Time-varying expected momentum profits

This paper examines the time variations of expected momentum profits using a two-state Markov switching model with time-varying transition probabilities to evaluate the empirical relevance of recent rational theories of momentum profits. We find that in the expansion state the expected returns of winner stocks are more affected by aggregate economic conditions than those of loser stocks, while in the recession state the expected returns of loser stocks are more affected than those of winner stocks. Consequently, expected momentum profits display strong procyclical variations. We argue that the observed momentum profits are the realization of such expected returns and can be interpreted as the procyclicality premium. We provide a plausible explanation for time-varying momentum profits through the differential effect of leverage and growth options across business cycles.     

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.     

Feasible momentum strategies: Evidence from the Swiss stock market

While there is little controversy on the profitability of momentum strategies, their implementation is afflicted with many difficulties. Most important, chasing momentum can generate high turnover. Though there are already several attempts to make momentum strategies less expensive with respect to transaction costs, we go a step further in the simplification of momentum strategies. By restricting our sample to Switzerland’s largest blue-chip stocks and choosing only one winner and one loser stock, we find average returns to our momentum arbitrage portfolios of up to 44% p.a. depending on the formation and holding periods. While unconditional risk models are at odds with momentum profits, stock market predictability and time-varying expected returns explain a large part of the momentum payoffs, including the post-holding period behavior of the winner and loser stocks (overreaction and subsequent price correction).

Trading strategies based on past returns: evidence from Germany

Among the various strategies studied in this paper, only momentum investing appears to earn persistently nonzero returns: From 1965 to 2014, the classical momentum strategy based on performance over the previous 2–12 months earned an average return of 1.57% per month (excluding microcap stocks and value-weighted returns). In the most recent 10-year period, this return was even larger—2.27%—which is much larger than in the USA. However, profitability net of transaction costs is weak because the strategy involves trading in disproportionately small stocks with high transaction costs, something that is particularly true for the loser portfolio. A strategy that concentrates only on the winner portfolio and thus avoids potential problems associated with (short) selling the costly loser portfolio appears to earn strong and persistently abnormal profits, even after transaction costs.     

Slow diffusion of information and price momentum in stocks: Evidence from options markets

This paper investigates the source of price momentum in the stock market using information from options markets. We provide direct evidence of the gradual information diffusion model in Hong and Stein (1999): momentum profits are larger for stocks whose information diffuses slowly into the stock market. We exploit the options markets to identify stocks with slow information diffusion speed. As informed traders trade options to realize the information that has not been fully incorporated in the stock price, we are able to enhance the momentum strategy by selecting winner/loser stocks with high growth/large drop in call option implied volatility. Our empirical strategy generates a risk-adjusted alpha of 1.8% per month over the 1996–2011 period, during which the simple momentum strategy fails to perform. The results are robust to the impact of earnings announcement, transaction costs, industry concentration, and choice of options’ moneyness and time-to-maturity. Finally, our finding is not driven by existing stock- or option-related characteristics that are known to improve momentum.     

Is the Mean Return of Hotel Real Estate Stocks Apt to Overreact to Past Performance?

This study examines the return patterns of hotel real estate stocks in the U.S. during the period from 1990 to 2007.We find that the magnitude and persistence of future mean returns of hotel real estate stocks can be predicted based on past returns, past earnings surprise, trading volume, firm size, and holding period. The empirical evidence found from this paper confirms that short-horizon contrarian profits can be partially explained by the lead-lag effects, while in the intermediate-term price momentum profits and long-term contrarian profits can be partially attributed to the firms’ overreaction to past price changes. Our results support the contrarian/overreaction hypothesis, and they are inconsistent with the Fama-French risk-based hypothesis or the underreaction hypothesis. The study also confirms the earning underreaction hypothesis and finds the high volume stocks tend to earn high momentum profits in the intermediate-term. The study finds that the earning momentum effect for hotel stocks is more short-lived and smaller in magnitude than the market average. Price momentum portfolios (or contrarian portfolios) of big hotel firms underperform small hotel firms and the hotel price momentum portfolio (or contrarian portfolios) significantly underperform the overall market over the intermediate-term (or the long-term). These findings imply that the U.S. hotel industry, particularly the big hotel firms, have experienced relatively conservative growth in the sample period. It suggests that a conservative hotel growth strategy accompanied by an internal-oriented financing policy is proper in a period of prosperity.     

The timing of 52-week high price and momentum

We propose a new momentum strategy based on the timing of a stock’s 52-week high price. We find that the stocks that attained the 52-week high price in the recent past significantly outperform the stocks that attained the 52-week high price in the distant past. In particular, the top 10% of the stocks with the most recent 52-week high price outperform the bottom 10% of the stocks with most distant 52-week high price by 0.70% per month. Further, conditioning on the recency of 52-week high price significantly increases the profitability of momentum strategy based on the nearness of current price to the 52-week high price. Specifically, the average monthly return of this strategy is about twice as large for stocks with recent 52-week high price as compared with stocks with distant 52-week high price.     

Commodities momentum: A behavioral perspective

The growth in commodity-related investments has sparked interest in the performance of momentum strategies in these markets. This paper introduces a behavioral proxy of the 52-week high and low momentum that explains a significant proportion of the variation of conventional momentum returns after controlling for commodity specific risk factors. Our findings show that the 52-week high strategy generates significant profits after accounting for transaction costs. We report that the 52-week high strategy is a better predictor of returns than conventional momentum. Our findings suggest that term structure and hedging pressure risk factors provide only a partial explanation of the results.     

The 52-week high,momentum, and investor sentiment

This paper examines the link between the profitability of the 52-week high momentum strategy and investor sentiment. We hypothesize that investors' investment decisions are subject to behavioral biases when the level of investor sentiment is high, resulting in higher profits for the 52-week high momentum following high-sentiment periods. Our empirical results confirm this prediction. In addition, we find that the significant profit of the 52-week high momentum following high-sentiment periods persists up to five years. Further investigations show that the strong persistence of the 52-week high winners (losers) is concentrated in stocks with higher (lower) earnings surprises, especially during periods following high sentiment. Overall, our results provide supportive evidence for the anchoring biases in explaining the 52-week high momentum, especially when the role of investor sentiment is taken into account.     

The 52-week high momentum strategy in international stock markets

We study the 52-week high momentum strategy in international stock markets proposed by George and Hwang [George, T., Hwang, C.Y., 2004. The 52-week high and momentum investing. Journal of Finance 59, 2145-2176.]. This strategy produces profits in 18 of the 20 markets studied, and the profits are significant in 10 markets. The 52-week high momentum profits exist independently from the Jegadeesh and Titman [Jegadeesh, N., Titman, S., 1993. Returns to buying winners and selling losers: implications for market efficiency. Journal of Finance 48, 65-91.] individual stock and Moskowitz and Grinblatt [Moskowitz, T.J., Grinblatt, M., 1999. Do industries explain momentum? Journal of Finance 54, 1249-1290] industry momentum strategies. These profits do not show reversals in the long run. We find that the 52-week high is a better predictor of future returns than macroeconomic risk factors or the acquisition price. The individualism index, a proxy to the level of overconfidence, has no explanatory power to the variations of the 52-week high momentum profits across different markets. However, the profits are no longer significant in most markets once transaction costs are taken into account.     

Modelling momentum winner/loser asymmetry: the sources of winner and loser returns in the ASX200 and S&P500

There is an established body of work showing that the sources of momentum returns change over time. This paper finds that there is also winner/loser asymmetry – that the sources of the winner and loser components of momentum returns differ from each other at the same point in time. Together, these results raise concerns about the prospect of finding a single cause for momentum profits, as most efforts to date have tried to do. Rather, they indicate that investigation should proceed using time‐varying, nonparametric and ensemble techniques.     

Interaction of size,book‐to‐market and momentum effects in Australia

This study seeks to disentangle the effects of size, book‐to‐market and momentum on returns. Initial results show that each characteristic has a role in explaining returns, but that there is interaction between size and momentum, as well as between size and book‐to‐market. Three key findings emerge. First, the size premium is the strongest, particularly in the loser portfolios. Second, the value premium is generally limited to the smallest portfolios. Third, the momentum premium is evident for the large‐ and middle‐sized portfolios, but loser stocks significantly outperform winner stocks in the smallest size portfolio. When these interactions are controlled with multivariate regression, we find a significant negative average relation between size and returns, a significant positive average relation between book‐to‐market and returns, and a significant positive average relation between momentum and returns.     

Price behavior of small-cap stocks and momentum: A study using principal component momentum

This study analyzes why the negative momentum effect appears in Asian (China, Japan, Korea) stock markets, contrary to the U.S. market. We use principal component momentum (PMOM), a newly devised momentum measure. The PMOM is constructed by extracting commonalities from traditional momentum measures using principal component analysis. The results show evidence of positive and negative momentum profits in the U.S. and Asian markets, respectively. Negative momentum profits in Asian markets are attributable to the strong performance reversal of small stocks in the loser portfolio. Conversely, the positive momentum profits of the U.S. market are driven by the performance continuity of small stocks in the winner portfolio. The PMOM strategy is significantly more advantageous than traditional momentum strategies, based on the economic and statistical perspectives of momentum profits. These results are robust to changes in empirical designs.     

Short Sales Constraints and Momentum in Stock Returns

Abstract:   We show that stock characteristics identified by D'Avolio (2002) provide a reliable index of the mostly unobservable short sales constraints. Specifically, we find that this index is positively related to the level of short interest and to short selling costs implied by the disparity in prices in the options and stock markets, and is negatively related to future returns. Using this index, we show that the magnitude of momentum returns for the period 1984 to 2001 is positively related to short sales constraints, and loser stocks rather than winner stocks drive this result. We conclude that short sales constraints are important in preventing arbitrage of momentum in stock returns.     

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.     

Momentum strategies based on reward–risk stock selection criteria

In this paper, we analyze momentum strategies that are based on reward–risk stock selection criteria in contrast to ordinary momentum strategies based on a cumulative return criterion. Reward–risk stock selection criteria include the standard Sharpe ratio with variance as a risk measure, and alternative reward–risk ratios with the expected shortfall as a risk measure. We investigate momentum strategies using 517 stocks in the S&P 500 universe in the period 1996–2003. Although the cumulative return criterion provides the highest average monthly momentum profits of 1.3% compared to the monthly profit of 0.86% for the best alternative criterion, the alternative ratios provide better risk-adjusted returns measured on an independent risk-adjusted performance measure. We also provide evidence on unique distributional properties of extreme momentum portfolios analyzed within the framework of general non-normal stable Paretian distributions. Specifically, for every stock selection criterion, loser portfolios have the lowest tail index and tail index of winner portfolios is lower than that of middle deciles. The lower tail index is associated with a lower mean strategy. The lowest tail index is obtained for the cumulative return strategy. Given our data-set, these findings indicate that the cumulative return strategy obtains higher profits with the acceptance of higher tail risk, while strategies based on reward–risk criteria obtain better risk-adjusted performance with the acceptance of the lower tail risk.     

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.     

Understanding the nature of the risks and the source of the rewards to momentum investing

Buying recent winners and shorting recent losers guaranteestime-varying factor exposures in accordance with the performanceof common risk factors during the ranking period. Adjusted forthis dynamic risk exposure, momentum profits are remarkablystable across subperiods of the entire post-1926 era. Factormodels can explain 95% of winner or loser return variability,but cannot explain their mean return components are more profitablethan those based on total returns. Neither industry effectsnor cross-sectional differences in expected returns are theprimary cause of the momentum phenomenon.     

Momentum profits and time-varying unsystematic risk

This study assesses whether the widely documented momentum profits can be attributed to time-varying risk as described by a GJR-GARCH(1,1)-M model. We reveal that momentum profits are a compensation for time-varying unsystematic risks, which are common to the winner and loser stocks but affect the former more than the latter. In addition, we find that, perhaps because losers have a higher propensity than winners to disclose bad news, negative return shocks increase their volatility more than they increase those of the winners. The volatility of the losers is also found to respond to news more slowly, but eventually to a greater extent, than that of the winners.     

Momentum and Foreign Investors: Evidence from the Korean Stock Market

Abstract:

We examine whether the price impact of foreign investors on the Korean stock market from December 2000 to February 2007 generated a momentum phenomenon. In our empirical results, foreigners seem to have exerted a significantly positive impact on prices in “up” markets (periods of positive stock returns), but have had little impact on prices in “down” markets (periods of negative returns). We document that the impact of foreigners’ trades is concentrated in large companies. Most importantly, when the market is in the up state, the returns of stocks of large companies that were positively affected by foreign investors in the previous six-month period continue to increase in the subsequent six-month period. As a result, the subsequent six-month return on a past “winner” stock portfolio is significantly higher than that on a past “loser” stock portfolio. This brings to mind a momentum phenomenon that has been reported not to exist in the Korean stock market.