# Correlation Matrix

How closely funds move together, for diversification decisions.

Source data: AMFI daily NAV (17,900+ schemes) + Nifty benchmark indices. Last updated: 2026-07-02. Interactive tool: https://mfpro.tigzig.com

## Overview



The correlation matrix shows how closely the daily returns of different funds move together.
 A high correlation means two funds tend to go up and down on the same days. A low or negative
 correlation means they move independently - which is valuable for diversification.

 


## Formula


 
 Correlation(A, B) = Covariance(R_A, R_B) / (StdDev(R_A) × StdDev(R_B))
 

Where R_A and R_B are daily returns of Fund A and Fund B. The result is always between -1 and +1.


Computed using DuckDB's built-in **CORR()** aggregate function, which computes
 Pearson's correlation coefficient in a single pass over paired daily returns. Only trading days
 where both funds have valid returns are included (INNER JOIN on date).

 


## How to Interpret





- **+0.8 to +1.0 (dark green):** Very high correlation. Funds move almost identically. Adding both to a portfolio provides little diversification.

- **+0.5 to +0.8 (light green):** Moderate to high correlation. Common among funds in the same category (e.g., two large-cap funds).

- **0 to +0.5 (white/neutral):** Low correlation. Good diversification potential.

- **-0.5 to 0 (light red):** Slight negative correlation. Excellent diversification - when one falls, the other tends to hold or rise.

- **-1.0 to -0.5 (dark red):** Strong negative correlation. Rare in equity mutual funds. Typically only seen between equity and inverse/hedge instruments.


 


## Evaluation Period



Correlation is computed over the selected period (1Y, 3Y, 5Y, 10Y, Full, or Custom dates).
 Shorter periods show recent co-movement; longer periods give more stable estimates.
 Correlation can change over time - two funds that were uncorrelated in 2020 may become
 highly correlated in 2025 if market conditions change.

 


Example: 3 Funds


| | Large Cap A | Mid Cap B | Small Cap C |
| --- | --- | --- | --- |
| Large Cap A | 1.00 | 0.85 | 0.62 |
| Mid Cap B | 0.85 | 1.00 | 0.78 |
| Small Cap C | 0.62 | 0.78 | 1.00 |



Large Cap A and Mid Cap B (0.85) move very similarly - holding both adds little diversification.
 Small Cap C has lower correlation with Large Cap A (0.62) - a better diversification pairing.

 


## Important Notes





- Uses **daily returns** (percentage change in NAV), not NAV levels.

- Minimum 30 overlapping trading days required per pair.

- Benchmark index is always included for reference.

- Handles missing dates via INNER JOIN - only days where both funds traded are used.

- All Indian mutual funds share the same trading calendar (AMFI), so date alignment is rarely an issue. Index data from Yahoo may have minor gaps.

- Correlation does not imply causation - two funds may be correlated because they hold similar stocks, not because one drives the other.

## Related metrics

More Advanced Risk methodology from the MFPRO analytics tool:

- [Treynor Ratio](/mfpro/treynor-ratio)

- [Value at Risk (VaR) and CVaR](/mfpro/value-at-risk-cvar)

- [Skewness and Kurtosis](/mfpro/skewness-and-kurtosis)

- [Ulcer Index](/mfpro/ulcer-index)

- [Drawdown and Recovery](/mfpro/drawdown-recovery)

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Source: https://www.tigzig.com/mfpro/correlation-matrix