is about minimizing mistakes and just stay in the heck out of the way of compound interest way, like let compound interest do its thing. And you mentioned cost. That seems like such a pervasive one. You mentioned the competition. I mean, when you are thinking about who is out there in the market setting prices and the amount of PhDs and Bloomberg terminals and incentives to go try to find an undervalued security or an overvalued security, it just if there's something that's obvious out there, it just gets competed away so quickly.

13:55The Long Term Investor:But there's one thing that you said that started getting me onto Google so I could find the stat real quickly. You mentioned, you know, you have to a small percentage of stocks drive all the returns. And there's a paper by Hendrik Bessenbender, Do Stocks Outperform Treasury Bills is what it's called. And so he looked at U.S. common stocks from 1926 through 2016. Not only did he find the median stock generated a return of negative 3.66%, but he found that only 90 companies, just 90 out of the 25 ,967 companies generated half of the return. So it's 0.33%. So I think if you're an individual investor out there, you're and you're trying to do this yourself.

14:37The Long Term Investor:I mean, look, to me, the data says that if the pros can't do it, why could you? Another thing is, if you think the pros can do it, you just have to wonder, like, how are they? How could so many people possibly be adding value at this stage? Now, I guess let me ask a question that maybe I know what your answer will be. But, you know, there are people who do beat the benchmark. I sometimes hear people say, well, then why not just invest in those managers who beat the benchmark? What would you say to that?

15:05Anu Ganti:Yes. And I love this question. It's a very common one that we get. And we're certainly not saying that there's no outperformers. They're out there, right? They're certainly outperformers. But what SPIVA tells us is that beating the market is difficult, right? And I think what our persistence scorecards do, and it takes it one step further, is it tells us that identifying those winners, those winning managers, is really tough as well. Because, for example, if you have an outperforming manager, say, this year or last year, chances are next year or in five years or 10 years. is the outperformer going to be that same manager?

15:48Anu Ganti:Our persistence scorecard actually shows that it could change, that what happens is you have these top performers, but that the outperformance tends to be fleeting, right? And I think that's a really important point. And what that actually tells us is that active outperformance, when it occurs, it tends to be more the result of luck rather than skill. Because, you know, if I'm a manager and I have the skill and I outperformed last year, chances are I'm going to outperform next year and the year after that and the year after that. So going back to that point about picking the outperformers, they're out there.

16:28Anu Ganti:It's just they're really hard to find. And manager selection is so tough as well.

16:35The Long Term Investor:Well, you need a lot of data points to assess whether outperformance was the result of skill or luck. And what I'm going to say can be debated and disputed. But if you were like only using annual data points, you would need almost 40 years worth of data to assess whether the outperformance was due to skill or luck. Now, if you use monthly data, I realized the number is different. And there's maybe some things you could do at the margins. But you mentioned the persistence score card. I believe there's an update to that coming out in a few months. But if I just look at the year end one that goes through 2024, I can see that only 2 % of all large cap equity funds remained in the top half over a five-year period.

17:16The Long Term Investor:Meaning if they're in the top half, only just a few of them survived in the top half the next five years. And so it goes to show you, and the thing that's great about the persistence scorecard, and I'll link to that too in the show notes at thelongterminvestor.com, is you'll look at, hey, how did people in the top quartile do over the last three years, and then how they do over the next three years. And then you also do that for the five-year periods. I know that those numbers are coming out sometime in the next few months, but can you maybe, I kind of spoiled one of the results, but do you have off the top of your head a memory of what some of those results showed in the prior year's report?

17:51Anu Ganti:Yes. And you alluded to some of those important findings from the persistence scorecard. And we do this once a year, like I said. It's sort of the sister scorecard to SPIVA and takes it a step further in terms of looking at persistence relative to peers within a fund category, as well as persistence of alpha. How consistently are you beating the benchmark? And the report's findings show exactly what you said. And you mentioned the 2 % stat for large cap funds, only 2 % staying in the top half over a five-year period. And to put it into perspective, if you think about flipping a coin, right, and just flipping a coin and having that random distribution over a five-year period, it was actually less than the chances that you would have flipping a coin, which I think really puts it into context onto how difficult manager selection is.

18:45Anu Ganti:A couple of other points for you on persistence is we slice and dice it a lot of different ways. So we look at funds in the top quartile, in the top half. We look over a three-year period. We look over a five-year period. We have transition matrices showing the evolution over the quartiles and the halves. We also show the persistence in the rankings over consecutive three - and five-year periods. And no matter how you slice and dice it, the end result is very consistent, as we've talked about from year to year. And another finding for you, if you just look at funds within the top quartile, none of them were able to stay in the top quartile over a five-year period.

19:29Anu Ganti:So really powerful findings here. I will add one more point is we actually see persistence on the other end of the spectrum. And what I mean is if you look at the bottom performing quartiles, for example, we see increased likelihood of them getting merged or liquidated in the subsequent three years, in the subsequent five years, which intuitively makes sense, right? Because if you're consistently an underperformer, it's going to be harder to perform and stay in business.

19:59The Long Term Investor:You've already referenced this, that if we're going to take the SPIVA and the persistence scorecard and put them together, a big takeaway is that, hey, it's really hard to beat the market. I mean, what other actionable insights when you publish this are you hoping that people glean?

20:17Anu Ganti:Excellent question. And I think there's a few things here. And we like to think of the SPIVA scorecard and persistence as tools, as tools for education, as tools for the market and for investors. Because, for example, if you look at the SPIVA U.S. scorecard, there's 38 categories in there. And we've talked a lot about large caps, but you can look at large caps versus mid and small caps. Mid and small caps did relatively better. You can look at value versus growth. We can look at international funds. We can look at all the fixed income categories and look at survivorship, for example. So we like to think of it as a tool for the market to understand which categories are doing better, which categories are doing worse, for example.

21:06Anu Ganti:And we offer that transparency with SPIVA because, for example, in years that were relatively better. For example, we call out the numbers and we continue to keep reporting the numbers, which has been so great to see over the past couple of decades.

21:24The Long Term Investor:I'm going to kind of take a turn to some maybe trickier, more abstract topics here. There is something I have a book coming out in September. It's called The Perfect Portfolio. And this is my second book. And both in the first book and this book, I reference the SPIVA results. I referenced the persistence scorecard. I think they make a really important point. When I started my career in 2007, it was a big debate. Like active versus passive was a debate that didn't seem settled. And S &P offered a scorecard of sorts, a scoreboard. I mean, I guess you do call it a scorecard. One of the things, though, that I think has been interesting since then is kind of thinking, is active versus passive the right debate?

22:06The Long Term Investor:And so let me kind of share some thoughts and then you can react. Because to me, it's a lot more about like, hey, was it low cost or high cost? Was it something that required predicting the future versus was it rules based? And so, for example, you can have a factor fund that is not passive in the sense that it's not an index, but it also isn't active in the sense that it's a traditional stock picking fund. So how do you think about that? You know, I don't know exactly what the question is, if I'm being honest. is I think that active versus passive is the wrong conversation. What are your thoughts on that?

22:40Anu Ganti:Yes, you're certainly seeing that blurring of the lines. If you sort of think of an imaginary Venn diagram, for example, with active on the one side and passive on the other. And what you asked and what you alluded to sort of reminds me of another piece of research that we've produced. It's called the liquidity landscape. And what we do is we track all the trading volumes tied to all the products tied to our indices. And there are some really fascinating findings in there. And one of them is that we're increasingly seeing greater trading, greater active usage of passive index-based products. And it's sort of an initial misnomer if you think about, you know, indexing.