Mint50 methodology that sifted through risk, returns, portfolios of funds6 min read . Updated: 21 Jul 2019, 12:49 PM IST
Out of the 36 categories of mutual funds defined by capital markets regular Securities and Exchange Board of India (Sebi), we selected 16 for inclusion in the Mint basket
The Mint50 basket, a curated list of 50 mutual fund schemes, is selected on the basis of a two-level evaluation process. Out of the 36 categories of mutual funds defined by capital markets regular Securities and Exchange Board of India (Sebi), we selected 16 for inclusion in the Mint basket. These categories were seen as important to building the core and satellite investment portfolios, and in facilitating the financial management of a household.
We put the 16 shortlisted categories into four buckets—equity, hybrid, international and debt. Within equity, we chose large-cap, large-and-mid-cap, multi-cap, mid-cap, small-cap, value-oriented/contra, equity-linked savings schemes and focused categories. Within hybrid, we chose conservative hybrid and aggressive hybrid categories. Within debt, we took liquid, ultra-short duration, low duration, short duration and corporate bond categories.
To be eligible for inclusion, the schemes had to meet two requirements. One, we considered funds with net asset value (NAV) history of at least five years for equity, hybrid, short duration and corporate bond funds categories, and three years for liquid, ultra-short duration and low duration categories. Two, we took funds with assets under management (AUM) in the 98% percentile, which ensured that except for funds with very small AUMs, all others came into the evaluation bucket.
(This is how the 98% percentile works: If we assume that the total AUM in a category across all funds is ₹1,000 crore, then the 98th percentile translates into ₹980 crore. The funds in the category are arranged in descending order from the highest AUM to the lowest and all those funds are included till the cumulative AUM reaches ₹980 crore.)
However, funds which had totally different portfolios before the re-categorization of schemes were excluded.
The evaluation was done at two levels. At the first level, all the schemes that met the eligibility criteria were put through a quantitative evaluation of their past performance. At the second, we looked at the qualitative aspects such as strategy and style, processes and procedures to understand how they impact outcomes.
In a departure from previous versions of Mint50, this time we decided to get in the experts to run the numbers. CRISIL is our data partner in this exercise who has been entrusted to run the numbers and generate the report cards that would lead to the next stage of evaluation. The parameters used for evaluation in the first stage were return, risk and portfolio characteristics.
The period of analysis was five years for equity funds, hybrid funds, short duration and corporate debt funds. For other debt funds, it was three years . We used rolling returns to evaluate the return performance given its superiority over trailing returns in its ability to capture the actual return experience, which is not marred by the level of net asset value (NAV) at the start or end date.
For example, we used the three-year rolling returns, rolled daily for the last five years, for equity funds. This means that every continuous three-year holding period within this five-year period was considered and returns were calculated for each holding period. The first three-year holding period would start on the first day of the five-year period and end three years from then. The second three-year period would begin on the second day of the five-year period and end three years from then, and so on, till the last three-year holding period would end on the last day of the five-year consideration period. The returns are calculated for each of these holding periods and averaged to get the three-year rolling returns of the fund. Daily rolling means we looked at a three-year period starting every day and, thus, all market highs and lows in the period are reflected in the final rolling returns number. On the other hand, point-to-point returns just looks at one data point and the calculation may be inflated or depressed depending upon the level of NAVs at the start and end points of the period. To extrapolate this one return data point as reflective of the return of the scheme for the holding period, say three-year return, may be misleading.
The standard deviation of the rolling return was taken as the risk measure. The period of analysis was broken into four overlapping periods and each period was assigned a progressive weight starting from the longest period as follows: 32.5%, 27.5%, 22.5% and 17.5%, respectively. For equity funds and aggressive hybrid funds, the overlapping periods were the latest 60, 54, 48 and 42 months. For short duration funds, corporate bond funds and conservative hybrid funds, the periods were the latest 60, 48, 36 and 24 months; and for liquid, ultra-short and low duration funds, it was the latest 36, 27, 18 and nine months. The near-term return numbers, thus, get included in every bucket. This gave greater representation to recent performance, while not ignoring the long-term performance of the fund.
For equity schemes, we used active rolling returns instead of plain rolling returns to evaluate the return performance of the fund. Active return is the excess returns over the appropriate market benchmark index. An actively-managed equity fund is expected to beat its benchmark. A fund that does not do that should be penalized. The three-year active rolling returns, rolled daily, for the last five years were used and a 50% weight was assigned to it. The standard deviation was given a weight of 25%. Portfolio characteristics that explained the risks and returns of the fund was given 25% weight. These include stock and sector concentration, ease of liquidity in the portfolio, cash holding and portfolio churn.
For short duration and corporate bond categories, one-year rolling returns, rolled daily, for the last five years were considered and a weight of 50% given to it. The standard deviation had a weight of 10%, while portfolio characteristics got a higher weight of 40% since these features build the risk in the portfolio. The parameters considered were issuer concentration, sensitive sector exposure, liquidity, asset quality and modified duration of the fund.
For liquid, ultra short and low duration categories, we considered the one-month, three-month, six-month returns, respectively, rolled daily for the last three years and gave the parameter a weight of 50%. The weights for standard deviation and portfolio characteristics were the same as for short duration and corporate bond categories and so were the parameters, except that here the parameter of number of issuers was also considered.
For aggressive hybrid funds, a 50% weight was assigned to the return parameter and the three-year active rolling returns with respect to category benchmark, rolled daily, for the last five years were used. The standard deviation was given a weight of 25% and portfolio characteristics got 25% weight. The parameters here were stock concentration, sector concentration, liquidity of the portfolio, cash holding and portfolio churn. For the debt portion, the portfolio characteristics considered were issuer concentration, sensitive sector exposure, liquidity, asset quality and modified duration.
For conservative hybrid funds, the one-year rolling returns, rolled daily, for the last five years were considered and a weight of 50% given to it. Standard deviation got a weight of 15%, and portfolio characteristics 35% and considered the stock and sector concentration and skewness and the liquidity of the portfolio using CRISIL’s liquidity score. For the debt portion of the portfolio, the parameters considered were issuer concentration, sensitive sector exposure, number of issuers, liquidity, asset quality and modified duration.
For international funds, the rolling returns and risk had a weight of 50% each. The report card for each fund was generated and a final score assigned to it. This was used as the filter to identify a short list of schemes that generated good risk-adjusted returns that made it to the second level of evaluation. At this stage, Mint reached out to the fund management team of each scheme to understand the strategy, the processes, capabilities, and the checks and balances that would contribute to desirable outcomes for the investor’s money.
The final Mint50 list that made it through both these processes, we believe, are well-poised to continue giving investors the best experience.