How correlated are our Canada TSX and USA momentum strategies — overall, and specifically during the six largest drawdowns since 2000? Monthly returns, both net of costs and regime, 2000–2026.
Positive and real — not noise — but moderate. Not close to 1, and not close to 0 either: enough shared exposure to broad market and commodity cycles that the two aren't independent bets, but enough daylight that combining them does real diversification work (Section IV).
It moves a lot. Rolling 12-month correlation ranges from −0.73 to +0.85 (mean 0.34, std 0.32) across the sample, and is outright negative in 15.4% of 12-month windows. A single "the correlation is 0.35" number hides a genuinely unstable relationship — which is exactly why the rest of this article looks at specific periods instead of stopping here.
Both strategies carry a regime filter that moves them to 100% cash when their local index is below its moving average. During a drawdown, both books are very often sitting in cash at the same time — two flat, near-zero return streams will show high correlation with each other almost by construction, whether or not the underlying markets are actually moving together. Before trusting any crisis-period correlation number, we recompute it on "active" months only — months where at least one strategy had a real (>1%) move, excluding the both-parked-in-cash months that would otherwise inflate the number for free.
| Sample | N | Correlation |
|---|---|---|
| Full sample | 316 | 0.346 |
| Active months only (excl. both-cash) | 253 | 0.326 |
Close enough (0.346 vs 0.326) that the full-sample number isn't meaningfully inflated overall — but as Section III shows, the gap between the two matters a lot more inside individual short crisis windows, where the sample size is small enough for a couple of cash months to swing the number substantially.
Windows are standard, well-known drawdown periods, chosen by calendar date rather than detected algorithmically from either return series (so the choice of window isn't itself curve-fit to either strategy's results).
| Crisis | Months | Canada cum. | USA cum. | Corr (all) | Corr (active only) |
|---|---|---|---|---|---|
| Dot-com crash (2000–03 to 2002–10) | 32 | +32.9% | +14.5% | 0.549 | 0.545 |
| GFC (2007–10 to 2009–03) | 18 | −3.5% | +13.1% | 0.292 | 0.319 |
| US downgrade / Euro crisis (2011–05 to 2011–10) | 6 | −0.3% | −7.5% | −0.099 | 0.002 |
| Oil / commodity crash (2015–08 to 2016–02) | 7 | −0.6% | −11.0% | 0.660 | 0.783 |
| COVID crash (2020–02 to 2020–04) | 3 | −11.1% | −7.3% | 1.000 | n/a (1 active month) |
| 2022 bear market (2022–01 to 2022–10) | 10 | +34.4% | −0.5% | −0.655 | −0.868 |
COVID's "1.000" is not a real number — ignore it. Once cash months are stripped out, only one month in the entire three-month window had both strategies actually invested (Feb 2020). Correlation from a single data point is undefined, not perfect; the raw 1.000 is an artifact of two mostly-flat, mostly-cash series moving together in the one month they were both still invested, not evidence the strategies behave identically in a liquidity panic. We're showing it precisely so we can say this clearly, not to quietly drop the inconvenient case.
2022 is the standout real diversification case. −0.655 raw, and it gets more negative (−0.868), not less, once cash-timing is stripped out — this is genuine anti-correlated performance, not an artifact. Canada's commodity-heavy book was up +34.4% cumulative through a year that hammered US growth/tech names; USA's momentum book, concentrated in whatever was working (semiconductors and related names for parts of this window), was roughly flat. This is exactly the kind of year a combined book is built for.
The oil crash is the opposite lesson: correlation rose when it mattered. 0.660 raw, 0.783 active-only — both strategies were hit by the same 2015–16 global growth scare, just to different degrees (Canada roughly flat at −0.6%, USA down −11.0%). Diversification did not fully show up here. Worth remembering: the 2022 result above is a real pattern, not a guarantee that applies to every risk-off period.
Using the full 316-month sample, monthly rebalanced, no re-optimization over time (fixed weights throughout):
| Allocation | CAGR | Sharpe | MaxDD | Vol |
|---|---|---|---|---|
| 100% Canada | +37.0% | 1.39 | −24.5% | 24.6% |
| 70/30 (Canada/USA) | +33.8% | 1.46 | −21.6% | 21.1% |
| Max-Sharpe (74/26) | +34.2% | 1.46 | −21.4% | 21.4% |
| 60/40 | +32.5% | 1.43 | −22.4% | 20.6% |
| Min-Variance (53/47) | +31.6% | 1.39 | −23.0% | 20.5% |
| 50/50 | +31.1% | 1.37 | −23.3% | 20.6% |
| 100% USA | +23.3% | 0.79 | −33.2% | 25.6% |
50/50 is not on the efficient frontier here. 70/30 (Canada-heavy) beats it on every metric simultaneously — higher CAGR, higher Sharpe, and shallower MaxDD. This happens because Canada alone already has a better risk-adjusted profile than USA (Sharpe 1.39 vs 0.79); the math doesn't reward splitting evenly between a stronger and a weaker Sharpe just because the two are diversifying. 50/50 is an intuitive starting point, not an optimized one.