In the series of articles, we have covered everything regarding ETFs. It is time to select the best ETFs for your portfolio. If you are wondering how to select the most suitable ETFs, this article will help you understand it by applying all that you have learned in the ETF masterclass.
Selecting a suitable ETF involves a lot of analysis. Let’s try to simplify it for you.
At sharpely, we feel investors should follow the “portfolio first” approach. As a starting point, it is essential to define your objective and then identify assets that are best suited for your objective.
Once you have done that, you need to identify the set of ETFs that can best represent your assets.
Let us understand this with an example.
Suppose one of the assets in your portfolio is large-cap Indian equity. Your ETF universe to represent this asset is all the ETFs tracking the Nifty 50 index. You can also consider ETFs tracking Nifty Next 50, but let’s not complicate things here.
On the contrary, if you want medium-term corporate credit exposure, we cannot take the exposure directly, as there is no ETF tracking corporate credit. So, the next best thing one can do is choose between the Nippon India ETF (Nifty SDL Apr 2026) and the Bharat Bond 2025 ETF.
Once you have narrowed down the universe based on the fitment criteria, we now move on to evaluate the ETFs using 3 step selection framework.
A lot of ETFs in India are not liquid. This means that when you buy/sell them, you can potentially incur large transaction costs.
We need to make sure that the ETF has enough liquidity. Bid-ask spread and volumes are an obvious starting point. We need to choose ETFs that have narrow bid-ask spreads and large trading volumes. When considering trading volumes, one should look at the average trading volume over the past month (or 3 months) to eliminate the possibility of any recent spike in volume that may be transient.
As discussed in the blog on ETF Liquidity, it is also possible that even low-volume ETFs can have decent market depth due to the presence of active market makers. The presence of active market makers is the key. Make sure that the ETF has at least 2 active APs. This information can be found in the scheme information document.
ETFs track indices and try to replicate the returns of the underlying index. Ideally, we would want to hold ETFs with the lowest expense ratio. But we might have to trade off some cost for higher liquidity or lower tracking error.
Tracking error is the measure of divergence of performance of a portfolio (ETF in our case) with respect to a particular benchmark. In our blog on ETF tracking error, we made a distinction between “tracking error” and “tracking difference”. Tracking difference captures the actual difference in return with the benchmark (ETF return will almost always be less than the benchmark). Tracking error and tracking difference should be as low as possible.
Ideally, the tracking difference should be exactly equal to the expense ratio of the ETF. But generally, it is higher and, therefore, we need to look at tracking the performance of an ETF separately.
Now that we have all our metrics to evaluate and screen ETFs, we need a framework to make our selection. We will explain the framework with an example.
The first 2 metrics are filter criteria that help us narrow down our universe and should be applied sequentially.
Let’s say we want to invest in Indian banking stocks. Here is how we will proceed:
As we are planning to invest in Indian banking stocks, we will apply the filter of the benchmark. Here we select all ETFs tracking Nifty Bank Total Return Index (TRI).
As shown below, users can apply the benchmark filter in sharpely.
There are only 10 ETFs tracking the Nifty Bank TRI index.
Now we apply the liquidity screen. You can check the 1-month average daily turnover in (Rs. Cr) in sharpely. We have sorted them in descending order based on the turnover.
At this stage, we are almost certain that we will pick one of the top 4 ETFs. But we are not eliminating others just yet. If big divergences show up in expense ratio and/or tracking error, we will revisit these funds and do a secondary liquidity check (order-book depth).
It is quite possible that after 2 rounds of screening, you are left with only 1 option or worse, no option at all. In that case, you need to go back to Step 1 and find some other suitable proxies.
Now we will look at the expense ratio, tracking error, and tracking difference of these ETFs on sharpely.
These numbers throw up some interesting observations. Nippon India ETF Bank BeES is the clear winner. None of the other high-volume ETFs offer any significant advantages in terms of expense ratio or tracking performance.
But at the bottom of the table, we have Edelweiss Bank ETF which has a positive delta of 0.26% (5-year horizon) over Bank BeES. But it has a much higher tracking error and almost no volume (average daily volume over the past 1 month is Rs 0.01 Cr).
Below is the snapshot of the order book of Edelweiss Bank ETF.
Source: Zerodha
The market depth is very shallow. The bid-ask spread is huge and no shares are traded at the time of writing this (roughly 4 hours of trading). What’s more, the market price seems to be at a significant premium to NAV.
These are all screaming red flags. Lower tracking difference is simply not worth it. We should stick with Nippon India ETF Bank BeES.
The diagram below captures the iterative nature of the entire framework.
We will close this article (and the entire masterclass) by noting a few points that investors must keep in mind when transacting in ETFs.
That’s it! We bring this masterclass to an end. I hope you enjoyed reading it as much as we enjoyed writing it.
Defining your investment goals and risk appetite is the first step. This is important as selecting the best ETF involves a few steps like filtering based on fitment, liquidity, expense ratio, tracking error, and tracking difference.
iNAV or indicative Net Asset Value is the actual price of the ETF. It is calculated by dividing the total value of all securities in the ETF by the outstanding number of units.