Does revenue momentum drive or ride earnings or price momentum?

This paper examines the profits of revenue, earnings, and price momentum strategies in an attempt to understand investor reactions when facing multiple information of firm performance in various scenarios. We first offer evidence that there is no dominating momentum strategy among the revenue, earnings, and price momentums, suggesting that revenue surprises, earnings surprises, and prior returns each carry some exclusive unpriced information content. We next show that the profits of momentum driven by firm fundamental performance information (revenue or earnings) depend upon the accompanying firm market performance information (price), and vice versa. The robust monotonicity in multivariate momentum returns is consistent with the argument that the market does not only underestimate the individual information but also the joint implications of multiple information on firm performance, particularly when they point in the same direction. A three-way combined momentum strategy may offer monthly return as high as 1.44%. The information conveyed by revenue surprises and earnings surprises combined account for about 19% of price momentum effects, which finding adds to the large literature on tracing the sources of price momentum.     

Are Momentum Profits Robust to Trading Costs?

We test whether momentum strategies remain profitable after considering market frictions induced by trading. Intraday data are used to estimate alternative measures of proportional and non-proportional (price impact) trading costs. The price impact models imply that abnormal returns to portfolio strategies decline with portfolio size. We calculate break-even fund sizes that lead to zero abnormal returns. In addition to equal- and value-weighted momentum strategies, we derive a liquidity-weighted strategy designed to reduce the cost of trades. Equal-weighted strategies perform the best before trading costs and the worst after trading costs. Liquidity-weighted and hybrid liquidity/value-weighted strategies have the largest break-even fund sizes: $5 billion or more (relative to December 1999 market capitalization) may be invested in these momentum strategies before the apparent profit opportunities vanish.     

Can exchange traded funds be used to exploit industry and country momentum?

There is overwhelming empirical evidence on the existence of country and industry momentum effects. This line of research suggests that investors who buy country and industry portfolios with relatively high past returns and sell countries and industries with relatively low past returns will earn positive risk-adjusted returns. These studies focus on country and industry indexes that cannot be traded directly by investors. This raises the question of whether country and industry momentum effects really can be exploited by investors or whether they are illusionary in nature because they exist only on non-tradable assets. We analyze the profitability of country and industry momentum strategies using actual price data on exchange traded funds (ETFs). We find that over the sample periods during which these ETFs were traded, an investor would have been able to exploit country and industry momentum strategies with an excess return of about 5 % per annum. These returns cannot be explained by unconditional exposures to the Fama–French factors. The daily average bid-ask spreads on ETFs are substantially below the implied break-even transaction cost levels. Hence, we conclude that investors who are not willing or able to trade individual stocks may use ETFs to benefit from momentum effects in country and industry portfolios.     

Price and earnings momentum: An explanation using return decomposition

We explain price and earnings momentum by investigating dynamics of cash flow (CF) news and discount rate (DR) news. We find that before the holding period, winners experience higher DR news than losers, which makes winners display lower ex-ante expected returns than losers. Momentum returns come from the persistently higher CF news for winners as compared to losers both before and during the holding periods. The evidence favors a behavioral explanation that the market incorporates cash flow information too slowly, which drives momentum returns. In addition, we find that the DR news, in particular that of the momentum losers, drives the time-series profitability of momentum strategies. Furthermore, by comparing price momentum with earnings momentum, we show that the relative load on past CF news as compared to past DR news affects long-run portfolio performance.     

Industry momentum strategies and autocorrelations in stock returns

In this study, we examine the sources of profits to momentum strategies of buying past winner industry portfolios and selling short past loser industry portfolios. We decompose the profit into (1) own-autocovariances in industry portfolio returns, (2) cross-autocovariances among industry portfolio returns, and (3) cross-sectional dispersion in mean portfolio returns. Our empirical results show that the industry momentum effect is mainly driven by the own-autocorrelation in industry portfolio returns, not by return cross-autocorrelations or by cross-sectional differences in mean returns. Indeed, the industry momentum strategy generates statistically significant profits only when own-autocorrelations are positive and statistically significant. The evidence is consistent with several behavioral models (e.g. Journal of Financial Economics 45 (1998) 307; Journal of Finance 53 (1998) 1839; Journal of Finance 54 (1999) 2143) that suggest positive own-autocorrelations in stock returns and hence the price momentum.     

Momentum in weekly returns: the role of intermediate‐horizon past performance

Gutierrez and Kelly (2008) recently documented momentum in weekly returns. Using the Australian market as a setting, we find that stocks with high 1‐week returns exhibit a continuation in returns up to 1 year after a brief initial return reversal. However, after controlling for the intermediate‐horizon past performance, the continuation in returns after 1‐week returns disappears. These findings suggest that different past investment horizons contain separate information about price momentum and that intermediate‐term trends dominate short‐term trends in driving future returns. Overall, we show that understanding momentum over different horizons facilitates the design of more profitable trading strategies.     

On the Earnings and Price Momentum Strategies: Evidence from European Real Estate Firms

We test the performance and interaction between earnings and price momentum for European real estate companies by first making use of decile portfolios sorted on the previous 3- to 12-month returns, standardized unexpected earnings and a combination of both. Then, the relation is tested on a risk-adjusted basis employing a 3-factor asset pricing model and Fama and Macbeth (1973) cross-sectional regression analyses. Our analyses reveal several critical findings: (1) both price and earnings momentum are effective for European firms, the effect being stronger for the UK than EU firms; (2) unlike U.S. REITs, price momentum seems to dominate drift for European firms; (3) there is weak evidence for positive interaction between drift and price momentum, contrary to the U.S. evidence; (4) the performance of momentum strategies depends on the state of the economy, while controlling for systematic factors; (5) idiosyncratic risk of real estate property firms may influence the returns on drift and momentum factors.     

The 52-week high,momentum, and predicting mutual fund returns

George and Hwang (J Finance 59:2145–2176, 2004) have shown that the 52-week high share price carries significant predictive ability for individual stock returns, dominating other common momentum-based trading strategies. Based upon their results and other methods, this paper examines and compares the performance of three momentum trading strategies for mutual funds, including an analogous 1-year high measure for the net asset value of mutual fund shares. Strategies based on prior extreme returns and on fund exposure to stock return momentum are also examined. Results show that all three measures have significant, independent, predictive ability for fund returns. Further, each produces a distinctive pattern in momentum profits, whether measured in raw or risk-adjusted returns, with profits from momentum loading being the least transitory. Nearness to the 1-year high and recent extreme returns are significant predictors of fund monthly cash flows, whereas fund momentum loading is not.     

Informed trading,information uncertainty,and price momentum

In this paper we investigate the effects of informed trading (PIN) and information uncertainty in determining price momentum. We find that trading strategies based on buying high-uncertainty good-news stocks and shorting high-uncertainty bad-news stocks work well when limited to high-PIN stocks, while stocks with low-PIN do not exhibit price continuations, even when the uncertainty level of those stocks is high. In contrast, momentum returns are always significant for high-PIN stocks, irrespective of information uncertainty. Overall, we show that the informed trading effect is both independent of and stronger than that of information uncertainty in determining price momentum.     

Conducting event studies with Asia-Pacific security market data

We investigate the effectiveness of several well-known parametric and non-parametric event study test statistics with security price data from the major Asia-Pacific security markets. Extensive Monte Carlo simulation experiments with actual daily security returns data reveal that the parametric test statistics are prone to misspecification with Asia-Pacific returns data. Two non-parametric tests, a rank test [Corrado and Zivney (Corrado, C.J., Zivney, T.L., 1992, The specification and power of the sign test in event study hypothesis tests using daily stock returns, Journal of Financial and Quantitative Analysis 27(3), 465-478)] and a sign test [Cowan (Cowan, A.R., 1992, Non-parametric event study tests, Review of Quantitative Finance and Accounting 1(4), 343–358)] were the best performers overall with market model excess returns computed using an equal weight index.     

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.     

(Re-)Imag(in)ing Price Trends

We reconsider trend-based predictability by employing flexible learning methods to identify price patterns that are highly predictive of returns, as opposed to testing predefined patterns like momentum or reversal. Our predictor data are stock-level price charts, allowing us to extract the most predictive price patterns using machine learning image analysis techniques. These patterns differ significantly from commonly analyzed trend signals, yield more accurate return predictions, enable more profitable investment strategies, and demonstrate robustness across specifications. Remarkably, they exhibit context independence, as short-term patterns perform well on longer time scales, and patterns learned from U.S. stocks prove effective in international markets.     

Asymmetric dynamics of stock price continuation

This paper finds that the dynamics of stock price continuation are asymmetrical, in terms of both business cycles and past performances. During times of recession, stock returns are explained differently for past losers and winners; the level of credit quality dominates the return dynamics for extreme losers, while levels of information-based trading activity and information ambiguity contribute to winners’ medium-term returns. Such asymmetry is proposed as the source of insignificant profits achieved using conventional momentum strategies. On the other hand, in times of expansion, conventional asset pricing factors are found to affect stock returns with a dependence on the level of credit quality; this suggests that more profitable momentum strategies remain to be discovered.     

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 strategies in commodity futures markets

The article tests for the presence of short-term continuation and long-term reversal in commodity futures prices. While contrarian strategies do not work, the article identifies 13 profitable momentum strategies that generate 9.38% average return a year. A closer analysis of the constituents of the long–short portfolios reveals that the momentum strategies buy backwardated contracts and sell contangoed contracts. The correlation between the momentum returns and the returns of traditional asset classes is also found to be low, making the commodity-based relative-strength portfolios excellent candidates for inclusion in well-diversified portfolios.     

Price Momentum and Trading Volume

This study shows that past trading volume provides an important link between 'momentum' and 'value' strategies. Specifically, we find that firms with high (low) past turnover ratios exhibit many glamour (value) characteristics, earn lower (higher) future returns, and have consistently more negative (positive) earnings surprises over the next eight quarters. Past trading volume also predicts both the magnitude and persistence of price momentum. Specifically, price momentum effects reverse over the next five years, and high (low) volume winners (losers) experience faster reversals. Collectively, our findings show that past volume helps to reconcile intermediate-horizon 'underreaction' and long-horizon 'overreaction' effects.     

Pension Plan Funding and Stock Market Efficiency

The paper argues that the market significantly overvalues firms with severely underfunded pension plans. These companies earn lower stock returns than firms with healthier pension plans for at least 5 years after the first emergence of the underfunding. The low returns are not explained by risk, price momentum, earnings momentum, or accruals. Further, the evidence suggests that investors do not anticipate the impact of the pension liability on future earnings, and they are surprised when the negative implications of underfunding ultimately materialize. Finally, underfunded firms have poor operating performance, and they earn low returns, although they are value companies.     

Currency momentum strategies

We provide a broad empirical investigation of momentum strategies in the foreign exchange market. We find a significant cross-sectional spread in excess returns of up to 10% per annum (p.a.) between past winner and loser currencies. This spread in excess returns is not explained by traditional risk factors, it is partially explained by transaction costs and shows behavior consistent with investor under- and overreaction. Moreover, cross-sectional currency momentum has very different properties from the widely studied carry trade and is not highly correlated with returns of benchmark technical trading rules. However, there seem to be very effective limits to arbitrage that prevent momentum returns from being easily exploitable in currency markets.     

The 52-Week High and Momentum Investing

When coupled with a stock's current price, a readily available piece of information—the 52‐week high price–explains a large portion of the profits from momentum investing. Nearness to the 52‐week high dominates and improves upon the forecasting power of past returns (both individual and industry returns) for future returns. Future returns forecast using the 52‐week high do not reverse in the long run. These results indicate that short‐term momentum and long‐term reversals are largely separate phenomena, which presents a challenge to current theory that models these aspects of security returns as integrated components of the market's response to news.     

A new strategy using term-structure dynamics of commodity futures

The term structure of commodity futures is important information for traders and investors. Traditional term-structure strategies are static; they tend to use the slope of term structure at a given moment. Instead, our trading strategy uses the change of term structure and generates statistically significant return. It also produces significant abnormal return in excess of the traditional two factors, i.e. the returns from static-slope strategy and daily momentum. Thus, its return includes orthogonal information or excess return that standard static-slope and momentum strategies cannot explain. This suggests a novel risk factor in the asset class of commodity futures or robust trading opportunities.