Charlie
Investment Research
| Rank | Code | Fund Name | Avg Rolling Return ↓i | Rolling Return SD ↕i | Age ↕ |
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Buffett Indicator
Loading macro data...
Buffett Indicator
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Market cap / nominal GDP
All India Market Cap
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BSE
Nominal GDP
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MoSPI NAS
Methodology
A transparent look at how Charlie analyses and ranks mutual funds. Every number you see is backed by a rigorous, reproducible process.
Rolling Return Analysis
Instead of relying on point-to-point returns that are sensitive to start and end dates, Charlie computes rolling CAGR over your chosen investment horizon. This produces hundreds of overlapping return windows, giving a far more reliable picture of a fund's typical performance.
We then calculate the average and standard deviation of all rolling windows. A fund with a high average and low standard deviation has delivered strong, consistent returns.
Ranking Criteria
Average Rolling CAGR
The primary sort metric. Funds are ranked by their mean rolling annualised return across all available windows for the selected horizon (1Y, 3Y, 5Y, or 10Y).
Return Standard Deviation
Measures consistency. A lower SD means the fund's rolling returns cluster tightly around the average — less surprise, more predictability.
Fund Age
Older funds have more rolling windows, which makes their statistics more robust. Age is displayed so you can factor in track-record depth.
Benchmark Comparison
When you select a fund, Charlie overlays its cumulative return against the appropriate TRI benchmark (such as NIFTY 500 TRI, NIFTY 100 TRI, NIFTY Midcap 150 TRI, etc.) for that fund's category. The TRI includes dividends reinvested, providing a fair apples-to-apples comparison. Both series are rebased to 0% at the start of the chosen timeframe.
Buffett Indicator
The Macro Indicators tab surfaces the India Buffett Indicator — the ratio of total market capitalisation to nominal GDP. This is a broad valuation gauge popularised by Warren Buffett.
Market capitalisation is sourced from BSE, and nominal GDP from the Ministry of Statistics (MoSPI NAS). The indicator is refreshed periodically and cached for performance.
Data Sources
- NAV data — AMFI (Association of Mutual Funds in India) daily NAV feed
- Benchmark indices — Category-specific Nifty TRI indices (Nifty 500, Nifty 100, Nifty Midcap 150, Nifty Smallcap 250, etc.) via NSE / data providers
- Market Capitalisation — BSE India
- Nominal GDP — MoSPI National Accounts Statistics
Limitations & Disclaimers
Past performance does not guarantee future results. Charlie is a research tool, not investment advice. Rolling return statistics are only as good as the underlying NAV history — younger funds will have fewer data points and therefore less reliable averages. Always consult a qualified financial advisor before making investment decisions.
About Charlie
An independent, open research tool built to bring clarity and rigour to mutual fund investing in India.
Why Charlie?
Most mutual fund comparison tools show you point-to-point returns that can be misleading depending on when you look. Charlie takes a different approach: it uses rolling return analysis across every possible investment window to surface funds that have been consistently strong — not just lucky with timing.
The name "Charlie" is a nod to Charlie Munger, whose emphasis on rational analysis and long-term thinking inspires the way this tool is built.
What You Can Do
Rank Mutual Funds
Compare funds across categories — Multi Asset, Flexi Cap, Large Cap, Large and Mid Cap, Mid Cap, Small Cap, Multicap, and ELSS — using rolling CAGR over 1, 3, 5, or 10 year horizons.
Visual Fund Analysis
Click any ranked fund to see its full NAV history plotted against its category-specific TRI benchmark, with interactive timeframe controls and cumulative return overlays.
Macro Indicators
Track the India Buffett Indicator — a broad market valuation gauge — alongside the latest market capitalisation and GDP figures.
Fast & Cached
Charlie caches NAV data and macro indicators aggressively so repeat queries are instant. Cache status is always visible so you know how fresh the data is.
Tech Stack
Charlie is a lightweight, single-page application with a Python backend. The frontend is vanilla HTML, CSS, and JavaScript — no framework overhead. Charts are rendered with ApexCharts. The backend API handles data ingestion, caching, rolling-return computation, and macro indicator aggregation.
Open Source & Feedback
Charlie is built for transparency. If you spot an issue, have a feature idea, or want to contribute, feel free to reach out or open an issue on the repository. Investment research should be accessible to everyone.