Stock Momentum Research Articles

Industry momentum and reversals in stock markets

AbstractAlthough price trends such as momentum and reversal patterns of stock prices are well established in the literature, little is known whether price patterns still hold at the international level. Using data from over 24,000 stock prices, the analysis forms international within and across industries portfolios for the EU and the Asia/Pacific regions and studies the presence of momentum and reversal patterns, compared with the typical benchmark, which is the U.S. market. Interestingly, it finds that both patterns are related to low capitalized firms. Price reversals appearing only at the short‐run validating the liquidity constraint assumption, while momentum holds for a longer period and is related to investors' underreaction. Finally, it finds that only a few sectors can predict the market as an indirect result of momentum. A trading strategy that builds on industries' portfolios own predictive ability beats the market. Overall, matching returns patterns from the national to the international level supports the presence of unobserved risk factors and behavioural biases.

Economic policy uncertainty and momentum

AbstractWe show that a news‐based measure of economic policy uncertainty (EPU) negatively forecasts momentum. A 1‐standard‐deviation increase in EPU is associated with a 1.11% decrease in risk‐adjusted momentum returns. The predictive power of EPU is robust after controlling for previously documented economic state variables and macroeconomic uncertainty. We provide an explanation for these results from the perspective of a fund flow‐induced trading mechanism and offer direct empirical support. The literature documents that momentum can be partially attributed to performance‐chasing mutual fund flows. We find that this flow‐induced mechanism functions more effectively in low EPU states, thereby generating stronger stock momentum.

Liquidity and the Strategic Value of Information

We offer a simple, intuitive and empirically useful expression quantifying the value of asset-specific information to a strategic trader. The value of information reflects the ratio of return volatility to price impact measured using a version of Kyle's lambda. While volatility and illiquidity are highly correlated, their ratio fluctuates markedly giving rise to considerable variation in the value of information over time and across stocks. Using high frequency data on US stocks, we find that the value of information rises dramatically during crises and on earnings announcement days, and falls at calendar year ends. Furthermore, the value of information is higher for large, growth, and momentum stocks. The most dramatic spikes in the value of information occur at the start of the COVID-19 pandemic and the financial crisis of 2008, when the Fed announces novel liquidity facilities. Such policy interventions aimed at improving liquidity may unintentionally increase the private incentives to collect information.

Momentum, asymmetric volatility and idiosyncratic risk-momentum relation: Does technology-sector matter?

This paper examines systematic differences in momentum, asymmetric volatility and the relationship of idiosyncratic risk to momentum in both hi-tech stocks and low-tech stocks for 5795 US stocks. The findings show that the stocks of high-tech firms generate greater momentum returns especially with regard to portfolios that have holding and ranking periods of less than 12 months. In most cases the momentum returns in the hi-tech stocks explain the symmetric response to good and bad news, though this response is asymmetric in the low-tech stocks. Finally, the relationship between idiosyncratic risk and momentum return is insignificant for high-tech stocks and significantly negative for low-tech stocks.

Overlapping Momentum Portfolios

Different momentum investors use different time horizons, or formation periods, to evaluate prior stock performance. We show that this heterogeneity has important consequences on asset returns. We provide evidence that heightened trading pressure due to the concurrence of the heterogeneous momentum investors contributes to enhanced return autocorrelation. In particular, U.S. overlapping momentum stocks - stocks that are in the intersection of the 6-month and 12- month momentum portfolios - display superior medium-term returns to the momentum strategy that neglects the overlap. The differential returns of the overlapping momentum portfolio are robust to the inclusion of a broad set of risk factors and interpretations. The results provide insights on the underlying mechanisms of under and over-reaction in financial markets as the result of limited information investment rules and slow information diffusion.

White lie effects of information asymmetry on stock momentum

This paper aims to explore the relationship between information asymmetry and stock momentum. Using winner and loser approach, we find that winners with exaggerated forecast of earnings per share are more likely to have contrarian profits in subsequent holding periods. On the contrary, winners with low or middle-low information asymmetry tend to continue their good returns in future holding periods. In addition, the losers with middle information asymmetry achieve the highest contrarian profits, which may be called “white lie effects.”

Is Factor Momentum More than Stock Momentum?

Yes, but only at short lags. In this paper we investigate the relationship between factor momentum and stock momentum. Using a sample of 72 factors documented in the literature, we first replicate earlier findings that factor momentum exists and works both directionally and cross-sectionally. We then ask if factor momentum is spanned by stock momentum. A simple spanning test reveals that after controlling for stock momentum and factor exposure, statistically significant Sharpe ratios only belong to implementations which include the last month of returns. We conclude this study with a simple theoretical model that captures these forces: (1) there is stock-level mean reversion at short lags and momentum at longer lags, (2) there is stock and factor momentum at all lags and (3) there is natural comovement between the PNLs of stock and factor momentums at all horizons.

Momentum Effect all over the World

This study is intended to reaffirm the existence and profitability of momentum investment strategies in 40 countries around the world during the period 1996–2018. The contradictory findings of previous research on the existence and profitability of momentum strategies have raised a pertinent question on the validity of efficient market hypothesis. We documented the momentum effect in 90% of our sample countries of which 52.5% exhibited positive momentum effect while 37.5% exhibited negative momentum effect. The findings were robust to two distinct sub-period analyses. The clear rejection of efficient market hypotheses is valuable to momentum traders and stock market regulators.

The Value-Momentum Correlation: An Investment Explanation

This paper shows that both value and momentum premia arise in a q-theoretic framework that considers optimal corporate policies under uncertain financing conditions. Book-to-market and past performance predict future returns because they serve as indicators of firm financing position. The book-to-market ratio increases with financing constraints, with high book-to-market firms investing less and demanding higher risk premia compared to unconstrained, low book-to-market firms. The value premium increases in bad times because value firms become even more constrained, while ample cash reserves allow growth firms to fare much better. Momentum effects appear among the most financially constrained firms. For these firms, financing constraints imply large price swings following cash-flow shocks and valuable equity market timing options imply positive autocorrelation in returns. Absent equity market timing during bad times, momentum disappears. The model is able to explain many empirical features of value and momentum premia, such as: (i) the procyclicality of the momentum premium, (ii) the countercyclicality of the value premium (iii) the negative correlation between the two, and (iv) severe losses to momentums strategies during market rebounds. Several new testable hypotheses arise regarding the fundamentals of value and momentum stocks. The empirical evidence is largely supportive.

Can tail risk explain size, book‐to‐market, momentum, and idiosyncratic volatility anomalies?

AbstractWe examine the impact of tail risk on the return dynamics of size, book‐to‐market ratio, momentum and idiosyncratic volatility sorted portfolios. Our time‐series analyses document significant portfolio return exposures to aggregate tail risk. In particular, portfolios that contain small, value, high idiosyncratic volatility and low momentum stocks exhibit negative and statistically significant tail risk betas. Our cross‐sectional analyses at the individual stock level suggest that tail risk helps in explaining the four pricing anomalies, particularly size and idiosyncratic volatility anomalies.

Unraveling Momentum's Moments

I examine the momentum anomaly through the prism of higher order risk neutral moments of high and low momentum stocks. I use option prices from 2002 to 2013 to extract time varying ex ante estimates of variance, skewness and kurtosis of high and low momentum stocks. High momentum stocks have lower variance, less negative skewness and lower kurtosis. This is in contrast to studies that use static, ex post estimates of skewness to explain momentum returns as a function of exposure to the higher order moments of the underlying return distribution. These results highlight that momentum returns can not be explained by ex ante estimates of higher order moments and remain dicult to resolve empirically in a rational expectations framework.

Extrapolative Factor Momentum

Stock factor returns exhibit greater predictability from the weighted least squares (WLS) estimator of autoregressions with time-varying volatility. The predictability transmits into superior mean-variance optimal portfolio performance that is hardly achieved by other strategies that utilize volatility timing and return predictability. This outperformance can be interpreted through an empirically weak factor risk-return relation. A WLS-based systematic factor long-short strategy subsumes the stock momentum factor, industry momentum and factor momentum, and produces sizable excess returns. The outperformance is not limited to particular ways of portfolio formation, which testifies that the WLS-based strategy fully exploits predictability.

How about selling commodity futures losers?

AbstractThis paper explores the benefits of extending the investment universe to commodity futures, from the perspective of momentum traders. We find that the growth‐optimal portfolio includes negative (positive) weights on commodity futures losers (stock winners). Motivated by this finding, we construct a joint momentum strategy, buying stock winners and selling commodity futures losers, and show that it generates an average monthly return of up to 1.91% and provides much lower skewness (0.04) and kurtosis (1.27) than a traditional stock momentum strategy. It also greatly improves profitability, especially in unfavorable market states, and thus effectively manages tail risk.

How do disposition effect and anchoring bias interact to impact momentum in stock returns?

Abstract We show that when the disposition effect and anchoring bias of investors reinforce each other, the momentum profit is strengthened. When the two effects offset each other, the momentum profit decreases or disappears. Second, stocks dominated by small investors, with low analyst coverage, and illiquidity issues show greater momentum profits in presence of these mutually reinforcing biases. Third, stock return in momentum strategy show reversal in the long run when they are affected by both anchoring bias and disposition effect consistent with prior literature.

Decomposing Momentum Spread

Since momentum arbitrage activity, buying winners and selling losers, effectively enlarges the return spread between these two groups, I find that the momentum spread (the difference of the formation-period recent 6-month returns between winners and losers) negatively predicts future momentum profit in the long-term, but not in the following month. I further decompose the momentum spread into the spreads of old or young momentum stocks based on whether a stock has been identified as a momentum stock for more than three months. I show that the negative predictability is mainly driven by the old momentum spread. For the top 20% of the sample period associated with the highest values of old momentum spread, the momentum reversals happen sooner (only six months after formation) and stronger (more than 120 basis points per month from month 7 to month 24 after formation), relative to negligible momentum reversals observed following the bottom 20% period with low old momentum spread. As these old momentum stocks are more likely to be exploited by arbitrageurs, these findings suggest that momentum is amplified by arbitrage activity and excessive arbitrage destabilizes asset prices and generates strong reversals.

Ethical investments and financial performance: An international evidence

This paper examines the financial performance of ethical funds in different regions and concludes that there is a cost attached to ethical investing. An analysis of 964 mutual funds comprising of Socially responsible funds (SRFs) and the Shariah-compliant equity funds (SCFs) suggests that: a) except for global funds, both types of funds underperform in the market, b) both types of funds are preferred for investment in growth and momentum stocks, c) SRFs are preferred for small capitalized stocks whereas SCFs do not follow any specific style or investment strategy, d) unlike SRFs, SCFs do not provide a safe haven for investors during crises. These findings are probably due to the lack of diversification opportunities and poor managerial skills. The results are robust to various asset pricing models and macroeconomic factors.

The fundamentals of momentum investing: European evidence on understanding momentum through fundamentals

AbstractThis paper tests Ahmed and Safdar's noise‐related fundamentals‐based explanation for the momentum premium in European equity markets. Consistent with the view that past price changes may be partially driven by noise, the future return behaviour of winners and losers is significantly dependent upon the degree to which past price performance is consistent with fundamentals. European momentum profits are concentrated among those firms where past price performance is congruent with fundamentals, but absent among those firms where past price performance is incongruent with fundamentals. The significantly different momentum premiums on congruent and incongruent fundamentals‐momentum strategies are attributable to the exploitation of existing mispricing among momentum stocks that can be ex ante identified using firm fundamentals.

Factor Momentum and the Momentum Factor

Momentum in individual stock returns emanates from momentum in factor returns. Most factors are positively autocorrelated: the average factor earns a monthly return of 1 basis point following a year of losses and 53 basis points following a positive year. Factor momentum explains all forms of individual stock momentum. Stock momentum strategies indirectly time factors: they profit when the factors remain autocorrelated, and crash when these autocorrelations break down. Our key result is that momentum is not a distinct risk factor; it aggregates the autocorrelations found in all other factors.

Investor Behavior in Manager Selection: Impact on Performance

Selecting managers on the basis of past performance is an intuitive strategy that seems trusted by investors. Indeed, many studies report a positive correlation between past fund returns and investor cash flows. Evidence also suggests that at least at shorter-term horizons investing with the top performing managers may generate future out-performance. This was initially dubbed the “smart money” effect, the idea that investors are capable of identifying manager skill. More recent studies suggest that manager exposure to momentum stocks, on one hand, and the persist-ency of fund flows, on the other hand, are the more likely explanations of the fact that past and future fund alphas seem to be positively correlated at shorter-term horizons in the pooled cross-section of funds. However, at longer-term horizons, e.g. over the standard investment evaluation horizon which is roughly three years for the average institutional investors, there is evidence of a negative correlation between past and future fund alpha. Managers with stronger performances seem more likely to under-perform subsequently over longer-term horizons. If there is mean reversion over the horizon of interest, then the modern hiring/firing practice should lead to worse outcomes than the apparently paradoxical strategy of investing in managers with poor performances and firing the successful ones. While such a contrarian approach to manager selection might seem counter intuitive and unreasonable, there is at least, a justification to it under this “dumb money” effect. A more practical approach consists on using other factors than performance for manager selection. Literature supports the use of factors such as the theoretical soundness of the “investment thesis” driving the fund’s strategy, the link between manager compensation and fund performance or the fund active share.

Separating momentum from reversal in international stock markets

Taking into account expected return characteristics like firm size and book-to-market in the selection of winners and losers helps to ex ante separate stocks with momentum from those that exhibit reversal in international equity markets. A strategy that buys small value winners and sells large growth losers generates significantly larger momentum profits than a standard momentum strategy, is robust to common return controls, and does not suffer from return reversals for holding periods up to 3 years. The superior performance of the strategy is attributable to a rather systematic exploitation of cross-sectional mispricing among momentum stocks.