How, in a nutshell, do momentum investing strategies work? In his December 2017 paper entitled “Keep Up the Momentum”, Thierry Roncalli summarizes the nature of the momentum premium in a less mathematical way than in the previously available “Understanding the Momentum Risk Premium: An In-Depth Journey Through Trend-Following Strategies”. He distinguishes between:
- Time-series or trend-following or intrinsic or absolute momentum (long assets with a positive past trend and short assets with a negative past trend).
- Cross-sectional or relative or winners-minus-losers momentum (long assets that have outperformed and short assets that have underperformed relative to each other).
Based on mathematical derivations and prior research, he concludes that:
- Momentum strategy performance depends on:
- Absolute value of asset Sharpe ratios.
- Pairwise correlations between asset returns.
- The length of the interval used to calculate momentum.
- Intrinsic momentum works best when pairwise asset correlations are zero, and hence makes sense for multi-class assets.
- Relative momentum works best with highly correlated assets, and hence works best for similar assets (such as regional stocks).
- Short-term momentum is riskier, has a lower Sharpe ratio and is more sensitive to the type of moving average employed than long-term momentum.
- In the long run, intrinsic momentum has low correlation with traditional asset classes due to averaging of high beta during bull markets and low beta during bear markets.
- Too much leverage can be harmful to momentum portfolios.
- One way to view intrinsic momentum (and perhaps long-only relative momentum) is as a beta strategy during good times and a diversification strategy during bad times.
In summary, theoretical analysis indicates that long-short intrinsic momentum applies best to asset classes and long-short relative momentum applies best to similar assets.
Note that long-only relative momentum may be more like intrinsic momentum than relative (winners-minus-losers) momentum.
Cautions regarding findings include:
- Findings derive from a simple model of momentum summarized in “Momentum Risk Premium Theory”. As noted there, this model is imperfect.
- As also noted there, findings do not account for implementation frictions/barriers, including:
- Using indexes as assets ignores implementation costs/fees of creating liquid funds that track the indexes. These costs/fees may vary considerably across asset classes.
- Monthly portfolio turnover may be high, generating additional material costs.
- Shorting may in some cases be costly/infeasible due to lack of assets to borrow for shorting. Using futures rather than underlying assets eliminates this concern, but momentum may work differently for futures versus underlying assets.
- The author does not address long-only momentum strategy variations.
