R-squared in mutual funds

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R-squared (\(R^2\)), or the coefficient of determination, measures the proportion of a mutual fund’s return variance that is explained by variance in its benchmark index. It ranges from 0 to 1 (or 0 to 100 per cent). An R-squared of 1.0 (100 per cent) means all return variation is explained by the benchmark; an R-squared of 0 means the fund’s returns have no statistical relationship with the benchmark.

R-squared is an essential companion to beta because beta is only a reliable predictor of fund behaviour when R-squared is high. A fund with a calculated beta of 1.20 but an R-squared of 0.40 cannot be relied upon to behave in line with that beta, much of its movement is independent of the benchmark.

Formula

R-squared is the square of the Pearson correlation coefficient \(r\) between fund and benchmark returns:

\[ R^2 = r^2 = \left[\frac{\text{Cov}(R_p, R_m)}{\sigma_p \times \sigma_m}\right]^2 \]

Equivalently, from the CAPM regression \(R_p = \alpha + \beta R_m + \epsilon\):

\[ R^2 = 1 - \frac{\text{SS}{\text{residual}}}{\text{SS}{\text{total}}} \]

Where \(\text{SS}{\text{residual}}\) is the unexplained variation and \(\text{SS}{\text{total}}\) is the total variation in fund returns.

A high R-squared means little residual variation (the regression line fits the fund returns well). A low R-squared means large residuals (the benchmark explains little about the fund’s day-to-day return fluctuations).

Interpretation

R-squaredInterpretation
85–100High correlation; fund closely follows the benchmark
70–85Moderate-high; some idiosyncratic exposure
50–70Moderate; significant non-benchmark risk
< 50Low; fund behaviour largely independent of benchmark

CAPM reliability threshold: Most practitioners treat R² below 0.70 as a threshold below which CAPM-derived statistics (beta, alpha) are unreliable. A beta computed with R² = 0.40 tells you little about how the fund will behave relative to the index.

Typical R-squared values in Indian mutual funds

CategoryTypical R-squared
Nifty 50 index fund0.98–1.00
Large-cap equity (actively managed)0.85–0.97
Flexi-cap equity0.80–0.95
Mid-cap equity0.75–0.92
Small-cap equity0.65–0.88
Sector fund (thematic)0.40–0.80 (depends on sector/benchmark match)
Aggressive hybrid0.70–0.90
Balanced advantage0.50–0.75
Arbitrage fundNear 0 (when benchmarked to equity; ~0.90 when benchmarked to liquid fund index)

Index funds have R-squared near 1.0 by construction. Sector funds can have very low R-squared against a broad market index because their returns are dominated by sector-specific factors.

R-squared and the closet indexing problem

R-squared is used to identify closet indexers, actively managed funds whose portfolio is so similar to the benchmark that their R-squared approaches the level of a true index fund (above 0.95–0.98), yet they charge active management fees. A closet indexer has:

These funds deliver index-like returns at active fund costs. The direct vs regular plan TER differential makes closet indexing in the regular plan particularly value-destructive.

R-squared for benchmark selection

R-squared is also a diagnostic for whether the right benchmark is being used. A fund with very low R-squared against its stated benchmark may be drifting from its mandate. For example:

  • A large-cap equity fund showing R² = 0.65 against Nifty 100 TRI should probably be investigated, it may have significant mid-cap or small-cap exposure.
  • An aggressive hybrid fund showing R² = 0.90 against a pure equity index may actually be holding very little fixed income despite its hybrid mandate.

SEBI’s category-and-benchmark rationalisation (October 2017, circular SEBI/HO/IMD/DF3/CIR/P/2017/114) was partly motivated by inconsistencies in fund behaviour relative to stated benchmarks, situations where R-squared analysis would have flagged the problem.

R-squared, beta, and systematic vs unsystematic risk

The decomposition of total risk (variance) into systematic and unsystematic components uses R-squared:

\[ \sigma_p^2 = R^2 \times \sigma_p^2 + (1 - R^2) \times \sigma_p^2 \]

More precisely:

\[ \sigma_p^2 = \beta_p^2 \times \sigma_m^2 + \sigma_\epsilon^2 \]

Where:

  • \(\beta_p^2 \times \sigma_m^2\) = systematic risk (explained by the market)
  • \(\sigma_\epsilon^2\) = unsystematic (idiosyncratic) risk
  • \(R^2 = \frac{\beta_p^2 \times \sigma_m^2}{\sigma_p^2}\) is the proportion of total risk attributable to the market

For a fund with R² = 0.90, 90 per cent of its variance is systematic (market-driven) and 10 per cent is fund-specific. For a thematic fund with R² = 0.45, only 45 per cent is market-driven.

Limitations

  • R-squared is sensitive to benchmark choice. The same fund will show different R-squared values against different benchmarks. Always verify that the benchmark used is the fund’s stated regulatory benchmark.
  • Period sensitivity. Rolling R-squared can shift significantly, a small-cap fund may show R² = 0.75 in a normal market and R² = 0.90 during a market panic when all stocks become highly correlated.
  • R-squared does not indicate performance quality. A high R-squared is not inherently good, it simply means the fund is benchmark-like. An index fund investor wants high R-squared; an active investor who is paying for stock-picking skill may expect lower R-squared.

See also

References

  1. Bodie, Z., Kane, A., and Marcus, A. J., Investments, 12th edition, McGraw-Hill.
  2. AMFI, Risk statistics methodology, amfiindia.com.
  3. SEBI circular SEBI/HO/IMD/DF3/CIR/P/2017/114 dated 6 October 2017, category and benchmark rationalisation.
  4. Morningstar India, R-squared data for Indian mutual funds, morningstar.in.
  5. Value Research, Fund analytics platform, valueresearchonline.com.

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