Asset Class Rotation
Classic momentum rotation strategy. Ranks assets by recent returns and allocates to the strongest performers. Uses multi-timeframe momentum and absolute momentum filter.
At a glance
What the backtest shows
- Beat buy-and-hold on 0 of 1 markets by annual return over 5 years.
- Had a smaller maximum drawdown than buy-and-hold on 0 of 1 markets.
- Best market by Sharpe ratio: ROTATION (Sharpe 0.68, CAGR 12.9%).
Equity curve
Score and risk profile
Each bar is a percentile against every strategy on the same market and window (100 = best).
How it held up in sell-offs (ROTATION)
| Period | Strategy | Buy & hold |
|---|---|---|
| Q4 2018 sell-off | -30.4% | -15.9% |
| COVID crash (Feb–Mar 2020) | -7.0% | -26.0% |
| 2022 bear market | -6.2% | -4.4% |
| Market above its 200-day average (annualized) · 69% | +8.5% | +6.9% |
| Market below its 200-day average (annualized) · 31% | +9.2% | +1.7% |
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 (ROTATION)
| Check | Value |
|---|---|
| Chosen parameters on their 3-year training windows (average Sharpe) | 0.64 |
| Same parameters in the following 6 months, when traded (Sharpe) | 0.67 |
| Default parameters over the same months (Sharpe) | 0.67 |
| Parameter re-selections / changes | 28 / 10 |
| Parameter settings with a positive Sharpe (full history) | 3 of 3 |
| Sharpe across settings: worst / median / best | 0.40 / 0.60 / 0.72 |
Out-of-sample periods start on 2013-01-04. Training-window figures are flattered by picking the best of 3 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)
| Market | CAGR | Buy & hold CAGR | Sharpe | Max drawdown | Buy & hold max DD | Volatility | Arena Score |
|---|---|---|---|---|---|---|---|
| ROTATIONAsset Rotation | 12.9% | 13.8% | 0.68 | -28.5% | -16.5% | 20.3% | 54 |
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.
ROTATION across time windows
Rules
Entry
1. Rank assets by momentum 2. Select Top N with positive momentum 3. Equal weight allocation
Exit
Monthly rebalance, drop assets with negative momentum
Indicators
N-month return for each asset
Inputs
Lookback = 126 (6 months) Top_N = 2 Absolute_Filter = True
Risk
Absolute momentum filter reduces drawdowns
Strategy evidence
- ROTATION · Inspect evidence 2026-11-10
Only available, validated bundles appear below. Missing evidence is not a passing validation result.
Evidence coverage
1 / 1 declared strategy–market pairs validated
Notes
- Adapts sector rotation concept to asset classes
- Monthly target decisions; synthetic daily-target accounting is applied by the engine
- Can go to cash if no positive momentum assets
Related strategies
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<a href="https://quantarenas.com/strategy/mom-04-asset-class-rotation/"><img src="https://quantarenas.com/badge/mom-04-asset-class-rotation.svg" alt="Asset Class Rotation Arena Score on Quant Arena" height="20"></a>
[](https://quantarenas.com/strategy/mom-04-asset-class-rotation/)
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.