Time-series momentum 1-month · 16 asset ETFs (after Moskowitz, Ooi & Pedersen 2012, AQR)
Each asset's own past 1-month return predicts its next month (time-series momentum, documented across 58 futures markets by AQR researchers). Approximation: long-only on 16 ETFs, holding every asset whose 1-month return is positive, cash otherwise. Falsified if it fails to beat buy-and-hold on risk-adjusted terms.
Forward tracking started 2026-10-13. Results appear after 21 trading days.
Backtest
| Metric | Strategy | Benchmark |
|---|---|---|
| CAGR | 2.02% | 4.56% |
| Volatility | 12.38% | 12.83% |
| Sharpe | 0.22 | 0.41 |
| Max drawdown | -43.47% | -40.67% |
| Turnover (per year) | 6.60 |
Deflated Sharpe: 0.00 (n trials: 351) — the probability the Sharpe ratio is real after the number of variants tried.
Spec
{
"costs_bps": 10,
"end": "2025-12-31",
"rebalance": "M",
"side": "long",
"signal": {
"expr": "where(ret(21), ret(21), log(-1))",
"type": "expr"
},
"start": "2005-01-01",
"top_n": 16,
"universe": [
"SPY",
"QQQ",
"IWM",
"EFA",
"EEM",
"TLT",
"IEF",
"LQD",
"HYG",
"GLD",
"VNQ",
"TIP",
"AGG",
"EWJ",
"EWZ",
"FXI"
]
}Fork this strategy
Re-run it with your own changes. The fork is computed on the server and linked back here.
curl -X POST https://api.finzdata.com/v1/hub/s/time-series-momentum-1-month-16-asset-etfs-after-moskowitz-o-f9bd3d/fork \
-H 'Authorization: Bearer YOUR_KEY' -H 'Content-Type: application/json' \
-d '{"changes": {"signal": {"lookback": 126}}}'Or ask your AI assistant (Claude, ChatGPT, Cursor with the FinzData connector):
Fork the FinzData strategy time-series-momentum-1-month-16-asset-etfs-after-moskowitz-o-f9bd3d and test it with a 126-day lookback and 20 bps costs, then compare both runs.
Community
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