VIG vs XLV: Correlation & Overlap
How closely do Vanguard Dividend Appreciation ETF (VIG) and Health Care Select Sector SPDR Fund (XLV) trade together? Their weekly returns over three years give a correlation of 0.62, which is strong. The two funds also share 17.7% of their portfolios by weight.
Data as of 2026-08-27 · refreshed every trading day · weekly returns · methodology
How correlated are VIG and XLV?
Across a 3-year window, the weekly returns of VIG and XLV correlate at 0.62, strong. Lately the two have drifted apart, with the 1-year correlation at 0.48 versus 0.62 over 3 years. Stretching to 5 years gives 0.71, with an annualized covariance of 109.2 %².
By 3-year correlation, XLV places #53 of the 106 assets tracked against VIG. Over the last 12 months XLV came out ahead by 10.4 percentage points (+17.1% against +27.5%). On a rolling one-year basis the correlation drifted between 0.52 and 0.81, a moderate band.
How is this computed?
Pearson correlation on weekly returns: ρ(A,B) = cov(rA, rB) / (σA · σB), over windows of 52, 156 and 260 weeks. Covariance is annualized (×52) and expressed in %². Full definitions on the methodology page.
VIG vs XLV: side by side
| VIG (Vanguard Dividend Appreciation ETF) | XLV (Health Care Select Sector SPDR Fund) | |
|---|---|---|
| 1-year return | +17.1% | +27.5% |
| 5-year return | +64.0% | +37.4% |
| Volatility (ann.) | 11.9% | 14.7% |
| Beta vs S&P 500 | 0.74 | 0.42 |
| Max drawdown (3Y) | -15.0% | -17.1% |
| Dividend yield | 1.50% | 1.56% |
| Expense ratio | 0.04% | 0.08% |
| Assets under management | $130.9B | $41.7B |
| Sector / category | ETF · Dividend | Sector ETF |
On the fund side, VIG sits in the Large Blend category at Vanguard, with $130.9B under management, 333 holdings, a 0.04% expense ratio, a 1.50% trailing dividend yield. On the fund side, XLV sits in the Health category at State Street Investment Management, with $41.7B under management, 61 holdings, a 0.08% expense ratio, a 1.56% trailing dividend yield.
Portfolio overlap between VIG and XLV
The two portfolios partially overlap: 17.7% of the funds' weight sits in the same underlying holdings (22 common positions). Correlation tells you they move together; overlap tells you why.
| Common holding | Weight in VIG | Weight in XLV |
|---|---|---|
| LLY | 3.94% | 15.03% |
| JNJ | 2.68% | 10.38% |
| ABBV | 1.92% | 7.42% |
| UNH | 1.63% | 5.82% |
| MRK | 1.40% | 6.04% |
| AMGN | 0.90% | 3.80% |
| ABT | 0.80% | 3.17% |
| GILD | 0.70% | 2.94% |
| DHR | 0.53% | 2.17% |
| SYK | 0.49% | 1.82% |
| MDT | 0.48% | 1.89% |
| MCK | 0.45% | 1.72% |
| ELV | 0.35% | 1.40% |
| COR | 0.26% | 1.02% |
| CAH | 0.23% | 0.89% |
Largest positions held only by VIG: AVGO (4.65%), AAPL (4.47%), MSFT (4.35%), JPM (4.09%), XOM (2.80%). Only by XLV: TMO (3.76%), PFE (2.58%), VRTX (2.22%), BMY (2.20%), ISRG (2.10%).
Overlap = sum of the smaller of the two weights across common holdings, from issuer disclosures as of 2026-07-31. Top 15 common positions shown.
Year-by-year returns
| Year | VIG | XLV |
|---|---|---|
| 2022 | -9.8% | -2.1% |
| 2023 | +14.5% | +2.1% |
| 2024 | +17.0% | +2.5% |
| 2025 | +14.2% | +14.5% |
| 2026 | +11.6% | +11.8% |
Calendar-year price returns; the current year is year-to-date as of the data date above.
Are VIG and XLV good diversifiers for each other?
To a limited degree. At 0.62 the two still catch most of the same waves, so the pair smooths returns a little without insulating either from a shared selloff.
FAQ
What is the correlation between VIG and XLV?
The VIG/XLV correlation stands at 0.62 on a 3-year window (1 year: 0.48, 5 years: 0.71), computed from weekly returns as of 2026-08-27.
Is XLV a good diversifier for VIG?
To a limited degree. At 0.62 the two still catch most of the same waves, so the pair smooths returns a little without insulating either from a shared selloff.
How much do VIG and XLV overlap?
17.7% by weight, across 22 common holdings, based on issuer-disclosed portfolios as of 2026-07-31.
Use this data
$ curl https://www.pairbook.io/api/v1/pairs/vig-vs-xlv.json
Drop this badge in a README or notebook; it updates with the data:
[](https://www.pairbook.io/pair/vig-vs-xlv/)
Free with attribution; caching and terms are described in the API documentation.
Related comparisons
Hubs: VIG correlations · XLV correlations
