Momentum Returns Research Articles

Momentum, Idiosyncratic Volatility and Market Dynamics: Evidence from China

Recent evidence on the relation between momentum and idiosyncratic volatility (IV) in the U.S. is mixed. We verify the relation between momentum and IV in China and find at best, no relation supporting the view that idiosyncratic risk is not a significant arbitrage cost for momentum returns. While the absence of a positive relation between momentum returns and IV rejects both the underreaction and the overconfidence and self-attribution stories of momentum, we find support for the overconfidence and self-attribution story from our results on market dynamics and momentum. Our results are robust when verified in other Asian markets. We also find support for the suggestion that cross-country differences in momentum returns could be the result of differences in market dynamics rather than differences in levels of individualism as suggested earlier in the literature.

Momentum, idiosyncratic volatility and market dynamics: Evidence from China

Recent evidence on the relation between momentum and idiosyncratic volatility (IV) in the U.S. is mixed. We verify the relation between momentum and IV in China and find at best, no relation, supporting the view that idiosyncratic risk is not a significant arbitrage cost for momentum returns. While the absence of a positive relation between momentum returns and IV rejects both the underreaction and the overconfidence and self-attribution stories of momentum, we find support for the overconfidence and self-attribution story from our results on market dynamics and momentum. Our results are robust when verified in other Asian markets. We also find support for the suggestion that cross-country differences in momentum returns could be the result of differences in market dynamics rather than differences in levels of individualism as suggested earlier in the literature.

Implied Volatility Changes as Evidence of Stock Price Disequilibrium

Past works have documented the predictive power of short-term stock return momentum and option volume ratios for future stock returns. In this article, the authors find option volume ratios have greater power to predict future returns when evidence exists that prices are out of equilibrium, proxied for by increases in implied volatility. In the studied sample, short-term momentum has significant power to predict future stock returns only in the presence of evidence prices are out of equilibrium. The authors document that option volume ratios, changes in option implied volatility, and short-term momentum together have significant predictive power for the cross-section of stock returns in subsequent periods. The difference between firms predicted to be strong performers and those predicted to be weak performers is more than 1% a month. Buy-and-hold returns for an equally weighted portfolio of predicted strong performers are 249% over the 1996–2009 period compared with a loss of 38% for predicted weak performers. S&P 500 Index returns over the same period were 60%.

Asset Pricing and Momentum: A South African Perspective

ABSTRACTBoth the capital asset pricing model and Fama and French’s (1993) three-factor model have consistently failed to explain momentum in stock returns, with only Carhart’s (1997) four-factor model having some success in this regard. This study examines whether an alternative three-factor model proposed by Chen, Novy-Marx, and Zhang (2011) and a five-factor model forwarded by Fama and French (2015), which both include profitability and investment as pricing factors, can explain momentum on the South African market. Consistent with international evidence, the pricing errors from these two models are lower and although these errors remain significant, the results reveal that profitability and, to a lesser extent, investment are important risk-based factors that must be considered in explaining the short-term continuation in stock returns.

Do Equity Analysts Help Diffuse Geographic Information?

We examine whether social interactions among local peers, defined as analysts working in the same brokerage office who cover different firms headquartered in the same area, communicate or garble information. We find that analysts with local peers produce more accurate earnings forecasts and their forecast revisions generate stronger stock market responses. Their forecasts are less optimistically biased and less affected by common errors in consensus forecasts. We also find that geographic momentum in stock returns is weaker when firms are followed by analysts with local peers, and that analysts are more likely to initiate coverage of firms with more local peers. These findings indicate that social interactions among local peer analysts can transmit useful information.

Common Macro Factors and Currency Premia

We study the role of domestic and global factors in the payoffs of portfolios mimicking carry, dollar-carry, and momentum strategies. Using factors summarizing large data sets of macroeconomic and financial variables, we find that global equity-market factors are predictive for carry-trade returns, whereas U.S. inflation and consumption variables drive dollar-carry-trade payoffs, momentum returns are predominantly driven by U.S. inflation factors, and global factors capture the countercyclical nature of currency premia. We also find predictability in the exchange-rate component of each strategy and demonstrate strong economic value for risk-averse investors with mean-variance preferences, regardless of base currency.

Where Has the Trend Gone? An Update on Momentum Returns in the U.S. Stock Market

Prior studies have found broad-based support for the efficacy of trading strategies based on momentum in stock returns. More recent studies, however, have noted a declining benefit relative to that identified in seminal studies on momentum. These recent studies, however, primarily examined time periods ending prior to or immediately following the 2008 financial crisis. Thus, we extend this line of research by exploring the profitability of momentum trading in the U.S. equity markets over the broader 1986 to 2015 time period. Our results for the earlier part of our sample period (i.e., 1986–2006) fall in line with previous studies, as we find a monotonic relationship between decile portfolios formed based on their prior six-month performance and subsequent twelve-month holding period excess returns. In contrast, when we evaluate more recent periods (i.e., 2007–2015 and 2010–2015), we find dramatically different results. In particular, alphas for the winner portfolio, which have historically been the highest, are actually negative during both subperiods. Furthermore, the curvature of the recent portfolio return distribution is clearly no longer monotonic. Rather, it follows a more inverted U-shaped curve from the winner portfolio (P1) to the loser (P10) portfolio, with excess returns cresting around the fifth decile portfolio (P5). In fact, we find that the risk-adjusted returns of the winner portfolio (P1) are significantly less than those of the middle portfolio (P5) for both recent subperiods. These results suggest that individual and institutional investors seeking to profit from traditionally based momentum trading strategies may need to rethink their approaches.

Stock Price Reaction to News: The Joint Effect of Tone and Attention on Momentum

ABSTRACTThe authors find that the market's underreaction to good news is a driver of Gutierrez and Kelly's [2008] weekly momentum returns. By employing a dataset of 10.1 million news items in 4 regions (the U.S., Europe, Japan, and Asia Pacific), they find that stocks having important and positive news exhibit stronger return continuation. The study findings suggest that investors in international markets have similar underreaction to the same news characteristics.

Conditional Skewness in Asset Pricing Tests

If asset returns have systematic skewness, expected returns should include rewards for accepting this risk. We formalize this intuition with an asset pricing model which incorporates conditional skewness. Our results show that conditional skewness helps explain the cross-sectional variation of expected returns across assets and is significant even when factors based on size and book-to-market are included. Systematic skewness is economically important and commands a risk premium, on average, of 3.60 percent a year. Our results also suggest that the momentum effect is related to systematic skewness. The low expected return momentum portfolios have higher skewness than high expected return portfolios.

Market Volatility and Momentum: Evidence from Pakistani Stock Exchange

This study explores the relationship between market volatility and momentum profitability. This study indicates that market state volatility has significant power to forecast momentum payoffs, especially in negative market states. The results are the context in the presence of market state and business cycle variables. Market premium is significant and negative. Market volatility is also found negatively influencing momentum profits. Volatility is divided into volatility in the positive market and volatility in the negative market. Both are significantly and negatively influencing momentum profits. Vol+ and Vol- both have negative signs; Vol- is dominant in terms of the magnitudes of the coefficient and the t-statistics. Business cycle effect measured by term and yield is not found significant. Non-linearity has not been observed regarding the term. Results are found robust for market adjusted momentum payoff. The study also explores the impact of market state, volatility and business cycles on the return of loser and winner portfolio. This study reports that returns of the loser portfolios are explained by market component, whereas volatility is found to be insignificant. The macroeconomic variables TERM, TERM2 and YLD show signs of statistical significance. Market factor is significantly and positively influencing winner portfolios. The results indicate that volatile markets forecast low returns on winner stocks. Return dispersion used to measures cross-sectional is also found significant. The study recommends that investors should devise investment and momentum strategies on the basis of the volatility of stocks and the business cycle. The tests of this study show that volatile down markets forecast low momentum payoffs. The time-series predictability of momentum is asymmetric, which arises from loser stocks.

Momentum strategies in European equity markets: Perspectives on the recent financial and European debt crises

We investigate the profitability and return patterns of momentum strategies in 10 European countries. Using data from December 2003 to December 2015, we find momentum returns to be lower than to those reported in previous research. Our results indicate that the low momentum returns can be attributed to market conditions during the period of 2007–2012. When examining momentum returns generated by small and large stocks in separate time periods, we find momentum returns to be stronger among small stocks and weaker in large stocks.

The Behavior of Investor Flows in Corporate Bond Mutual Funds

This paper provides a comprehensive examination of money flows in corporate bond funds, which, although less researched, represent an important setting to study investor behavior. Based on a large sample of corporate bond funds over 1991–2014, we first show that flows are sensitive to both fund performance and macroeconomic conditions, but unlike equity funds, the flow–performance relationship is not convex. Then, we find that investor flows can predict fund performance. More importantly, the predictability cannot be explained by return momentum or price pressure but is subsumed by performance persistence. Finally, an examination of idiosyncratic flows reveals little evidence that fund investors use finer-than-public information. This paper was accepted by Lauren Cohen, finance.

Momentum meets value investing in a small European market

In this paper, we investigate two prominent market anomalies documented in the finance literature – the momentum effect and value-growth effect. We conduct an out-of-sample test to the link between these two anomalies recurring to a sample of Portuguese stocks during the period 1988–2015. We find that the momentum of value and growth stocks is significantly different: growth stocks exhibit a much larger momentum than value stocks. A combined value and momentum strategy can generate statistically significant excess annual returns of 10.8%. These findings persist across several holding periods up to a year. Moreover, we show that macroeconomic variables fail to explain value and momentum of individual and combined returns. Collectively, our results contradict market efficiency at the weak form and pose a challenge to existing asset pricing theories.

Momentum, Reversals, and other Puzzles in Fama-MacBeth Cross-Sectional Regressions

The existence of reversals and momentum in equity returns has challenged proponents of efficient markets for over 30 years. Although explanations for momentum profits based on cross-sectional mean return dispersion have been proposed, evidence of time-series autocorrelation from Fama-MacBeth cross-sectional regressions persists without any good risk/return explanation. In this paper I show that common implementations of the Fama-MacBeth procedure will yield upward biased estimates of time-series autocorrelation coefficients. Even in absence of autocorrelation, the bias is strictly positive, leading to apparent momentum when there is, in fact, none. This biased implementation of the Fama-MacBeth procedure has found its way into a great many other studies and may, similarly, lead to apparent effects when there are none. I outline conditions under which this bias occurs and prove the existence of bias under these conditions. I also provide a Monte Carlo simulation showing the magnitude of the bias, I demonstrate the impact of this bias with reference to published results in the literature, and I introduce a new test for misspecification of an asset pricing model. Additionally, I suggest and explore simple fixes for this bias. Some variation of a firm fixed-effects model is appropriate to correct for this bias in applications using the Fama-MacBeth method.

Momentum returns, market states, and market dynamics: Is China different?

Recent studies suggest that momentum returns are conditioned by market states, but we find that China is different. First, we find that momentum returns in China exclusively follow DOWN markets contrary to the U.S. evidence. Second, the absence of momentum returns following UP markets in China cannot be explained by market dynamics, unlike in the U.S. Third, momentum returns in China are higher when the market continues in the same state than when it transitions to the other state as in the U.S. but this is true in China only following DOWN states.

Implications from Biased Probability Judgments for International Disparities in Momentum Returns

ABSTRACTMomentum is a consistent phenomenon in financial data from the majority of markets around the globe. One prominent exception is the Japanese market, where returns from a momentum-investment strategy are nonexistent. The authors investigated international differences in the representativeness heuristic, which is one potential driver of momentum. After observing sequences of a random walk, subjects give probability estimates for the direction of the respective next change. The experiment was conducted in Japan and in Germany. For a subgroup of participants with lower cognitive abilities our results are perfectly in line with international momentum evidence.

Dynamic Momentum and Contrarian Trading

High momentum returns cannot be explained by risk factors, but they are negatively skewed and subject to occasional severe crashes. I explore the timing of momentum crashes and show that momentum strategies tend to crash in 1-3 months after the local stock market plunge. Next, I propose a simple dynamic trading strategy which coincides with the standard momentum strategy in calm times, but switches to the opposite contrarian strategy in one month after a market crash and keeps the contrarian position for three months, after which it reverts back to the momentum position. The dynamic momentum strategy turns all major momentum crashes into gains and yields average return, which is about 1.5 times as high as the standard momentum return. The dynamic momentum returns are positively skewed and not exposed to risk factors, have high Sharpe ratio and alpha, persist in different time periods and geographical markets around the Globe.

Stop losses momentum strategy: From profit maximization to risk control under White’s Bootstrap Reality Check

Abstract This paper proposes a new approach to decision making processes for investors to focus on factor investing and stock selection strategies on the national stock market by capturing the momentum effect (when two portfolios of past relative winners and past losers continue to beat a given benchmark for a certain period of time in the future). Our approach is based on ranking all the combinations of strategy design (5184 strategies) and the disclosure of the momentum effect with two criteria (mean return and risk) controlling for momentum return probability distribution. It is new perspective on the momentum effect permitting its analysis from a comprehensive view taking into account the strategy’s different design elements and observing how the disposition of investor preferences has changed depending on the criterion. We distinguish two criteria: (1) maximizing the mean return of the investment with control t-statistics and the author’s innovation with the Bootstrap p-value, (2) minimizing the risk approximated by the number of drawdowns. This paper conducts the first comprehensive examination of the momentum effect on the Russian stock market.

Another Look at Value and Momentum: Volatility Spillovers

This paper examines volatility interdependencies between value and momentum returns. Using U.S. data over the period 1926-2015, we document persistent periods of low and high volatility spillovers between value and momentum strategies. Moreover, we find that the intensity of the volatility spillovers may change substantially in very short periods of time and that these shifts in spillover intensity can be linked to prominent economic events and financial market turmoil. Our results further demonstrate that value returns increase and momentum returns decrease monotonically with increasing volatility spillovers between the two strategies. Given this linkage between spillover intensity and returns, we propose a simple trading strategy which utilizes a volatility spillover index for allocating funds between value and momentum portfolios. The proposed trading strategy outperforms value and momentum strategies and generates payoffs that are not subject to option-like behavior.

Dynamic Momentum and Contrarian Trading

High momentum returns cannot be explained by risk factors, but they are negatively skewed and subject to occasional severe crashes. I explore the timing of momentum crashes and show that momentum strategies tend to crash in 1-3 months after the local stock market plunge. Next, I propose a simple dynamic trading strategy which coincides with the standard momentum strategy in calm times, but switches to the opposite contrarian strategy after a market crash and keeps the contrarian position for three months, after which it reverts back to the momentum position. The dynamic momentum strategy turns all major momentum crashes into gains and yields an average return, which is about 1.5 times as high as the standard momentum return. The dynamic momentum returns are positively skewed and not exposed to risk factors, have high Sharpe ratio and alpha, persist in different time periods and geographical markets around the globe.