Discover more from The Founder Thesis Podcast | Learn from disruptive founders
A masterclass on indexes | Morningstar
Even if you don’t follow finance news, you would have surely heard of Sensex - which is basically an index representing the Indian Equity market.
An Index is basically a basket of stocks picked with some science behind it which represents a view on something. For example, you can follow the small-cap index to get a view of how small-cap companies are performing in the stock market.
This episode of the Founder Thesis podcast is a masterclass in the business of indexes.
Morningstar is a renowned financial services firm that provides investment research, data, and analysis to help people and institutions in making informed decisions about stocks, mutual funds, and other investment opportunities.
Sanjay Arya is an Indian-born American who established the Index business at Morningstar. With his extensive expertise in financial services, he plays a pivotal role in shaping Morningstar's success.
In our conversation, Sanjay talks about why indexes are a big business, how they have evolved over the years and what is on the horizon.
Other Ways to Listen:
Read the text version of the episode below:-
Sanjay: My name is Sanjay Arya. I lead the innovation team at Morningstar Indexes.
I sat down with our CEO at that time, Joe who is the founder of the company. I had a one-page business plan, we had a 20-minute conversation and at the end of the conversation he said, " let's do it but be scrappy".
I was obviously excited and elated about the whole thing but I did not capture what the scrappy means. Later on I understood, there's not a lot of money to be invested in the business but see if you can make something out of it.
Our timing was good. I think it was a fun time to be in the industry where ETFs were beginning to grow and a lot happening.
Akshay: And ETF is an exchange traded fund.
Sanjay: ETF is like an open-end fund which actually trades intraday. Generally, it started off as an index, taking an index basket and building an open-end mutual fund around that. So if somebody wanted to kind of trade during the day, you could do that as well.
Akshay: The difference between a mutual fund and an ETF is that in a mutual fund you pay money to the fund manager and if you want to withdraw money, the fund manager gives it back to you.
But in an ETF, that mutual fund can be sold to other people directly. You don't have to go through the fund managers.
Sanjay: It's listed on an exchange that there's a transaction happening between two different entities. The other big difference in the US obviously is that the tax benefit; if you own an ETF, you don't really pay taxes on an annual basis. But in the US, you actually have to pay taxes on the mutual fund, on any unrealized gains as well.
It's much more a tax efficient vehicle, you control your own tax destiny. When you sell, then you kind of have to pay it. So there's that added benefit to that as well. And all of the ETFs that were in the first generation, they were all index space so they were low cost.
Akshay: And ETF can also continue to accept money directly from investors. It's not just people buying and selling on the exchange but the fund also continues to take money in from investors.
Sanjay: The other thing is, since it's listed on exchange it's very transparent, so you know exactly all the underlying holdings, what's it's holding.
There are a few benefits that came along with that and low cost being one of them. I think that, the whole notion of being a more investor friendly structure, it appealed to a lot of people and today it's about 7, 8 trillion dollars in total assets on the management in ETF structure.
That was actually part of our initial motivation. We'll build the indexes that'll be useful for Morningstar and its entire ecosystem and then be able to find ways to license it for other applications as well.
Akshay: And how does one go about building an index? How did you build your first index? And I'm sure it would've evolved today, the way of building an index would be very different.
Sanjay: What we used to say was, the barriers to entry at that point when we got in were very high.
And today the barriers to entry in the business are relatively low because the technology has evolved so much. The data is easily accessible. But the barriers to success in the business are still very high. It's an industry that is dominated by a handful of very large providers.
And then there's a long tail of providers. It's a big pie. They can have a small fraction of the pie, but the big pieces of the pie are still owned by some very large providers. But to your question again, I think what you really need is access to data that is coming from all the listed companies on an exchange. You need to have capability to gather all the information.
Akshay: Which probably through a Bloomberg subscription you could get that.
Sanjay: There are sources through which we can get that. If you want to maintain real-time calculation, I think that's a whole different ball game because the indexes that have listed the ETS on it, you do need to be able to maintain that on a real time basis.
So you need to capture the data as the trades are happening, you need to pick up those trades and the index, the company values, your corporate actions when the company is paying dividends, stock splits and things of that nature.
You need to have a good source to gather all of that as well. And then be able to publish some of those. So those are the main thresholds in order to gather that. Today it's outside the run of possibility but back in the day, you really needed to invest in technology and be able to gather information from different exchanges around the world, all the corporate actions that are happening.
Those are the main things. And then you try to find what are some of the unique gaps in the industry once an index is done or you have defined what the market makeup is, it's basically the same thing that other people would come up later on. Is there value in creating more of those indexes?
I guess it becomes very commoditized once you define market, we call it beta. Once the beta is defined, there's not too many different ways you can actually enhance the value of that.
Akshay: There's no use making a broad index because everyone will use S&P 500. You would rather want to find a niche and make an index in that niche.
Akshay: What was Morningstar's journey in terms of what niches you made indexes for and how did you monetize them?
Sanjay: We always have the view that we want to focus on what you're really good at or what you're known for. Morningstar is very well known for how we've taken mutual funds and we've created a two-dimensional three by three, what we call the style box.
On the horizontal axis we have value, core and growth. So you look at what stage of growth they are in, are they value based or growth based. And then on the vertical axis- large, mid and small. So it buckets all the companies in the universe along those two dimensions into one of the nine boxes. That's how we were looking at all the mutual funds, how the mutual fund managers were managing their portfolio, where their orientation was. And then using the same kind of lens to help people understand how the market is behaving. It was helpful.
If you want to, you can have a big picture overall what the market is doing but then underneath the market, it behaves very differently in large growth versus small value. So having been able to provide that nuanced insights into the market, where the headwinds and tailwinds are, I think it was helpful.
We took that as a starting point, started off and it actually resonated quite well because a lot of users who actually already understood that it layered the land. I think for them this was a very helpful tool.
Akshay: So you created 9 indexes then? One for each of those boxes in the metrics.
Sanjay: There were nine, one for each. I would say that we combined different permutation combination so there was a 16 total. There's a overall market and then there's a large cap, mid-cap, small cap and value growth. Overall they were 19 but the nine components; they were the building blocks of the whole market.
They were what we would call mutually exclusive and exhaustive. Exhaustive, if you combine them together you get the whole market. But there was no overlap in any of the securities.
Akshay: What's the difference between a value stock and a growth stock?
Sanjay: Value stock is; companies that are not growing very fast but they have good value, a lot of the banking energy sectors. Growth is generally kind of companies that are growing very fast, less focused on earnings.
And a lot of the technology type businesses you would find in that.
Akshay: How did you monetize once you created the index?
Sanjay: It was not a easy journey. We built the products and then it took us about two years to find a partner, which was a big milestone for us and then they created ETS around that. There were nine ETF products that were launched and introduced.
And that started off our journey. We certainly felt, in our industry there's a huge inertia. People do not change or move away from existing products or benchmarks unless they really have to. And there was no compelling reason for them to do that.
We had the early success and along the way we actually did some other interesting things. But the market was still pretty complacent. Again, I don't really need to see a lot of new products here. I'm happy with the branded indexes that are existing out there.
And then the global financial crisis happened and I think in the US, the market was on 38%. And people, it gave them a little bit of a pause that, if I'm investing in an index and the index which people would say if you follow the efficient market hypothesis, that the market is actually the best gauge and the market knows best.
And if it's down 38%, there might be other ways for me to contemplate the investing. And that for our business was actually very beneficial because at the heart of it we said our DNA is research.
We actually thrive in understanding, what are some of the factors that are driving managers behaviour or equity markets and so forth. Having access to a very large team of equity analysts, we could lean on them to figure out what are some of the factors that are showing persistence, that could add value to an investor's portfolio.
I think that gave us an opportunity to maintain the indexing structure, which we had mastered by that time. One beautiful thing about being late to the market is, you have to work harder to understand how you can add value and how you can bring value.
In the US there still is actually a car company; Avis Rental Car and their motto used to be" we are number two, we work harder". And that was our thesis as well. There are index providers who've been there for 1500 years before we got there, if you're going to make an impact of some sort, we just going to have to understand and discover what we could do better.
We knew the indexing model quite well, but we wanted to explore how we can actually take that and use that in a different format. And that's where we brought in our equity research and post the global financial crisis, the whole notion of what is called strategic beta or smart beta, people started getting comfortable with that.
Market is what it is. But perhaps there are better ways to bring in some active research transparent indexing structure that is much more investor friendly; could be a better way to invest in index funds. So that was the tipping point for our business.
We actually launched a product which was taking out the best equity research that we had into an index structure in a very focused portfolio, it was like a 20-stock portfolio. And then later on we expanded that to 40 stocks. But the holdings would be transparent, the weights are very transparent and people could license it to create investment product. And we find partners along the way who actually did that and had tremendous success with that product.
Akshay: I want to break down some of the stuff that you spoke about. You said after the financial meltdown of 2007, smart beta or strategic beta came into focus. What does this term mean?
Sanjay: The traditional beta means that you invest with the market. Everything that's listed on the market, you're going to take that. And proportionately you include every single stock, whatever is part of the index in the same rate. You're not making any bets there.
You're basically saying that, whatever the size of the company is relevant to others- that's what your makeup of the index is going to be. It's that simple. Strategic data is, if you think of a spectrum on one side you have the market and the other side you have an active manager who's selecting stocks, they have a high conviction amount.
It's somewhere in the middle where you're trying to bring the two pieces together. You still preserve the indexing model where it's a rule-based transparent, you periodically rebalance the portfolios, but you are not betting on all the companies and all the size and everything.
You have a way to identify, there might be a factor that you have conviction about and you are using that to introduce a bias or selection criteria. That'll help you whatever your objective might be. If you're looking to generate alpha, that would be the one. If you're looking for more income or mitigate risk, I guess you could actually do with whatever proven research you have access to.
Akshay: Alpha means what an active investor is able to generate over and above the market.
Sanjay: As an active investor, that's what you aspire to do. You're trying to beat the market and as an active investment manager, that's what people entrust you to do with the money, that you should be able to beat the market. If not then why bother, I can actually go with an index fund and save some money there.
We were very privileged and we still are. We have an ecosystem of research, equity research, ESE research and asset allocation research where we can actually understand how the asset allocation can add value.
Having unfettered access to some of the research allows us to experiment and kind of look at things a bit differently. We do have the indexing model, which we know quite well but then trying to meld some of the other research, it is just bringing a different style of indexing that actually I think for the future, this is how it's going to be as we think about the industry evolving.
Akshay: I'm still not fully clear on what is this new product that you made which was based on research. You launched a new type of index which was based on research. What is that? How is it different from the other indexes around?
Sanjay: We have a team of 125 analysts, which was actually smaller at that time and they do research and they have recommendation on,
Akshay: like a buy, sell, hold and a target price.
Sanjay: They have their first look at the business fundamentals. The company, does it have any moat in their business. They have a economic moat rating, wide moat, narrow moat, no moat. It's a term from Warren Buffett. You want to go for businesses that have a wide moat. Then they have something unique advantage that are difficult to replicate which means they will have more pricing power and high margins and so forth.
Then they do their own discount cash flow and come up with evaluation models if the company is trading below their expectation or above. So taking a combination of companies that have a wide moat which are businesses that are more entrenched pricing power and which are trading at a discount.
There's a lot of active research that goes into determining those criteria but beyond that we have rules which have been established that once a quarter we look at the 20 cheapest, wide moat businesses. So that'll be the basket we actually create the index of.
I would say it's a marriage between active and passive to create something. In this case, the index is not giving you beta, it's giving you alpha and it's actually done quite well. It's not every year it's hitting out of the park but for the most part when you look at the long term, when you look at the peer group in the large core category, it's actually been in the top decile for over the last 10 years or so. Its just, necessity is the mother of invention. We had something but the barriers were very high.
What we went back to, what we were really good at is, our research and we tried to bring that into the indexing practice.
Akshay: So this is in a way an unbundling of the actively managed mutual fund what it used to be. An actively managed mutual fund would probably be doing something like this where they would say, let's look at companies which are value picks and have a good vote and they would manage that money for you and charge at 2% or 1%.
Now this has got unbundled where Morningstar is doing this research and creating an index which is equivalent to what a mutual fund might have been doing. And now an index mutual fund can be built on top of that with a very low fees, which overall benefits the investors.
Sanjay: Like I said, it's a marriage between good, active and passive. You bring some of the attributes of an index.
Akshay: It has the benefits of active and the cost of passive, basically like for an investor.
Sanjay: That's strategic data, what we call it at Morningstar. People call it smart beta, enhanced beta, there are many different terms in the industry. If you were to do a Venn diagram, it's like the overlapping part in the middle where you have passive and active on either side but this is where you can meet in the middle.
Akshay: Very innovative in terms of how it's cut down cost for actively managed. You're getting an actively managed portfolio at one tenth of the cost.
So you've now also launched an index for private market. Tell me about that. What is the use case for an index on private market and what made you want to launch that?
Sanjay: As I mentioned earlier, there has been a tremendous shift from public to private. This segment of the market which is really at explosive growth is the late-stage private venture-backed businesses. The term 'Unicorn' which is a private venture backed companies with a billion dollar in market valuation.
It was coined in 2014 and it was named after a mythical creature 'The Unicorns' which means it's very rare. And at that time there is about less than 40 unicorns globally.
Akshay: India probably had just one. I think InMobi was probably the only unicorn at that time.
Sanjay: Today there's close to about 1300 Unicorns and some of these are Decacorn and some of them by times it's about 300 billion stripe, 100 billion. So these are not rare anymore and these are not small anymore. There's a whole segment of the market that's actually pre-IPO that is actually huge.
And this market is growing. You hear anecdotally people saying that, this is a market which is actually doing really well. But there is no gauge, there's no market sentiment, there's no understanding what the market looks like. So having the PitchBook, the level of data that they have and recess they have, I think we are very fortunate to be able to take some of that even though it's very unstructured data, unlike public markets where each company has a ticker and Qsep. It's very easy to manage and move things around.
We had to jump a lot of hoops in order to normalize this data and kind of create a more structured way, so we can build some index back histories and normalize some of this. But we were very excited. I think now we can shine the light on what the market looks like in this space.
This is between companies before they go public and the late stage. And this is where in our view, convergence of public and private market is beginning to happen. You see a lot of mutual fund managers of what they call crossover managers; they're beginning to own late-stage private companies in the mutual fund portfolios.
And you have the traditional VCs and the general pension plans and the like who are actually investing in that. This market is going to become much more visible and transparent and our goal is; whatever we can do to shine the light and kind of help people understand what are the risks here.
When people say there is more than meet the eye. You saw FTX, which was another company that just went bankrupt from 32 billion to zero. Those kinds of things and when you aggregate the whole market, I think it'll give you a full picture on a daily basis how the market is behaving, what are the long-term risk and return features of this market.
If you want to look through the lens of different industry verticals; what are the FinTech or what are some of the SaaS businesses doing. You'd be able to kind of slice and dice some of that as well. So it's a beginning of a journey. We think the first step is- create a market sentiment and then as the market infrastructure improves, there'll probably be ways you can invest in this segment of the market as well.
We are not there yet but if there are managers who are actually investing purely in this segment, this would serve with a reasonable benchmark for them as well.
Akshay: What is your unicorn index? How many companies does it consist of and how did you build it? Help me understand that.
Sanjay: Today there's about 1300 companies that are part of the Unicorn and we have a broad global index which actually includes all of those. I would say that's akin to a beta product in this space. And then we have 10 other regional indexes. There is US, UK, China and India.
Akshay: All the whole universe of US Unicorns is included and same for India and so on.
Sanjay: There is a broad product for US, which has about 6 under 50 which is virtually every unicorn out there. And then we have a US 100, which is a scaled-on version of the parent index.
This is indexing science here but with hundred securities, we can actually replicate almost 99.9, the correlations that you have. So you don't really need to have every single company being part of that. And same thing, we have the UK Index and then China and India.
In India we have India 25. The total number of Unicorns in India is somewhere between 70 and 100. The number is disputable, but that 25 actually will give you a very healthy mix of what the market looks like. It tracks the broad index quite well.
The other thing we've done is, we built a pricing model that goes beyond with unicorns or any private company for that matter. A value is described only when a new deal happens. It's like real estate, when the transaction happens, typically it's like once every 18 months or so on average, but what happens in those 18 months especially in the last 18 months, a lot can change. And our goal is to be able to present what is the more indicative value of the market in that time period as well. We've looked at the other places where there's some price discovery on the private market side, looking at companies that are similar to the business we are looking at.
So PitchBook has analysts who actually can help us look at what are some of the cohorts similar companies and if there's a funding round that is happening in those, that actually provides you an indication of where the market is heading.
Likewise on the public market side as well there are industries within which the company sits. So we can use that as an indication of how the price is likely to be. Plenty of research out there that shows there's a 9-to-12-month lag between public markets and private markets.
So we are able to bundle all of those three factors together. And on a daily basis, we are able to get a single value for each company and provide a market view which is more realistic view, as opposed to looking at the last few values.
Akshay: So for example, Amazon is a publicly traded company and price movement of Amazon would affect Flipkart's valuation in India, which you would factor in to create a real-time daily update of Flipkart's valuation in addition to, let's say, other transactions happening in the e-commerce space. So all of those would factor into a daily revision of Flipkart's estimated value.
Sanjay: That's right. Swiggy is a big Indian food delivery company and you have comparables; DoorDash and others who've gone public.
Akshay: Zomato is listed in India.
Sanjay: You can actually look at their fluctuation, their market value, because within the industry cohort, there's a lot of systematic risks which are very similar to the businesses.
Akshay: Similarly, Paytm's price would influence all FinTech companies pricing valuation in the index.
Like you told me the first time you built an index, it took you 2 years to monetize. So right now you are in that two-year phase of this index, because monetization right now is tough because there is no exchange for buying and selling stocks of startups which are not listed.
But you feel that eventually some liquidity would come in here, you would be able to buy and sell stocks of unlisted startups.
Sanjay: You'll be surprised, I think where there's a will, there's a way. Even in the short period since we've announced the introduction of index, we've actually had people from different parts of the world who reach out and said that we've been thinking about this or we've actually built our own index which is on a spreadsheet. But this gives us something that we can actually hang our hat on and use it. They've got some ideas synthetically or other ways they would actually start looking at it.
The arc of innovation will suddenly solve some of these problems today. It's not easy to fully replicate it and I don't think we'll ever get there. But the main thing is exposure. And there's a lot of wealthy investors who are looking to gain exposure to this segment of the market.
There are funds out there, but I think when you look at the fee structure, it's the traditional institutional 2 and 20, which are very high. I'm sure there's folks who will actually figure out how to do it in a more cost-efficient manner.
And our goal is; we've got the infrastructure and we can create more bespoke products. If somebody has a need we don't have to have a hundred stock portfolio. We can actually make it smaller based on what is more tradeable or what is more accessible from their market.
So again, I think it's going to be a little bit collaborative in terms of working with the prospective asset manager in terms of what their needs are and how we kind of solve these problems.
Akshay: Two use cases for this currently. One would be, say a Sequoia would use this as a benchmark that are they doing better than the Unicorn index because Sequoia is essentially private equity investor.
And the second is to build synthetic products. Now help our listeners understand what's a synthetic product which could be built on top of the Unicorn index.
Sanjay: We've got a history in terms of what the risk return pattern of this index looks like. Plenty of these global banks who actually know how to synthetically replicate when you give them a risk return profile. They can use derivatives to create, replicate that.
And with the swap product, I guess there could be somebody on the long side and somebody in the short side. Then, long side people who are looking to invest and gain exposure for the long term. And on the short side, somebody who already has exposure and they're trying to mitigate their risk.
So they would sit in the middle and be able to use some kind of a derivative instrument to predict what the pattern of returns going forward would be.
Akshay: What is your view on the future of the indexing industry?
Sanjay: Obviously, I think the industry has grown so much and today, I might have mentioned this earlier, the beta has become commoditized, it's a race to the bottom in terms of how you access it and we've already seen that.
Gradually I think all of that, we see with the big providers in the US, be the BlackRock, iShares and Vanguard and State Street, it's an access point. It's not something unique that anybody can offer. So the cost is obviously going to be a big determinant in terms of how this is delivered.
I guess the future innovations are going to be in some areas like, ESE. Again, I think how people are trying to align their portfolios to their value systems and belief systems, and if they believe in climate is going to have an impact, how they express their convictions in that way.
And then the third thing I would say is in the whole notion of personalization, Direct indexing is another area which has already caught on. So direct indexing is, you take a starting point as an indexing basket and then you can actually eliminate some stocks based on, let's say if you work for a technology company or in that sector and you don't want any more exposure, you can actually underweight that segment.
It just gives you a little more ability to personalize it. And with the technology today almost all the major asset manager, wealth managers are now beginning to offer you that personalization. So it's not, you don't have to buy an index fund, but you can have index which is tailored to your personal needs.
You can also implement your personal ESC, so you don't have to buy an ESG fund, which might be very generic in terms of, it's one size fits all. But if you really care about tobacco not being part of it or guns not being part of it, you can actually eliminate some of that exposure as well.
Before you go……the analytics only tell me so much, I want to hear what you feel and think about the conversations.
Mail me at firstname.lastname@example.org with your comments & feedback or if you just want to hear my comments on your startup idea - I love getting your emails!
Until the next founder's thesis📕,
Your host, AD