Risk–Return Classification of Mutual Fund Schemes across 46 Asset Management Companies: A Practice-Based Study at a Pune Distribution Firm

Author

Om Gajendra Mane


Abstract

 Purpose. To document how  a mutual fund distribution firm can screen a wide universe of schemes on risk and return together, and to show what a risk–return matrix built on live data reveals about scheme categories, evaluation horizons and suitability for different investor profiles.

Design. Practice-based study from a two-month on-the-job placement (25 May to 25 July 2026) at Sanchiit Investments Pvt Ltd, Pune. Scheme-level data for 784 entries across 46 asset management companies (AMCs) were compiled from AMC scheme documents, the NGEN and Felix Wealth platforms and AMFI/NSE/BSE sources, cleaned in Excel, and classified into four quadrants (low/high risk × low/high return) using standard deviation, CAGR and 1-, 3- and 5-year returns. A 136-entry illustrative subset is profiled in more detail.

Findings. Low Risk–Low Return was the largest quadrant (327 schemes, 41.7%) and High Risk–Low Return the smallest (107, 13.6%). In the illustrative subset the mean 1-year return ranged from −2.0% to 11.2% across quadrants, while the mean 3-year return ranged from 14.1% to 20.3%; of 46 entries with a negative 1-year return and a reported 3-year return, 28 (61%) had a 3-year return of 10% or more. Hybrid schemes were the most evenly spread across quadrants, and debt sub-categories differed in volatility. A directional reading of SEBI expense slabs suggests a cost gap of roughly 0.5 to 1 percentage point a year between large and small schemes in the same quadrant.

Originality. The study sits between academic theory, which seldom uses a large live dataset, and promotional factsheets, which show favourable metrics for one scheme. It applies one transparent classification logic to a wide cross-section of live schemes. Scheme data are secondary, one set of thresholds was fixed for all sub-categories and expense ratios were not compiled, so the matrix is a first-cut screen and not a cost-adjusted ranking or a recommendation.


Keywords

mutual funds; risk–return matrix; CAGR; standard deviation; scheme classification; investor suitability; India



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References


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