Our Selection Process

The Objective of the portfolio is to have a basket of diversified AIF/PMS that endeavors to generate an alpha of at least 3%-5% p.a. over and above the respective Benchmark.

• We start with a universe of 350 open-ended AIF/PMS available for selection.
• We bifurcate the above schemes into 7-8 large categories like large/mid/small/hybrid and sector based funds 
• We apply category filters, like a minimum of 3-5 years of track record (few exceptions basis fund house) and a minimum AUM of Rs 100 crores.
• Selection of Quantitative Parameters: Out of some 15 key statistical parameters, we shortlist a few parameters by checking each parameter’s correlation with 1-year future returns over the last 10-12years.
• Based on the historical parameters, which had the best correlation with future returns basis, earnings of the portfolio have been shortlisted, and 1 futuristic parameter (PEG) has also been incorporated to understand the next 12-month potential returns.
• Qualitative Judgements are applied by the investment committee comprising of the CEO, Director-  Product Research, and Research Head.

We apply our In-house proprietary-based framework, which uses Price to Earnings ratio to arrive at the ideal market cap allocation for the model portfolio.

The following categories are considered.

We apply our In-house proprietary-based framework, which uses Price to Earnings ratio to arrive at the ideal market cap allocation for the model portfolio.

The following categories are considered.

Funds that invest at least 80% of their assets in top 100 companies.

Funds that invest at least 65-70% of their assets in companies ranked 101 – 250 as per *market cap.

Funds that can invest across market cap without any restrictions.

Funds that invest at least 65-70% of their assets in companies ranked below 250 as per *market cap.

The fund that can invest across the asset classes such as equities, debt, gold, and commodities

The fund that invests in a particular theme or sector.

• Stable AUM 
• Stability in the Fund Management
• Stability in the Stated Investment Objectives
• Consistency in Performance
• Process-driven and methodical approach
• Strong track record
• Investment manager’s pedigree and DNA
• Investment Style
• Qualification of Fund Manager
• Due diligence of the Fund Manager
  • AMC Leadership team track record
  • Fund Manager track record and analyst team support and experience.
  • Views of the fund manager to understand if his view matches AR view and his/her portfolio positioning.
  • His stock-picking capability is evaluated by calculating his ratio of going right versus wrong.

• There are 10-12 key statistical parameters basis which any funds can be evaluated.
• Checking the past track records of earnings and correlating the same with its performance
• How many calls have gone Right/Wrong Since the inception of the Portfolio
• After shortlisting these parameters, we re-ran the process to choose funds that would be selected basis these parameters. We checked which parameter’s output gave a maximum number of top quartile performers basis the next 1 year’s returns.

Parameter Name

• Information Ratio
• Sortino Ratio  
• Efficiency Ratio
• Down capture return
• Rolling return
• Loss Std dev
• Average Loss

• 3 parameters namely Efficiency Ratio, Downcapture returns and Rolling returns have helped us pick a maximum number of top quartile funds.
• Apart from historical parameters, we also picked a futuristic parameter that will logically help us arrive at schemes with a high future return potential and considering information ratio

1 Year Average Rolling Return for Last 3 Years

This ratio tells us the average return made by 24 different investors who invested for a 1-year investment period anytime in the last 3 years.

Down Capture Return

The ratio shows how the fund performed when the market delivered negative returns. This leads to selecting funds that fall less than the benchmark in the falling market condition and logically leads to outperformance over the benchmark.

Efficiency Ratio

This ratio tells us the return the fund delivers for every one percent of risk taken. Risk is measured in terms of standard deviation. Thus leading to the selection of funds with a better risk-to-reward ratio.

Information Ratio

The information ratio calculates a portfolio’s or financial asset’s risk-adjusted returns compared to a predetermined benchmark. This ratio intends to demonstrate excess returns compared to the benchmark and the reliability of the excess return generation. The tracking error is a metric for determining how consistently excess returns are produced.

Sortino Ratio

The Sortino ratio is a variant of the Sharpe ratio that uses the asset’s standard deviation of negative portfolio returns, or downside deviation, rather than the total standard deviation of portfolio returns to distinguish between detrimental volatility and overall volatility. The Sortino ratio divides the amount left over after deducting the risk-free rate from the return on an asset or portfolio by the asset’s downside deviation. Frank A. Sortino was honoured with the ratio’s name.