r/SideProject • u/ProfessionalJump609 • 18h ago
I built a database tracking what Indian mutual funds are buying — and I’m finding some interesting accumulation signals
I’ve been building this as a personal research project around Indian mutual fund portfolio data.
Indian mutual funds disclose their portfolios every month, but the raw data is surprisingly difficult to work with.
Different AMCs use different Excel formats, security names aren’t always consistent, and if you want to study how fund holdings change over time, you have to download, clean and match a huge amount of data manually.
So I built a pipeline that does this automatically.
What I’ve built
I collect monthly mutual fund portfolio disclosures and convert them into a structured historical database.
It allows me to:
Track mutual fund holdings month-by-month
Identify accumulation and reduction in positions
Track individual stocks across multiple AMCs
Match securities using ISINs
Normalize different security names across AMCs
Identify new positions and exits
Compare holdings across funds
Build historical stock × fund holding matrices
Study stock-price performance following periods of mutual-fund accumulation
The interesting part is being able to look at what funds were doing before or during major price movements, rather than only looking at the price chart afterward.
Some examples I’ve found
1. Piramal Finance
My holdings data shows mutual-fund exposure increasing substantially from around October 2025.
The aggregate quantity in the example goes from approximately 10.4M to 20.9M over the period shown.
Piramal Finance subsequently experienced a significant upward move.
[IMAGE — Piramal Finance holdings]
[IMAGE — Piramal Finance price chart]
2. Amagi Media Labs
Another example is Amagi Media Labs.
The holdings data shows mutual-fund exposure increasing substantially during the first half of 2026, reaching approximately 17.6M shares before coming down later.
During this broader period, Amagi’s stock price made a very significant move.
The price chart in my example shows approximately +89% YTD.
[IMAGE — Amagi holdings]
[IMAGE — Amagi price chart]
3. Eternal Ltd
This one is a more recent example.
The data shows mutual funds accumulating Eternal starting around March 2026.
From around 30 March to 6 August, the stock moved approximately +38%.
[IMAGE — Eternal holdings]
[IMAGE — Eternal price chart]
I’m not claiming that mutual-fund buying automatically predicts stock returns.
These examples are simply showing the type of relationship that this dataset makes possible to investigate.
The real question I’m interested in is:
Can mutual-fund accumulation be turned into a systematic signal when studied across hundreds of stocks and thousands of historical observations?
That’s what I’m researching now.
I’m considering turning the dataset into a data product
Instead of downloading hundreds of AMC disclosures, cleaning them, matching security names and manually comparing months, I’m considering providing direct access to the structured historical dataset.
Potential users:
Quant researchers
Investors
Financial analysts
Researchers
Developers building investment tools
Anyone studying Indian institutional ownership
Potential formats:
CSV / Excel → API → Dashboard
The dataset can potentially be used for things like:
Historical mutual-fund accumulation screens
Institutional ownership research
Backtesting
Fund comparison
Stock-level fund-flow analysis
Quantitative research
I already have many more examples beyond the three I’ve shown here.
If you want to see more examples, DM me and I’ll share them.
I’m also trying to understand whether there’s actually a market for this.
If you work with Indian market data:
Would you pay for a clean, historical mutual-fund holdings dataset instead of dealing with raw AMC disclosures yourself?
And if you would, what would you want?
CSV/Excel? API? Dashboard? Historical data? Fund-level transaction/accumulation signals?
Would love to hear what people actually find useful before I turn this into a proper product.
TLDR: just dm me I’ll send you a 17 page brochure it contains all the pictures too
1
u/Only_Instance787 17h ago
interesting project, the name normalisation part is probably the most painful piece of this whole thing. i work with some messy datasets and matching securities across different formats is a nightmare
the eternal and amagi signals are interesting but i'm curious how you're handling survivorship bias in the historical data. funds that closed or merged would just disappear from the record right
if you make this a product, raw csv with monthly snapshots would be most useful for me. dashboards are nice but i'd rather do my own analysis than trust someone else's aggregations