Guide · PMS data
PMS returns vs benchmark: how to build a clean, comparable dataset.
Comparing PMS strategies starts with data that is complete, stored as numbers and kept month by month. Most of the work is in the collection.
PMS strategy returns are published for periods such as one month to three years, for discretionary and non-discretionary strategies, alongside benchmarks such as the Nifty 50 or Nifty 500. A research team that wants to compare strategies needs those figures collected for every strategy and kept over time.
Fields to keep for each strategy and month
| Field | Why |
|---|---|
| Provider and strategy | Identify the series consistently over time |
| Discretionary or non-discretionary | Compare like with like |
| Returns by period (1M to 3Y) | Stored as numbers, not text |
| Chosen benchmark and its return | Same period, same basis |
| Gap to benchmark | Calculated, not typed |
| Month of the data and fetch time | So the history can be rebuilt |
Pitfalls
- Pulling filters one at a time and copying rows by hand, so some strategies are missed.
- Each new pull overwriting the last, so there is no history.
- Text values like “(3.2)” or “--” left as text and silently dropped by formulas.
- Comparing strategies against different benchmarks or periods.
Use it carefully
Published returns describe the past and depend on the methodology used to report them. A dataset like this supports research, product and distribution analysis; it is not by itself a basis for choosing an investment. See the SEBI portfolio manager data guide.
How Terminal X does it
Terminal X runs data agents on public market and regulatory sources for portfolio managers, brokers and research desks. Four standard agents cover the SEBI Portfolio Manager Monthly Report for every registered portfolio manager, PMS strategy performance from APMI against Nifty 50 or Nifty 500, NSE ETF liquidity, and Nifty strategy-index constituents. Each agent works the portal in a real browser with parallel windows, extracts every row and sub-report, turns text like “12.4%”, “(3.2)” and “--” into numbers or blanks, matches names by registration number or ISIN, reconciles counts, marks empty filings as “no data” rather than zero and compares each run with the last. Every record keeps its source, fetch time, run and previous version; layout changes at the source are reported, not swallowed. Results arrive as the same Excel export every time, a REST API and alerts on new data, and other sources can be added as custom agents.
This page describes data collection and research workflow only. It is not investment advice.
Questions
How do I compare PMS returns with a benchmark?
Collect each strategy’s returns for the same periods as the benchmark, store them as numbers, compare like with like and calculate the gap rather than typing it.
Why keep PMS performance data month by month?
Because each published view replaces the last; keeping dated history makes trends a filter instead of a reconstruction.
See it on your own data. Terminal X — Filings and market data, collected. Book a 30-minute working session with an engineer.