Traditional Momentum Strategies Research Articles

Trend salience, investor behaviours and momentum profitability

Trend extrapolation in financial markets has been well documented, however it is contentious as to which trends will be extrapolated or mean reverted. This paper examines whether investors are more likely to extrapolate trends that they perceive to be salient, thereby providing an empirical test of the behavioural models of momentum. We employ an investment strategy that exploits trend salience by considering both the magnitude and the persistence of recent return performance. Consistent with behavioural models of momentum, an investment strategy based on trend salience significantly outperforms traditional momentum strategies and is not explained by the four-factor model. The relative performance of the trend salience signal is robust across different investment horizons and size-sorted portfolios, although is time-varying; the strategy does not outperform momentum in “down” markets or periods of high volatility in the formation period where trends are more difficult to identify.

Reward-risk momentum strategies using classical tempered stable distribution

Abstract We implement momentum strategies using reward-risk measures as ranking criteria based on classical tempered stable distribution. Performances and risk characteristics for the alternative portfolios are obtained in various asset classes and markets. The reward-risk momentum strategies with lower volatility levels outperform the traditional momentum strategy regardless of asset class and market. Additionally, the alternative portfolios are not only less riskier in risk measures such as VaR, CVaR and maximum drawdown but also characterized by thinner downside tails. Similar patterns in performance and risk profile are also found at the level of each ranking basket in the reward-risk portfolios. Higher factor-neutral returns achieved by the reward-risk momentum strategies are statistically significant and large portions of the performances are not explained by the Carhart four-factor model.

Exploiting commodity momentum along the futures curves

This study examines novel momentum strategies in commodities futures markets that incorporate term-structure information. We show that momentum strategies that invest in contracts on the futures curve with the largest expected roll-yield or the strongest momentum earn significantly higher risk-adjusted returns than a traditional momentum strategy, which only invests in the nearest contracts. Moreover, when incorporating conservative transaction costs we observe that our low-turnover momentum strategy more than doubles the net return compared to a traditional momentum strategy.

Momentum strategy and credit risk

The article first focused on the traditional momentum strategies, and the distance-to-default of the KMV (Kealhofer, McQuown and Vasicek) model was later applied as the proxy of credit risk. Then, based on the credit risk, two factors January effect and business cycle were added to investigate the momentum effect on them and credit risk. Empirical results indicated that investment portfolios had the momentum effects by traditional momentum strategies. After the credit risk was added, when the high-credit-risk group applied the momentum strategies in the mid- and long-term holding periods, significant excess return occurred. For low- and medium-credit-risk groups, the momentum profits only exist in 36–months holding periods. In addition, when credit risk was taken as the basis, and the January effect was included, the study found that positive momentum profits only took place in the low- and medium-credit-risk groups in 36-months holding period. Finally, when credit risk was taken as the basis, and busines...

Reward-Risk Momentum Strategies Using Classical Tempered Stable Distribution

We implement momentum strategies using reward-risk measures as ranking criteria based on classical tempered stable distribution. Performances and risk characteristics for the alternative portfolios are obtained in various asset classes and markets. The reward-risk momentum strategies with lower volatility levels outperform the traditional momentum strategy regardless of asset class and market. Additionally, the alternative portfolios are not only less riskier in risk measures such as VaR, CVaR and maximum drawdown but also characterized by thinner downside tails. Similar patterns in performance and risk profile are also found at the level of each ranking basket in the reward-risk portfolios. Higher factor-neutral returns achieved by the reward-risk momentum strategies are statistically significant and large portions of the performances are not explained by the Carhart four-factor model.

Trend Salience, Investor Behaviors and Momentum Profitability

Trend extrapolation in financial markets has been well documented, however it is contentious as to which trends will be extrapolated or mean reverted. We examine whether investors are more likely to extrapolate trends that they perceive to be salient by examining an investment strategy that considers both the magnitude and the strength of the trend. Consistent with behavioral models of momentum, our investment strategy based on trend salience significantly outperforms traditional momentum strategies and is not explained by the Carhart [1997] four-factor model. The relative performance of the trend salience signal is robust across different investment horizons and size-sorted portfolios, although is time-varying; the strategy does not outperform momentum in down markets where volatility is high and salient trends are more difficult to identify.

Price Momentum Components: Evidence from International Market Indices

Simply splitting the traditional momentum portfolios into two components based on past long-term performance produces contrasting strategies. Early-stage momentum profits are larger than the traditional momentum strategy’s profits when applied to developed and emerging market indices. For emerging markets, recent winners that have poor long-term returns outperform recent losers with good long-term returns on an average annualized basis by 10.4 per cent per year. In contrast, recent winners outperform recent losers on an average annualized basis by only 6.1 per cent per year.

Eureka! A Momentum Strategy that Also Works in Japan

This article explores an alternative definition of momentum that is calculated using the idiosyncratic returns from market regressions. By removing the return component due to market beta exposure, this new definition of momentum reduces the volatility of momentum strategies and generates sizeable four-factor alphas. These results hold in a sample of 21 countries, in addition to U.S. data. Most interestingly, the findings also hold in Japan, where previous studies have failed to find any significant power for traditional momentum strategies.

Momentum – Reversal Strategy

Various theories have been presented to explain momentum and reversals in stock returns. Based on the model of Hong and Stein (1999), this paper creates a hybrid strategy to avoid the losses from the reversal phase. The risk-adjusted returns of the new strategy are significantly higher than those of the traditional momentum strategy. Moreover, the risk-adjusted returns of the new strategy cannot be fully explained by Carhart’s four-factor model. Such a finding is robust in different time periods and size quintiles. Overall, this paper exploits the interaction between heterogeneous investors and generates distinctive applications.

Style Investing, Comovement and Return Predictability

Barberis and Shleifer (2003) argue that style investing generates (a) comovement between individual assets and their styles, and (b) momentum and reversals in both style and asset returns. These predictions imply that one can use comovement to assess the impact of style investing on asset-level return predictability. We find that high comovement winner (loser) portfolios have significantly higher (lower) future returns than low comovement winner (loser) portfolios. The magnitude of the improvement in three-factor alphas from traditional momentum strategies is both statistically significant and economically important. Long-horizon reversals are also larger for high comovement portfolios. Our results suggest that style investing plays an important role in the predictability of asset returns.

Firm-specific attributes and the cross-section of momentum

This paper identifies observable firm-specific attributes that drive momentum. We find that a firm's revenues, costs, and growth options combine to determine the dynamics of its return autocorrelation. We use these insights to implement momentum strategies (buying winners and selling losers) with both numerically simulated returns and CRSP/Compustat data. In both sets of data, momentum strategies that use firms with high revenue growth volatility, low costs, or valuable growth options outperform traditional momentum strategies by approximately 5% per year.

Are Momentum Profits Robust to Trading Costs?

This paper tests whether momentum-based strategies remain profitable after considering market frictions, in particular price concessions induced by trading. Alternative measures of price impact are estimated and applied to alternative momentum-based trading rules. The performance of traditional momentum strategies, in addition to strategies designed to reduce the cost of trades, is evaluated. We find that, after taking into account the price impact induced by trades, as much as 5 billion dollars (relative to December 1999 market capitalization) may be invested in some momentum-based strategies before the apparent profit opportunities vanish. Other, extensively studied, momentum strategies are not implementable on a large scale. The persistence of momentum returns exhibited in the data remains an important challenge to the asset-pricing literature.