MOM-05 · Trend Following

Faber TAA

Meb Faber's Tactical Asset Allocation from 2007 paper. Simple rule: hold an asset only when price is above its 10-month (200-day) moving average. Equal weight across all assets in uptrend.

MomentumTacticalTrend

At a glance

Best onMulti-asset portfolios
Signal frequencyDaily
Typical holding periodMonths
Asset classesIndex, Commodity, FX
Markets tested1
Data through2026-11-10

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 1 of 1 markets.
  • Best market by Sharpe ratio: FABER-TAA (Sharpe 0.91, CAGR 9.0%).

Equity curve

0.701.171.632.102.57 201020122014201620182020202220242026
Faber TAA Equal-weight basket · FABER-TAA, 2010-01-04 → 2026-11-10, growth of 1

Score and risk profile

Arena Score: 54.8FABER-TAA, 5 years
Return quality · 30%50
Drawdown control · 25%50
Consistency · 20%50
Robustness · 15%50
Significance · 10%98

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

How it held up in sell-offs (FABER-TAA)

PeriodStrategyBuy & hold
Q4 2018 sell-off-13.3%-15.9%
COVID crash (Feb–Mar 2020)-3.0%-26.0%
2022 bear market+2.1%-4.4%
Market above its 200-day average (annualized) · 69%+5.4%+6.9%
Market below its 200-day average (annualized) · 31%+2.8%+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 (FABER-TAA)

CheckValue
Chosen parameters on their 3-year training windows (average Sharpe)0.56
Same parameters in the following 6 months, when traded (Sharpe)0.74
Default parameters over the same months (Sharpe)0.64
Parameter re-selections / changes28 / 8
Parameter settings with a positive Sharpe (full history)3 of 3
Sharpe across settings: worst / median / best0.55 / 0.60 / 0.71

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)

MarketCAGRBuy & hold CAGRSharpeMax drawdownBuy & hold max DDVolatilityArena Score
FABER-TAAFaber TAA9.0%13.8%0.91-11.6%-16.5%9.9%55

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.

FABER-TAA across time windows

WindowTotal returnCAGRSharpeSortinoMax DDWin daysTrades
1 year+23.3%23.3%1.782.47-8.9%59%5
3 years+55.3%15.8%1.522.07-8.9%58%18
5 years+54.2%9.0%0.911.16-11.6%54%33
Full history+113.4%4.6%0.620.76-17.0%51%101

Rules

Entry

Hold asset if Price > SMA(200)

Exit

Exit asset if Price <= SMA(200)

Indicators

200-day SMA for each asset

Inputs

MA_Period = 200 (10 months)

Position sizing

Equal weight across assets in uptrend

Risk controls

Full cash position when all assets below MA

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

  • From Meb Faber's 2007 SSRN paper
  • Extremely simple trend-following rule
  • Monthly rebalancing for practical implementation

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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