Do Industries Explain Momentum?

This paper documents a strong and prevalent momentum effect in industry components of stock returns which accounts for much of the individual stock momentum anomaly. Specifically, momentum investment strategies, which buy past winning stocks and sell past losing stocks, are significantly less profitable once we control for industry momentum. By contrast, industry momentum investment strategies, which buy stocks from past winning industries and sell stocks from past losing industries, appear highly profitable, even after controlling for size, book-to-market equity, individual stock momentum, the cross-sectional dispersion in mean returns, and potential microstructure influences.     

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-based return comovement

Similarly priced stocks move together. Stocks that undergo splits experience an increase in comovement with low-priced stocks and a decrease in their comovement with high-priced stocks. Price-based comovement is not explained by economic fundamentals, firm size, or changes in liquidity or information diffusion. The shift in comovement following splits is greater for large stocks, high-priced stocks, and when investor sentiment is high. In the full cross-section, price-based portfolios explain variation in stock-level returns after controlling for movements in the market and industry portfolios as well as portfolios based on size, book-to-market, transaction costs, and return momentum. The results suggest that investors categorize stocks based on price.     

On the relationship between concentration of prospect theory/mental accounting investors,cointegration, and momentum

We examine the role of cointegration between stock prices and their estimated fundamental values in return momentum. We find that the positive relationship between capital gains overhang and future stock returns in Grinblatt and Han (2005) is significantly stronger among the “non-cointegrated” group of stocks as compared with the “cointegrated” group of stocks. Further, for the cointegrated stocks, the slower the speed of adjustment to the cointegrating equilibrium, the greater (smaller) is the future return of stocks with unrealized capital gains (losses). These findings are robust to various firm characteristics including firm size, book-to-market ratio, past returns, idiosyncratic volatility, dispersion in analysts’ earnings forecasts, turnover, individual investor ownership, and industry returns.     

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.     

Is momentum trading profitable from Shari'ah compliant stocks?

This research offers fresh evidence supporting the pervasiveness of the momentum effect. Two decades after the momentum profitability firstly documented by Jegadeesh and Titman (1993), yet little research has been specifically devised for the momentum profitability on Shari'ah compliant stocks. We assess the momentum profitability over the Shari'ah compliant stocks in a Malaysian setting. We find evidence of strong return persistence as far as toward four-year holding period. Interestingly, no significant momentum returns are found among the conventional stocks. Upon further exploration we find neither an industry-driven momentum effect nor the small size firms can account for the momentum returns. Using return persistency formation criteria, we further find that underreaction seems to well fit in explaining this unique long lasting momentum profitability.     

Do Qualified Foreign Institutional Investors Herd in Taiwan's Securities Market?

This paper investigates whether and why qualified foreign institutional investors (QFIIs) in Taiwan herd when picking stocks. The evidence shows that QFIIs herd in Taiwan's securities market: They follow each other into and out of the same securities. We identify how the herding behavior forms and how it changes over time. The results suggest that there is an industry effect when QFIIs pick up stocks. They herd on securities classified in specific industries and also prefer stocks with high past returns as well as large firm size, supporting the argument that QFIIs are momentum traders. Characteristic herding and investigative herding explain QFIIs' trading behavior in Taiwan.     

Momentum,reversal, and the trading behaviors of institutions

We identify two types of momenta in stock returns—one due to returns relative to other stocks and one due to firm-specific abnormal returns, where abnormal is determined by a stock's idiosyncratic return variation. Despite similar performances over the first year, these momentum portfolios perform dramatically differently beyond year one. Relative-return momentum reverses strongly; abnormal-return momentum continues for years. This complexity in return momentum challenges the current theories of momentum. We propose that both momenta are consequences of agency issues in the money management industry and provide empirical support for this economic rationale of momentum in returns. Incentives induce institutions to chase relative returns and to underreact to firm-specific abnormal returns.     

Lead–Lag Effects in Australian Industry Portfolios

This study finds that returns to stocks with relatively high market capitalizations lead returns to stocks with relatively low market capitalizations in Australian industry portfolios. These lead–lag patterns or positive cross-correlations are found in both daily and weekly returns and continue to hold even after the market factor is removed. The results for weekly returns are consistent with the findings of Hou (Rev Fin Stud 20:1113–1138, 2007) who found significant lead–lag effects in weekly returns to US industry portfolios. However while that study found stronger lead–lag effects for industries with relatively small average market capitalizations this study finds that industries with larger average market capitalizations have stronger lead–lag effects. This may be caused by industry momentum created by positive news to the leader stocks of an industry, and implies investors can gain significantly by investing in the smaller firms of prominent industries, following an earlier shock to the corresponding leader stocks.     

Predicting stock returns

This paper studies whether incorporating business cycle predictors benefits a real time optimizing investor who must allocate funds across 3,123 NYSE-AMEX stocks and cash. Realized returns are positive when adjusted by the Fama-French and momentum factors as well as by the size, book-to-market, and past return characteristics. The investor optimally holds small-cap, growth, and momentum stocks and loads less (more) heavily on momentum (small-cap) stocks during recessions. Returns on individual stocks are predictable out-of-sample due to alpha variation, whereas the equity premium predictability, the major focus of previous work, is questionable.     

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).

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.     

Does Financial Distress Risk Drive the Momentum Anomaly?

This paper brings together the evidence on two asset pricing anomalies—continuation of prior returns (momentum) and the market mispricing of distressed firms—using UK data. Our analysis demonstrates both these effects are driven by market underreaction to financial distress risk. In particular, we find momentum is proxying for distress risk, and is largely subsumed by our distress risk factor. We also find, as with US studies, no evidence that size and book-to-market (B/M) effects in stock returns are linked to financial distress .     

Momentum strategies of German mutual funds

The existence of the momentum effect in stock returns has been documented for the US (e.g., Jegadeesh and Titman in J. Finance 48(1), 65–91, 1993) and many other national equity markets worldwide (e.g., Griffin et al. in J. Finance 58(6), 2515–2547, 2003). However, little is known about the active employment of momentum strategies among institutional investors outside the US. This paper provides first evidence of momentum behavior among German mutual funds. We find the fund trades to follow stock returns on an aggregated institutional level. Moreover, we detect significant momentum behavior among funds with a European and global equity focus, as well as among funds predominantly investing in Asia. In contrast, German funds do not seem to engage in momentum strategies when trading domestic stocks. While only half the funds in our sample trade in accordance with past returns, 66 % of the funds within the largest size quintile follow momentum strategies. Finally, we do not find momentum trading funds to outperform the other funds.     

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.     

Pricing assets with higher moments: Evidence from the Australian and us stock markets

This paper investigates the importance of higher moments of return distributions in capturing the variation of average stock returns for companies listed in the leading S&P US and Australian indices. We find that Australian stocks are more negatively skewed but less leptokurtic than US stocks. As a result, we find that co-skewness plays a more important role in explaining Australian returns while co-kurtosis is consistently influential for US stock returns. We postulate that the differences in results are related to the underlying firm characteristics of the companies in the two indices, where principally the Australian firms are noticeably smaller than their US counterparts and concentrated in a smaller number industry sectors. This implies that for many smaller exchanges around the world higher moment characteristics displayed by the US market may not be applicable. We also show our results are robust to partly explaining average stock returns in the presence of size, value, and momentum effects.     

Earnings and price momentum

This paper examines whether earnings momentum and price momentum are related. Both in time-series as well as in cross-sectional asset pricing tests, we find that price momentum is captured by the systematic component of earnings momentum. The predictive power of past returns is subsumed by a zero-investment portfolio that is long on stocks with high earnings surprises and short on stocks with low earnings surprises. Further, returns to the earnings-based zero-investment portfolio are significantly related to future macroeconomic activities, including growth in GDP, industrial production, consumption, labor income, inflation, and T-bill returns.     

Bad News Travels Slowly: Size, Analyst Coverage, and the Profitability of Momentum Strategies

Various theories have been proposed to explain momentum in stock returns. We test the gradual-information-diffusion model of Hong and Stein (1999) and establish three key results. First, once one moves past the very smallest stocks, the profitability of momentum strategies declines sharply with firm size. Second, holding size fixed, momentum strategies work better among stocks with low analyst coverage. Finally, the effect of analyst coverage is greater for stocks that are past losers than for past winners. These findings are consistent with the hypothesis that firm-specific information, especially negative information, diffuses only gradually across the investing public.     

Dissecting Anomalies

The anomalous returns associated with net stock issues, accruals, and momentum are pervasive; they show up in all size groups (micro, small, and big) in cross-section regressions, and they are also strong in sorts, at least in the extremes. The asset growth and profitability anomalies are less robust. There is an asset growth anomaly in average returns on microcaps and small stocks, but it is absent for big stocks. Among profitable firms, higher profitability tends to be associated with abnormally high returns, but there is little evidence that unprofitable firms have unusually low returns.