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The Mutual Fund Show: How Rolling Returns Can Help In Better Scheme Selection

Rolling returns considers a series of returns over a long period of time and then takes average to see how the fund has performed.

A customer looks at paint samples at a store (Photographer: Victor J. Blue/Bloomberg)
A customer looks at paint samples at a store (Photographer: Victor J. Blue/Bloomberg)

One of the warnings mutual fund investors often hear is that past performances can’t predict future returns as they don’t address the volatility in markets.

Point-to-point returns can actually lead to the misleading inference of fund performances, and thus wrong decision-making, according to Sunil Jhaveri, founder and chairman of MSJ Misterbond. Instead, he suggested investors look at the rolling return for choosing funds. It considers a series of returns over a long period of time and then takes an average to see how the fund has performed.

If the outcome of ranking funds via rolling returns is divided by the standard deviation of the fund, it will show the funds that are able to deliver returns with low volatility, and thus for an average investor might be a better outcome, he said in BloombergQuint’s weekly special series The Mutual Fund Show.

Previously, in an interview with BloombergQuint, Sunil Subramaniam, chief executive officer at Sundaram Mutual Fund, had said rolling returns help investors choose the right asset allocation based on the time horizon for investment and risk appetite.

But the rolling returns data, according to Jhaveri, is not available freely unless people subscribe to specific services. An investor can write to mutual fund houses for rolling return reports and analyse it before choosing to invest.

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Watch the full video here:

Here are the edited excerpts from the interview:

Can you briefly tell us what is the rolling returns methodology?

SUNIL JHAVERI: So first and foremost I’ve been an advocate of rolling returns analysis for a very long time because point-to-point return is nothing but a post-mortem of the recent past performance which could have been impacted based on the events which were recent events. Just to give you an example, when the markets crashed by 1,700 points and if I wanted to just show a different picture to my investors, all I had to do was one day earlier and the point-to-point returns thereafter, which is six months 12 months backwards, would have looked very good. But if I want to show a different picture to my investors, I would have taken that particular day when the markets collapsed and then showcased the returns analysis of last six-12 months. It is just a one-day difference which could have changed the point-to-point returns dramatically, and the investors would be absolutely clueless as to what happened. But let’s assume I want to do rolling returns from 2010 to 2021 of daily five-year rolling returns analysis. What it does for the investor is that any time I’ve invested from April 1, 2010, in April 2011, I would have invested in 2012 and so on so forth, and then thereafter held it for five years, so all the observations which would have completed the five-year period from 2010 to 2021 all would be captured. So, the good, bad and ugly of every observation, which has completed five years in an equity analysis is the right way of taking into account, that is while selecting a scheme.

For example, let’s assume that I bought a fund exactly five years back from today, why would that rolling return analysis give me a better verdict than a point-to-point return analysis?

SUNIL JHAVERI: So, let’s take an example of 2008 and 2009. If I were to do a point-to-point returns analysis on Jan. 1, 2008 and five years back point-to-point returns, it would have looked stupendous, in terms of the returns analysis. Naturally, based on that somebody would have selected a fund, which has unfortunately become a norm rather than an exception to select based on the past performance. The same fund, one year later in 2009 March, if I would have selected it, the returns would have looked dismal based on the five-year returns analysis, post March 31 and earlier than that. As against that, if I would have done a five-year rolling returns analysis of the same scheme, it would have kept captured this period and beyond that also. So, let’s assume that minimum return was say 5% or negative 5%, which happened on March 31, 2009 when markets collapsed by 60%. It would have captured that as a minimum return also, and the rolling returns analysis will throw up two more numbers — the maximum returns and the average returns, and on top of that standard deviation. See, investors are looking to have consistently good performance but at the same time they want to have a consistently smoother investment journey that can be only through the standard deviation matrix.

...If we actually use standard deviation as a methodology in addition to rolling returns, then that might give us like a different picture which might be better. Why is it that?

SUNIL JHAVERI: Absolutely. So, these are the two methodologies which we are going to be introducing in the market for the first time. The first one points with weightage is nothing but consistently high performance and high returns over this five-year rolling returns analysis and that also in the higher returns band. What do I mean by higher returns band? The returns band will be 0-5% or less than zero is negative observations also, 5-10% and 10 -15% and so on so forth. So that means consistently, Mirae has been delivering very high returns and that also in a higher returns band at the same time. So that is one way of giving a ranking...

But more importantly from an investor’s point of view, this is what I call investor returns expectations, which is the higher returns—investor high return score, IHR is what I’m calling it. If you want to have investor experience score, which is how volatile the journey has been by delivering these high returns — as you can see number seven of Edelweiss comes down to number two that means Edelweiss has done phenomenally well in terms of giving investors a smoother journey and at the same time, consistently delivering high returns in the top 10 schemes of the large-cap space, as against that Mirae was number one consistently in terms of high returns in the higher returns band, but in terms of volatility it is number four, which is also extremely good. Because if you are in the top five, then that’s what you should be looking for as an investor. So, rather than a point-to-point returns analysis this methodology which we will introduce will get transparency as far as the rankings are concerned.

Where does an average investor get these rolling returns? Are they easily available, has it to be calculated, under the current scheme of things from publicly available and freely available resources?

SUNIL JHAVERI: Generally, it’s not available so easily. You have to ask the mutual fund house. Our platform has a rolling returns calculator but that is only through subscription by the advisers, the mutual fund distribution community, not available to the B2C, the investor segments so far.

So, it’s not freely available and a DIY investor may not be able to get rolling returns that easily unless she or he writes to the fund house for a history of the rolling returns, right?

SUNIL JHAVERI: Absolutely and that’s what they should be insisting on in terms of one of the data points.

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Sunil, when you’re saying that if we deduct or rather if we divide the returns by standard deviation, it makes the returns of the fund that much less volatile. We are effectively trying to say that over a period of time, the investor will probably make the same returns that a fund is giving, but if it is divided by the standard deviation, it will make the annual exercise a lot easy-breathing, if you will, because the investor will not see the portfolio really jumping up and down too much, year after year?

SUNIL JHAVERI: Let me explain to you in a different manner. Let’s presume that there are two schemes, both have delivered 12% average returns but the average returns hide the fact that there will be minimum returns and there will be maximum returns and then that’s what gives you the average returns of all the observations put together. One of the schemes may have a negative 10% minimum and maximum of 30% but still come to 12% return. The other scheme may be 5% positive minimum return and maybe 20% positive on the maximum side, but the average is 12%. But the scheme which has not delivered negative returns, there the investors’ exercise and their experience of investing in that scheme would have been far better than the one would have delivered negative 10% and a positive maximum return of 30%. So that’s what we’re trying to get at. The investor experience is more important because when markets collapse like they did in March 2020 or March 2009 and so on so forth, that’s the time when most investors go outside the market, go back to the traditional avenues like fixed deposits, etc., and they don’t come back to equity as an asset class or mutual fund as a vehicle also. This is where we are trying to get the mindshare of the investors, the AMCs and the mutual fund distributors also by saying, “please adopt and embrace rolling returns analysis”. What you saw in terms of the ranking, we have created a calculator for the ranking, automatically. So, there will be say 1,000 observations, which has completed five years during this period just for an example, every observation has a return of negative 5% to 5% positive 10% so and so forth. All the observations are given weightage and higher the returns band, higher the weightage and lower the returns band, lower the weightage. That’s how we arrive at that ranking of one, two or five, etc., and then thereafter that number which we arrive at and divide that by standard deviation is what the investor experience score is—what we are talking about now.

I’m presuming Sunil that the ranking is something that if an individual investor were to go and do this exercise as difficult as it is for even one fund, but for doing 10 funds would be nearly impossible. But let’s assume that I’m choosing one fund and I’m getting the numbers from the AMC then the ranking that you’re talking about—not the one divided by standard deviation, but the basic ranking would essentially come out to be the same if the investor is calculating the numbers themselves?

SUNIL JHAVERI: They will not come to know the ranking at all by analysing rolling returns on their own, they will not be able to come to know the ranking at all. There is a methodology which is happening inside that calculator which is creating this. As I told you we are getting the weightage of 1,000 observations. I also weight it with the returns band too, and thereafter the rankings are calculated. It’s a very complicated process, individually, you will not be able to come to know at all about the ranking but more importantly, investors are confused. So, one ranking company is giving one star to one particular scheme whereas the other ranking company is giving four stars to the same scheme. Now who to believe and what is the methodology behind that is not so transparent. As far as we are concerned it will be so transparent because we are giving you the rationale behind it too.

What is an average retail investor supposed to do? Let’s assume the retail investor is not going out and subscribing to any of the rankings or to this methodology because it’s subscription based, how does one use rolling returns to his or her advantage in choosing funds?

SUNIL JHAVERI: So, what the rolling returns analysis throws up as a summary is the minimum returns, the maximum returns, average returns, standard deviation and the returns bands which is 0-5 and 5-10 etc. So, what the investors should be looking for is the lower standard deviation and the average returns. These are the two important criteria for you to select, one is the average returns, and the average returns are similar as more or less 13-14 or 15%, nothing much to choose from on a five-year rolling basis between three schemes. But the lower the standard deviation, which is the denominator, the better will the ranking be for that scheme and that will be the investment, where the investor will have a much better experience in terms of getting consistently good returns at the same time at a lower volatility.

From the studies that you have done, the most recent count of rankings plus the low volatility, choose a category, let’s say large cap. Tell us about a couple of funds which have performed really well on the ranking front and at the same time, the standard deviation factor also makes them look attractive, which are these?

SUNIL JHAVERI: This is not a recommendation but what I’m saying is the Mirae Large Cap, Axis Blue Chip and the Edelweiss Large Cap—they’ve all made the cut as far as I’m concerned both on consistently higher returns and consistently higher returns adjusted for volatility.

Is there a way in which the investors can use this methodology to either eliminate funds or narrow down on funds? You mentioned that look at lower standard deviation, aside of that is there something else which people should keep in mind?

SUNIL JHAVERI: It’s very difficult for people to judge as to when the five-star rating will become one star, unfortunately. All of a sudden, a five-star can be rated one star and then investors are at a loss as to what happened. As it is that, our ranking methodology will also talk about the red flags and the green flags. The red flags will say that this particular scheme should be put on a watch list and if it continues to have a higher standard deviation, i.e., the ranking is on a higher number, when it goes beyond 10 to 15, it comes to be a red flag so please keep a watch on it on a month-on-month basis. At some point in time, we have realised that they will fall out of the top 10. So, that gives you an idea as to the schemes which may not do well in future because the volatility has crept in into that. There will be green flags also where you may not be consistently high in terms of the returns, but the standard deviation-based ranking, they might be coming up the ladder. So, they may be, say, 12 on the consistently higher returns ranking, but they may be 2 or 3 or 4 in consistently higher returns adjusted for standard deviation and we keep that in the positive watch list, and in some point in time in the future, I realise that they come into the top 10 on both the rankings methodology.