MACRO-01

Cross-Asset Momentum

Exploits lead-lag relationships between asset classes. Equity momentum can predict commodities; safe haven momentum signals risk appetite. Allocates based on cross-asset signals rather than own-asset momentum.

MacroCross-AssetLeading Indicator

At a glance

Best onDiverse asset pool with economic linkages
Signal frequencyDaily
Typical holding periodWeeks
Asset classesIndex, Commodity, FX
Markets tested1
Data through2026-11-10

What the backtest shows

  • Beat buy-and-hold on 1 of 1 markets by annual return over 5 years.
  • Had a smaller maximum drawdown than buy-and-hold on 1 of 1 markets.
  • Best market by Sharpe ratio: SPY (Sharpe 1.04, CAGR 11.3%).

Equity curve

0.721.652.583.514.44 2017201820192020202120222023202420252026
Cross-Asset Momentum Equal-weight basket · SPY, 2017-11-09 → 2026-11-10, growth of 1

Score and risk profile

Arena Score: 85.8SPY, 5 years
Return quality · 30%100
Drawdown control · 25%58
Consistency · 20%85
Robustness · 15%97
Significance · 10%99

Each bar is a percentile against every strategy on the same market and window (100 = best).

How it held up in sell-offs (SPY)

PeriodStrategyBuy & hold
Q4 2018 sell-off-6.7%-13.9%
COVID crash (Feb–Mar 2020)-15.9%-25.5%
2022 bear market-9.4%-9.1%
Market above its 200-day average (annualized) · 67%+12.5%+20.1%
Market below its 200-day average (annualized) · 33%+6.8%+8.7%

Sell-off dates follow the US stock market. Above/below the 200-day average uses the previous day's position, so there is no look-ahead.

Out-of-sample check (SPY)

CheckValue
Chosen parameters on their 3-year training windows (average Sharpe)1.27
Same parameters in the following 6 months, when traded (Sharpe)1.32
Default parameters over the same months (Sharpe)1.26
Parameter re-selections / changes12 / 4
Parameter settings with a positive Sharpe (full history)9 of 9
Sharpe across settings: worst / median / best0.96 / 1.06 / 1.11

Out-of-sample periods start on 2020-11-09. Training-window figures are flattered by picking the best of 9 settings; the out-of-sample figure is what the strategy actually earned. A large drop, or a result that depends on one setting, points to overfitting. How walk-forward testing works.

Results by market (5 years)

MarketCAGRBuy & hold CAGRSharpeMax drawdownBuy & hold max DDVolatilityArena Score
SPYSPDR S&P 50011.3%9.1%1.04-20.4%-25.1%10.8%86

Strategy metrics use daily returns without trading costs. Buy-and-hold figures are for the same market and window. Rows are sorted by Sharpe ratio.

SPY across time windows

WindowTotal returnCAGRSharpeSortinoMax DDWin daysTrades
1 year+6.4%6.4%0.750.94-9.0%54%251
3 years+74.4%20.4%1.912.65-9.0%58%750
5 years+70.9%11.3%1.041.46-20.4%55%1253
Full history+146.7%10.6%1.011.28-20.4%55%2223

Rules

Entry

SPY momentum positive -> long risk assets
GLD momentum positive -> defensive

Exit

Signals reverse

Indicators

SPY momentum -> predicts risk assets
GLD momentum -> signals risk aversion
Cross-correlations with lag

Inputs

Lookback = 21
Lag = 5
Threshold = 0

Position sizing

Based on signal strength

Risk controls

Volatility adjustment

Strategy evidence

Only available, validated bundles appear below. Missing evidence is not a passing validation result.

Evidence coverage

1 / 1 declared strategy–market pairs validated

Notes

  • Equity often leads commodities
  • Gold leads risk-off moves
  • Lag captures predictive relationship

Related strategies

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Backtests are historical simulations on daily data and do not include commissions or slippage. They do not guarantee future results and are not investment advice. See the methodology for how every strategy is tested.

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