A couple of weeks ago, we’d explained everything about using mutual fund rolling returns when looking at fund performance. Rolling returns forms the base for several other mutual fund ratios and metrics that are used frequently in understanding a fund’s performance. You know them – we talk about it when we write on funds, you see them in fund details pages. We are, of course, referring to the Sharpe ratio, alpha, beta, standard deviation and the like.
Each metric has a story to tell. But knowing what this story is, is important. Knowing how to look at these metrics together, is important. Knowing which metric to use for which type of fund is important. That’s what we’ll cover here. Do note that this is a more basic article for those not yet well-versed in looking at fund returns. For the more savvy among you, we’ll see you in our next article!
Metric #1 – Standard deviation
Standard deviation gives the extent to which a fund’s returns fluctuate. This fluctuation is both on the upside (gains) and the downside (losses). Measuring standard deviation involves taking a specific return period over a length of time (or rolling returns, in other words) and applying the normal standard deviation formula on these returns. Our mutual fund rolling return calculator will give you a fund’s standard deviation for the rolling period you choose.
A standard deviation number on its own won’t tell you anything – it should be compared with other funds. Quant Active Fund, for example, has a 1-year standard deviation in return over the past 4 years at 34%. DSP Flexi Cap, on the other hand, has a standard deviation of 20%.
What it shows: A high deviation equals high volatility or a greater extent of fluctuations in a fund’s returns. That is to say, the fund’s returns will tend to see frequent rises and dips. As a general rule, lower volatility is preferable as over time, smaller dips and rises help build better returns than big rises and big falls.
Volatility helps you understand the extent to which returns can swing and what to expect from the fund based on how the market is performing. Highly volatile funds may not suit more conservative investors.
- Volatility is a key metric in funds where there is an inherent propensity for returns to fluctuate. This, obviously, will be equity funds. In hybrid funds too, volatility is important; these funds are meant to help cushion your returns from equity-driven return swings and a highly fluctuating fund here is not going to help.
- In debt funds, volatility is not that important. Accrual funds are by nature low volatile as bond prices do not see significant fluctuations. This is especially true in very short-term categories such as liquid, ultra-short, low duration, short duration or even credit risk. Duration funds, such as gilt and dynamic bond funds, will see volatility in returns as they depend on bond price rallies to make their returns. In these categories, you can check standard deviation, and stick to shorter return timeframes as explained in the point below.
- While you look at ‘returns’ with a longer time frame, deviation is best looked at with a short-to-medium-term view as volatility anyway evens out over time. Consider periods such as 6 months (for hybrid categories such as equity savings/balanced advantage) or 12 months, or 24 months if you’re looking at pure equity funds. Don’t go too long-term as volatility evens out over time.
- Compare volatility between funds of the same category – a large-cap fund will be less volatile than a small-cap one.
Be careful: A high standard deviation does not automatically mean that a fund is unsuitable for you or that it is bad. All standard deviation does is to measure how much returns fluctuate. It does not measure the return itself. A fund can fluctuate a good bit, but still deliver if returns hold above peers or the benchmark. Invesco India Contra, for example, is more volatile than Canara Robeco Flexi Cap, considering 1-year returns rolled over 3 years. But both funds have similar longer-term returns.
Standard deviation also does not tell you whether the deviation was higher on the upside or downside. Therefore, use this metric to understand volatility, but combine it with metrics explained further down to get the full picture.
Metric #2 – Sharpe ratio
The Sharpe ratio is the return a fund has delivered for a given level of risk. The return here is looked at in the context of a risk-free rate. Typically, this is the yield on government bonds. The risk here is the volatility. Effectively, what Sharpe measures is that, for a given return, how much risk has been taken to arrive at it. When you have two funds with similar returns but where one has lower volatility and the other has higher volatility, you’d obviously go with the first one. As with volatility, the Sharpe ratio involves taking funds’ rolling returns. You can find a fund’s Sharpe in its scheme details page.
What it shows: When you’re investing in a fund, you are taking risk. By measuring excess over the risk-free rate, the Sharpe checks whether this risk is worth taking. But high returns can come with high volatility, as we’ve explained above. Therefore, since Sharpe considers the return deviation, it also checks what risk has been taken to deliver that return. Higher return in a fund does not translate into ‘being good’ if this return does not compensate for its volatility. Sharpe is useful in comparing funds that have delivered on par with each other.
Consider Aditya Birla Sun Life Corporate Bond fund, with an average 1-year return of 9.2% when rolled over 3 years. In the same period, L&T Triple Ace Bond delivered 10%. But the former’s Sharpe is far better at 2.54 against the L&T fund’s 1.46 because it was half as volatile. On the other hand, while UTI Flexicap is higher volatile than, say, DSP Flexicap (based on 1 year returns rolled over 3 years), it still scores better on Sharpe as its returns have been high enough to make up for that higher volatility.
As far as using this metric goes, keep the following points in mind:
- Sharpe can be used across fund categories in equity, hybrid and debt.
- The risk-free rate you take matters. You cannot take very long-term bond coupons as the risk-free rate but consider return timeframes of, say, 1 year for your fund. To skirt such issues, it’s easiest to keep to shorter-term bond rates.
- The Sharpe that you see can vary based on the rolling returns period and the frequency of rolling considered.
Be careful: Sharpe is, like with standard deviation, constricted because it doesn’t see whether the deviation comes on the upside or downside. A fund that deviates more on the downside is arguably worse than a fund that deviates more on the upside. The Sortino ratio refines the Sharpe by taking only downside deviation and ignores the upside. Two, in periods of significant equity market correction, the Sharpe ratio for equity and hybrid funds can get very low. If you take return timeframes such as 1 year or shorter to check Sharpe, it can so happen that in corrective phases, the Sharpe can be negative. Should this happen, it’s best to ignore Sharpe as a metric as it can get misleading. Use Sharpe along with both volatility and other metrics explained below.
Metric #3 – Downsides and upsides
As you now know, volatility and Sharpe can hide how a fund performs in different cycles. Splitting up returns into how it performs on the downside and on the upside will show that. There are few ways in which you can see this.
Downside/upside capture: For equity funds and equity-dominant hybrid funds, a great measure is the downside/upside capture ratio. This ratio looks at how much of an index’s loss/gain the fund captures. A fund needs to capture a smaller extent of the downside (so lower downside capture ratio is better) and a bigger share of the upside (higher upside capture is better).
Axis Bluechip, for example, captures 70% of the Nifty 100’s decline when looking at 1-month dips in the index over the past 4 years. That’s better than BNP Paribas Large Cap’s 80% capture. Or in other words, Axis Bluechip is better able to keep losses contained during market corrections than the BNP fund. Funds that keep downsides controlled have less need for big rallies to recoup that loss.
Generally, you’d want a fund that can contain downsides well. But if a fund that’s poor on the downside has a very strong upside capture ratio, it may still be worth considering for high-risk investors. Why? Because it means that while a fund can fall sharply, in rallying markets it can truly deliver well above the market and make up for lost returns. consider Invesco India Contra that has a downside capture of 98% (based on 1-month losses). On the upside, though, it captures 112% of the Nifty 500’s gains, resulting in better-than-average returns.
To calculate downside/upside capture, take a period when markets have corrected. Take the fund’s returns in the same period and divide the fund return by the index return. Ideally, do this for a few different market phases to get a better picture. The index you choose here should be one that fits the fund; there’s no point in taking the Nifty 50 index, for example, and seeing what small-cap funds are doing when that index falls or rises.
Loss instances: But calculating downside capture can be hard. In debt funds, the index is irrelevant. Here, the proportion of loss instances is a great metric to use. This metric measures how many times in a given period a fund delivered losses for a particular return timeframe. In debt funds (and even arbitrage funds), this metric is a useful risk measure because one, benchmarks don’t matter in debt funds rendering the downside capture ineffective. Two, funds see losses based on the maturity and/or credit risk in their portfolio. Three, other metrics such as volatility may again have limited use as returns don’t fluctuate much.
For example, ICICI Pru Savings Fund’s average 1-year return over the past 4 years has been 8.05%, better than ABSL Money Manager’s 7.8%. But the ICICI fund saw 1-week returns slip into losses 7% of the time against the ABSL fund’s 1.3%.
You can change the return timeframe you’re seeing based on the fund – for very short-duration funds, for example, you can take 1-week returns. For longer-maturity funds, you can take periods such as 6 months or 1 year. You can find this metric both in our scheme details page (where we take 1-year return rolled over 3 years) and in the fund rolling return calculator (where the loss instances are calculated on the rolling period you choose).
Minimum/maximum returns: This is another proxy measure for the risk-return balance. Looking at a fund’s worst performance in a period and its best performance will tell you how badly it can do, and if its returns make up for this performance. again, this metric can be very useful in low-risk hybrid fund categories and debt funds.
Like with every other metric, using rolling returns of different timeframes will give the best picture. You can find this information both in our rolling returns calculator and in a fund’s scheme details page. Comparing the maximum and minimum returns between funds will help you draw a picture of which fund is better-suited for you. Funds where the minimum return is very poor, even if maximum return is strong may not fit risk-averse investors.
Metric #4 – Proportion of outperformance
This is one of our favourites! Proportion of outperformance measures how often a fund beats its index and its category. The higher the proportion, the better its consistency and ability to stay ahead. You will get this number in our category-wise rolling returns comparison tool.
What it shows: Looking at current 1-year or 3-year or any other return is simply point in time (we have written in detail about mutual fund returns and on why point-to-point returns are misleading). A top-of-the-chart fund today can be much lower down later. Proportion of outperformance does away with point-in-time returns and looks at returns over different return timeframes and periods of time. Because you invest in a fund at various times, you want one that’s always (or nearly always) ahead of its benchmark and ahead of its category.
Consider ICICI Pru Midcap, whose 1-year return is about 86% right now, way above many mid-cap funds and 2 percentage points above the Nifty Midcap 150. But looking at this fund’s 1-year return over the past 3 years has it beating the mid-cap index just 62% of the time when the average for the mid-cap category is higher. But funds with a higher outperformance instances, such as Kotak Emerging Equity or Invesco Midcap at 86-88% are preferable.
It’s not just the benchmark that’s important, but the category as well. A fund that’s able to keep ahead of peers is also a quality one. This is important in debt funds, where benchmarks are not useful. Kotak Dynamic Bond, for example, beats its peer average virtually all the time. You can get the category outperformance in our category-wise mutual fund rolling return calculator.
Be careful: When taking the benchmark, consider the right one. Also take the relevant rolling return period to check for outperformance; an equity fund, for example, may show poor outperformance in short-term periods but be at the top of its game in longer-term periods.
Metric #5 – Alpha and beta
A fund’s beta is its volatility relative to its benchmark. A beta of more than 1 means that the fund can gain more on uptrends and fall more in corrections. A beta below 1 indicates the reverse. Alpha measures the excess returns a fund generates given its beta and what the market delivers. A fund is taking active calls in order to beat the benchmark, which is captured by its beta. Alpha measures how much over the market the fund is able to deliver, given this beta.
What it shows: Beta simply tells you if your fund is going to be one that you can count on to deliver really well on the upside and thereby push your returns up. High-beta funds that don’t do well during market upswings indicate that there’s something amiss in the fund’s strategy. High-beta funds are also better suited for more risk-taking investors. Alpha tells you whether the calls the fund is taking is paying off. The higher a fund’s alpha, the better it is.
Be careful: In both alpha and beta, the actual benchmark matters. For a fund that’s wildly deviant from its benchmark, both measures will not hold meaning as the fund’s performance is not related to the benchmark at all. These measures are also not of much use in debt funds or hybrid funds where benchmarks are either unrealistic or not actually aligned much with fund portfolios.