When collection is manual, coverage is set by analyst hours, not by the question being asked. We think that quiet limit shapes research conclusions more than most desks admit.
Ask a research or product team how they track the portfolio management industry and the answer is often a list: the same couple of dozen names, every month. The list was not chosen because the question needed it. It was chosen because that is how many managers an analyst could click through before the month got away.
We think this is one of the most common, least discussed limits in research work, and it is worth naming.
A SEBI Portfolio Manager Monthly Report has to be opened manager by manager, with several sub-reports each. Collecting the full universe by hand means thousands of page loads. So the team picks a subset. Usually it is the largest names, the direct competitors and whoever was interesting the year the list was made.
A bakery owner who only checks the prices of the three big chains nearby will understand the chains well, and will miss the small shop two streets away that is quietly taking the morning trade. The list is not wrong. It is just answering a narrower question than the one being asked.
| Question being asked | What a fixed list can miss |
|---|---|
| Where are flows going this year? | Smaller or newer managers gaining clients outside the list |
| How does our strategy rank? | Strategies that would sit above or below yours but were never collected |
| Is the industry growing in this segment? | Growth or decline concentrated among names nobody tracks |
| Who are our real competitors? | Whoever has emerged since the list was last revised |
Rankings are where this bites hardest. A strategy that looks mid-table among twenty-five tracked peers might look very different against every strategy that reported. Neither view is a recommendation about anything; the point is that the second is the honest denominator for a research comparison.
There are good reasons to focus on a subset. A team may only care about a particular segment. But that should be a choice made after seeing the whole universe, not a limit imposed by how long copy-paste takes. A few habits help:
When collection stops costing analyst hours, coverage stops being a constraint. That is the idea behind Terminal X. Its SEBI PMR agent works through every registered portfolio manager each month in parallel windows, with a live count of what is done, pending, in error or has no data filed. The PMS performance agent collects 1M to 3Y returns for every PMS strategy, discretionary and non-discretionary, stores them as numbers with the gap to Nifty 50 or Nifty 500, and keeps month-by-month history from April 2023. The desk can then filter to the names it cares about, starting from the whole list rather than a remembered one.
For the mechanics of building the returns dataset, see PMS returns vs benchmark: building the dataset. For what the regulatory report contains, see the SEBI PMR data guide.
If your competitive view has been the same list for years, it is worth asking whether the list reflects your question or your capacity. The answer is often the second. More on research data workflows is in the Terminal X guides.
This post is about research data workflows, not investment advice. For any investment decision, confirm with your adviser.
A list set by analyst time rather than the research question can miss smaller or newer managers, and makes rankings and trends depend on who was collected rather than who reported.
Its SEBI PMR agent collects every registered portfolio manager each month, and its PMS agent collects 1M to 3Y returns for every PMS strategy, with history from April 2023.
No. It is about research data coverage, not about which managers or strategies to choose. For investment decisions, confirm with your adviser.
See it on your own data. Terminal X — Filings and market data, collected. Book a 30-minute working session with an engineer.
