In a word, scientifically. Our 2018 recommendations are available at https://www.clearfunds.com/best-mutual-funds-2018


Our goal is to identify funds that are able to deliver sustainable performance across economic cycles and different market conditions. So we set out to design a data-driven predictive model that optimizes the 2-year returns on Equity Funds with minimal volatility. We started with the entire universe of mutual funds and applied a number of filters:

  • We selected only growth options, which are best suited from a tax perspective.
  • We limited our analysis to only diversified equity mutual funds — a mix of Large Cap, Flexi Cap and Mid & Small Cap funds helps investors achieve the required sector diversification, and avoids the volatility that comes with holding sector-specific funds.
  • We then eliminated funds which have been in existence for less than 3 years — we need a track record that the fund can be judged on.
  • To make sure that you can redeem your investments with minimal price impact when needed, we set the minimum size cut-off to Rs 500 crore for Large Cap funds and Rs 150 crore for all other funds.
  • Finally, while we will only recommend direct plans (see why), our analysis is on the regular plans as they have a longer history of data for our algorithm to run on.

Now for the hard work…
We collected all the possible data for these funds and threw this into a big-data statistical computing environment with one goal — to identify the factors that would determine 2-year performance. Our statistical model generated 30 possible factors resulting in more than a million data points.
After several iterations over several weeks (which turned into months), and innumerable cups of black coffee analysing longitudinal trends within the data, we were able to identify a number of factors that would predict 2-year outperformance. We recomputed these factors every two weeks going back in time to the inception of each fund, and back-tested this again, to ensure that the factors work across market cycles. The result is a sophisticated scoring algorithm that enables us to continuously identify optimal funds.