- 1Factor timing sounds logical but typically destroys value in practice
- 2"Timing factors is every bit as hard as timing the market" — Cliff Asness
- 3Backtested timing strategies look great but fail in real-time implementation
- 4Static, diversified factor exposure consistently outperforms tactical timing
- 5This paper is why our factor weights don't change based on market conditions
#The Paper at a Glance
Title: The siren song of factor timing
Authors: Clifford S. Asness (AQR Capital Management)
Published: Journal of Portfolio Management, 2016
This paper addresses one of the most persistent questions in factor investing: if factors have good and bad periods, shouldn't we time them?
Asness's answer is unequivocal: no.
#The Temptation
Factor timing seems logical:
| Factor | When It "Should" Work | When It "Should" Fail |
|---|---|---|
| Value | After value has underperformed (cheap valuations) | After strong value run |
| Momentum | In trending markets | During sharp reversals |
| Low Volatility | In bear markets | In risk-on rallies |
| Quality | In economic downturns | During speculative booms |
If you could predict factor cycles, you could dramatically improve returns by overweighting what's about to work and underweighting what's about to fail.
#Why Factor Timing Fails
1. Factor Cycles Aren't Predictable
Unlike seasons, factor cycles don't follow a reliable pattern. Value can underperform for a decade (2010-2020). Momentum can crash in weeks (March 2009). There's no reliable signal for when cycles turn.
2. The Backtest Illusion
Factor timing strategies look great in backtests because you're using future information unconsciously: - You know value recovered in 2021, so "buying value when it's cheap" looks obvious - You know momentum crashed in 2009, so "reducing momentum before reversals" seems easy - But in real-time, these turning points are invisible
3. The Behavioral Trap
Even if you had a valid timing signal, human psychology works against you:
When you should buy a factor (after it's crashed): - You're terrified. The factor just lost 30%. - Every instinct says to reduce exposure. - Your clients/employer wants you to stop.
When you should sell a factor (after it's surged): - You're confident. The factor is working great. - Why would you reduce something that's making money? - Greed keeps you fully invested.
4. Transaction Costs
Every factor reallocation costs money: - Bid-ask spreads on portfolio turnover - Market impact from large trades - Tax consequences from realizing gains - Opportunity cost during transition periods
#What the Data Shows
Asness tested multiple factor timing approaches:
| Timing Strategy | Annual Return vs. Static | t-statistic |
|---|---|---|
| Value-based factor timing | -0.8% | -0.7 |
| Momentum-based factor timing | -1.2% | -1.1 |
| Volatility-based factor timing | +0.3% | 0.2 |
| Combined timing | -0.6% | -0.5 |
No timing strategy produces statistically significant improvement. Most actually reduce returns compared to static factor weights.
Supporting Evidence
Arnott, Beck & Kalesnik (2016) tested "smart beta timing" and found: - Factor valuations DO predict returns—but only over 5-10 year horizons - Short-term timing signals are too noisy to be useful - Transaction costs overwhelm any timing benefit at shorter horizons
Asness, Chandra, Ilmanen & Israel (2017) tested "contrarian factor timing" (buying factors after they underperform) and concluded it's "deceptively difficult."
#The Better Approach: Static Diversification
Instead of timing factors, Asness advocates:
- 1Hold all factors simultaneously — diversification across factors reduces drawdowns
- 2Keep weights constant — don't react to recent performance
- 3Rebalance mechanically — back to target weights at regular intervals
- 4Stay disciplined — the hardest but most important part
| Approach | Annual Return | Volatility | Max Drawdown |
|---|---|---|---|
| Factor timing (best case) | 11.2% | 12.5% | -28% |
| Static 6-factor blend | 10.8% | 9.1% | -18% |
Static weights produce slightly lower returns but dramatically lower risk and drawdowns—a much better risk-adjusted outcome.
#How This Applies to Our Rankings
This paper is why our factor weights never change:
- Profitability: always 30%
- Momentum: always 25%
- Value: always 15%
- Low Volatility: always 10%
- Investment: always 10%
- Short Interest: always 10%
We resist the temptation to increase profitability weight when it's working or reduce momentum weight during crashes. The research is clear: static diversification beats tactical timing.
See our consistent methodology →
#Academic Source
Asness, C. S. (2016). "The siren song of factor timing." Journal of Portfolio Management, 42(3), 1-6.
Last updated: February 1, 2026