Mutual Funds Selection : Beyond Historical Returns

As I mentioned in my last article , around six months back I started giving shape and direction to my own portfolio , which till then was very haphazard and heterogeneous in its allocation. So to transform this haphazard asset allocation into a scientific allocation , I undertook below steps.

1. Deciding Asset Allocation - A balanced asset allocation across Mutual Funds (MFs) (45%) and Stocks (55%) was decided.Further allocation was done among Large, Small, Mid and Micro Cap in these two categories. This allocation was completely independent of existing portfolio, market conditions, economy data etc. 
   
2. Analyzing Current Portfolio  
• Segregating MFs into liquid/non-liquid based on their Close/Open ended period, Exit Load and Taxation 
• Identifying MFs from existing portfolio which are in sync with the Asset Allocation decided above 
• Selling/Switching MFs from existing portfolio which are not in sync with MF asset Allocation and are liquid 

Above two steps gave me a portfolio which was more synchronized with the decided Asset Allocation.What I had now was a bucket with some stones already in it and some more to be filled in. 
Now big question arises how did I decide which MFs and stocks to invest into or retain from existing portfolio. So lets dwell upon my selection methodology of MFs first. 

1. Selecting the Fund Houses - My filtering starts with filtering out those fund houses which are not backed by institutes of good repute and considerable legacy. So fund houses like Sahara makes an instant exit from the universe under consideration.  
2. Identifying Schemes - Jotting those schemes which are in sync with asset allocation from the selected fund houses only. So if I have not decided to have sector specific schemes, I will straight away ignore them.Similarly, if asset allocation is based on market cap only, schemes with market cap objective (like Small Cap Fund, Bluechip Fund etc.) only are selected
3. Collating Data - Compiling of data in a readable form which can be analysed easily ( in lay-man's language Excel) was completed. Data collected consisted of -

• Assets Under Management (AUM) - I generally prefer smaller AUM schemes , as they have more opportunities and lesser constraint to invest.
• Expense Ratio  - Theoretically lesser the Expense Ratio, better would be returns 
• Turnover Ratio - One should avoid higher turnover ratio schemes , as they imply lesser cohesion in investment approach. 
• Market Cap Allocation - Among Big, Small, Mid and Tiny cap stocks, so as to get better idea whether MF is Small/Mid or Large Cap oriented. I was surprised to know that even a supposedly Small and Mid Cap scheme had 25% Large Cap allocation.
• Historical Returns - 1 Year,2 Years, 3 Years and 5 Years Returns are collated
• Inception Date - To notice how old is the legacy of the fund 
• Exit Load - Funds with more liquidity and lesser Exit Load should be given preference 
• P/E Ratio - As with stocks, MF schemes with lower P/E ratio should be looked with favour
• Number of Stocks - MFs with higher number of stocks may suffer from over diversification 
• Ratios - (covered in detail in this Article)
• Alpha 
• Beta 
• Sortino Ratio 
• Standard Deviation 
• Sharpe Ratio 

Finally based on above data filtering of the mutual funds can be done to pare down the list to the exact number of MFs planned to be invested into. This framework reduced number of MFs held in my portfolio from 22 to just 6. 

Unfortunately in a country like India where financial literacy is more of a luxury, MFs are sold based on a very unscientific and single parameter of Historical Returns. I hope that above framework moves selection of MFs beyond Historical Returns and makes the process more holistic and hence more scientific. 

While MFs selection can be completed with the help of above framework only, Stocks selection involves a very comprehensive analysis of economy, industry, shareholders, and a lot many more parameters. Will be covering the same in our next article.