MATH vs SPY: Correlation
Metalpha Technology Holding Limited (MATH) and SPDR S&P 500 ETF Trust (SPY) show a near-zero relationship: their 3-year correlation of weekly returns is 0.08.
Data as of 2026-08-27 · refreshed every trading day · weekly returns · methodology
How correlated are MATH and SPY?
On 3 years of weekly data the MATH/SPY correlation comes out at 0.08, near zero, meaning they move largely independently. The past 12 months show a tighter link (0.22) than the 3-year average (0.08). The 5-year figure is 0.13, and annualized covariance runs at 110.7 %².
Among the 14 assets we track against MATH, SPY ranks #8 by 3-year correlation. Their recent paths diverged sharply: over the last 12 months SPY outperformed by 91.3 percentage points (-70.7% for MATH against +20.6% for SPY). Risk is not evenly split, since MATH carries 6.2 times the volatility of the other side.
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.
MATH vs SPY: side by side
| MATH (Metalpha Technology Holding Limited) | SPY (SPDR S&P 500 ETF Trust) | |
|---|---|---|
| 1-year return | -70.7% | +20.6% |
| 5-year return | -40.4% | +82.4% |
| Volatility (ann.) | 90.1% | 14.5% |
| Beta vs S&P 500 | 0.53 | 1.00 |
| Max drawdown (3Y) | -81.9% | -18.8% |
| Market cap | – | – |
| P/E (trailing) | 41.7 | – |
| Dividend yield | 0.00% | 1.01% |
| Expense ratio | – | 0.09% |
| Assets under management | – | $795.3B |
| Sector / category | US Listed | ETF · US Large Cap |
SPY is a Large Blend fund from State Street Investment Management: $795.3B under management, 504 holdings, a 0.09% expense ratio, a 1.01% trailing dividend yield.
Year-by-year returns
| Year | MATH | SPY |
|---|---|---|
| 2022 | -57.4% | -18.2% |
| 2023 | +323.3% | +26.2% |
| 2024 | -47.2% | +24.9% |
| 2025 | +82.6% | +17.7% |
| 2026 | -60.3% | +13.7% |
Calendar-year price returns; the current year is year-to-date as of the data date above.
Are MATH and SPY good diversifiers for each other?
Yes. With a correlation of 0.08, MATH and SPY have moved largely independently, which makes them a genuinely diversifying pair by historical standards.
FAQ
What is the correlation between MATH and SPY?
Using weekly returns as of 2026-08-27: 0.08 over 3 years, with 0.22 over the last year and 0.13 over 5 years.
Is SPY a good diversifier for MATH?
Yes. With a correlation of 0.08, MATH and SPY have moved largely independently, which makes them a genuinely diversifying pair by historical standards.
What does a correlation of 0.08 mean?
On the −1 to +1 scale, 0.08 describes how much the two returns move together: +1 is lockstep, 0 is independence, negative values mean opposite directions. It says nothing about which performed better.
Use this data
$ curl https://www.pairbook.io/api/v1/pairs/math-vs-spy.json
Embed this badge (it refreshes with the data), with attribution:
[](https://www.pairbook.io/pair/math-vs-spy/)
Free with attribution; caching and terms are described in the API documentation.
Related comparisons
Hubs: MATH correlations · SPY correlations
