Conventional momentum is a very well known anomaly; therefore, it is scrutinizingly studied. This strategy has been academically confirmed many times, but a lot of researchers have documented several momentum drawbacks. One important characteristic is that traditional momentum has substantial time-varying exposures to the classical Fama and French factors. Academic research shows that momentum loads positively (negatively) on systematic factors when these factors have positive (negative) returns during the formation period of the momentum strategy. As a consequence, a conventional total return momentum strategy experiences losses when the sign of the factor returns over the holding period is opposite to the sign over the formation period. One example is that negative market returns in the credit crises of 2008 caused the total return momentum to be tilted towards the low-beta segment of the market in early 2009. When the market recovered in the first quarter of 2009, the total return momentum’s negative market beta caused large losses. Luckily, the same academic research offers a solution. A residual momentum strategy based on residual returns estimated using the Fama and French three-factor model offers smaller time-varying factor exposures (which reduces the volatility of the strategy) and has a higher long-run average Sharpe ratio. A higher strategy consistency, large-cap investment universe, and a lower concentration in the extremes of the cross-section of stocks is an added bonus.

Fundamental reason

As it is mentioned in the “Description”, a residual momentum strategy uses the Fama and French three-factor model to remove the classical momentum strategy’s dependence on systematic factors. The residual momentum is closer to being factor neutral than total return momentum, which adds a lot of benefits.

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Markets Traded
equities

Financial instruments
stocks

Confidence in anomaly's validity
Strong

Backtest period from source paper
1926-2009

Notes to Confidence in Anomaly's Validity

Indicative Performance
9.18%

Period of Rebalancing
Monthly

Notes to Indicative Performance

per annum, data from table 8 for 12-1M residual momentum


Notes to Period of Rebalancing

Estimated Volatility
15.27%

Number of Traded Instruments
200

Notes to Estimated Volatility

data from table 8 for 12-1M residual momentum


Notes to Number of Traded Instruments

Estimated number of stocks in portfolio. We estimate that ~1000 stocks fulfill all criteria. Investor uses 2 deciles for investment.


Maximum Drawdown
0%

Complexity Evaluation
Complex strategy

Notes to Maximum drawdown

not stated


Notes to Complexity Evaluation

Sharpe Ratio
0.34

Simple trading strategy

The investment universe consists of all domestic, primary stocks listed on the New York (NYSE), American (AMEX), and NASDAQ stock markets with a price higher than $1. Closed-end funds, REITs, unit trusts, ADRs and foreign stocks are removed. The 10% largest stocks in terms of market capitalization are then selected for trading.

The residual momentum strategy is defined as a zero-investment top-minus-bottom decile portfolio based on ranking stocks every month on their past 12-month residual returns excluding the most recent month, standardized by the standard deviation of the residual returns over the same period. Residual returns are estimated each month for all stocks over the past 36 months using a regression model. The regression model is calculated every month for all eligible stocks using the Fama and French three factors as independent variables. The portfolio is equally weighted and rebalanced monthly.

Hedge for stocks during bear markets

Yes - Based on the source research paper (see Table 4), the strategy has a positive return during recession months (as defined by NBER); therefore, it probably can be used as a hedge/diversification to equity market risk factor during bear markets.

Source paper
Blitz, Huij, Martens: Residual Momentum
- Abstract

Conventional momentum strategies exhibit substantial time-varying exposures to the Fama and French factors. We show that these exposures can be reduced by ranking stocks on residual stock returns instead of total returns. As a consequence, residual momentum earns risk-adjusted profits that are about twice as large as those associated with total return momentum; is more consistent over time; and less concentrated in the extremes of the cross-section of stocks. Our results are inconsistent with the notion that the momentum phenomenon can be attributed to a priced risk factor or market microstructure effects.

Other papers
Huhn, Scholz: Alpha Momentum and Price Momentum
- Abstract

We implement a momentum strategy that ranks stocks based on their daily three-factor alpha. This strategy outperforms a conventional price momentum strategy in the U.S. and in Europe in terms of three-factor alphas and Sharpe ratios. The difference in the composition between these two strategies can be explained by differences in their factor-related return contributions during the ranking period. In addition, the alpha momentum strategy exhibits smaller dynamic factor exposures within the investment period. In further analysis we find that i) a hedge strategy based on factor exposures determined during the formation period only works for alpha momentum, ii) price momentum can be subsumed by alpha momentum but not vice versa, and iii) the three-factor alpha of momentum strategies based on “alpha only” stocks doesn’t reverse in the sixty months following the formation period.

Huij, Lansdorp: Residual Momentum and Reversal Strategies Revisited
- Abstract

In this note we revisit the 2011 and 2013 papers of Blitz, Huij, and Martens (BHM2011), and Blitz, Huij, Lansdorp, and Verbeek (BHLV2013) in which momentum and reversal strategies on residual returns are proposed. Our results indicate that the main findings of these studies, that residual momentum and reversal strategies exhibit significantly lower time-varying exposures to the Fama-French factors than conventional momentum and reversal strategies and consequently have significantly higher return-to-risk ratios, are robust across different global stock universes and out-of-sample periods after the publication of the first results.

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