Momentum Profits Research Articles

Momentum profits and idiosyncratic volatility: the Korean evidence

PurposeThis study aims to focus on the profitability of momentum trading in the Korean stock market. More specifically, it aims to conduct an examination of the relationship between momentum returns and idiosyncratic volatility (IVol) to determine whether momentum profits can be explained by IVol.Design/methodology/approachPortfolios are formed based on their past performance and examine the momentum, or contrarian returns, as the difference between winning and losing portfolios. To confirm that the momentum strategy provides excess returns, the relationship between momentum returns and IVol is studied. The Fama and French three‐factor model is also examined to see whether systematic risk affects momentum profits. Firm size, stock price, and turnover are controlled to determine robustness. Finally, a time‐series relationship between aggregate IVol and momentum profits is investigated.FindingsThe paper illustrates that excess returns are obtained from a momentum strategy, not a contrarian strategy, in the Korean stock market. Momentum returns are higher among high IVol stocks, especially high IVol winners. Examining the Fama and French three‐factor model, it is found that momentum returns cannot be explained by systematic risk. The findings are robust after controlling for factors such as firm size, book‐to‐market ratio, and turnover. The paper confirms the effect of IVol on momentum returns by illustrating that a time‐series relationship between momentum returns and aggregate IVol is positive.Originality/valueThis paper is among the first, to the authors' knowledge, to examine the relationship between momentum profits and IVol in the Korean stock market, one of the mature financial markets. The findings in this study can be applied to better understand the sources of gains from the momentum strategy in international stock markets.

Sources of momentum profits: bootstrap methods

PurposeThe purpose of this paper is to test the performance of momentum strategies and identify the sources of their profits.Design/methodology/approachTo identify the main source of momentum profits, first, the bootstrap method with replacement was used. Then, to eliminate the existence of the small sample bias, the bootstrap method without replacement and the block bootstrap method were employed. In this case, when the authors draw the observations without replacement the random effect is reduced, whereas the resampling procedure is based on the random draw.FindingsThe empirical results show the existence of a small sample bias in the bootstrap method with replacement, and that the time‐series relations of stock returns are the main source of momentum profits.Originality/valueTo ensure the random effect of the draws, the authors develop a new resampling procedure called the mixed bootstrap method.

International Real Estate Review

We find that the 3-day window around funds from operations (FFO) announcements drives the momentum profits found in the literature, which deliver an average excess monthly return of 1.22% over the period of 1990-2008 and 1.59% during the post-2000 period. Excluding this announcement window, a momentum strategy does not generate any significant returns. The FFO-surprised-based portfolio formation method produces higher momentum profits than the return-based formation method. There is a significant positive serial correlation between the unexpected FFO for the next two quarters. We contribute to the current literature by documenting that the persistence of momentum profits is due to the underreaction by analysts on public information, the FFO announcement.

Time-Varying Expected Momentum Profits

Time-Varying Expected Momentum Profits

Sources of momentum profits in international stock markets

AbstractThis paper examines the sources of momentum profits of countries exhibiting and not exhibiting momentum and compares the differences in the underlying factors determining momentum profits between these two groups of countries. We find remarkable differences in the decomposed components between these two groups of countries. Countries exhibiting momentum show that the cross‐sectional dispersion in unconditional mean returns dominates the negative contribution from the component reflecting the intertemporal behaviour of asset returns. However, this is not the case in countries exhibiting no momentum. Furthermore, countries with greater relative contribution from the cross‐sectional variance in unconditional mean returns tend to have greater momentum profits. Our results may support risk‐based explanations for the momentum phenomenon rather than behavioural finance‐based explanations.

The role of shorting, firm size, and time on market anomalies

We examine the role of shorting, firm size, and time on the profitability of size, value, and momentum strategies. We find that long positions make up almost all of size, 60% of value, and half of momentum profits. Shorting becomes less important for momentum and more important for value as firm size decreases. The value premium decreases with firm size and is weak among the largest stocks. Momentum profits, however, exhibit no reliable relation with size. These effects are robust over 86 years of US equity data and almost 40 years of data across four international equity markets and five asset classes. Variation over time and across markets of these effects is consistent with random chance. We find little evidence that size, value, and momentum returns are significantly affected by changes in trading costs or institutional and hedge fund ownership over time.

Firm ratings, momentum strategies, and crises: evidence from the US and Taiwanese stock markets

This paper investigates whether there is a link between momentum profitability and firm ratings. We follow traditional and practical (non-) investment-grade classifications to divide into three rating groups, high, median, and non investment-grade group (HIG, MIG, and NIG) since firm ratings express risk in relative rank order to contain valuable information. This study considers the US and Taiwanese stock markets. We find that firm ratings momentum strategies can even earn positive profits, larger than naive momentum, supporting that firm ratings can be used to strengthen naive momentum effects. By comparisons, the US firm ratings momentum with NIG produces larger profits than HIG but opposite in direction and V-shaped pattern in Taiwan. With an examination of crises on firm ratings momentum, we find that firm ratings momentum indeed helps increase the payoff during (non-)crises although firm ratings momentum profits should be strong following non-crises states and weak following crises states. However, firm ratings momentum profits partially result from the predictability of business cycle, calendar months, and information asymmetries. Our results highlight the critical importance of using firm ratings screens in empirical momentum studies.

MOMENTUM AND CONTRARIAN STRATEGIES EVIDENCE IN VIETNAM STOCK MARKET

This study mainly investigates the investment performance of momentum strategy and contrarian strategy in Vietnam stock market from January 2007 to March 2011 by using the empirical methodology in Jegadeesh and Titman (1993). The empirical results show that during the period January, 2007 to March, 2011 momentum strategy works effectively over the horizon of 1, 5, 10, 20, 60 and 90 days,meanwhile, no contrarian strategy can make significant profit during the same horizon, which is quite different from other developed stock markets. Moreover, the results suggest that in Vietnam stock market it is better to limit the holding period in short term because momentum profit will decrease rapidly when holding period is longer and the best choice is limiting the trading and holding period to 5 days. Additionally, I find that buying high-volume winners and selling high-volume losers is more profitable than buying low-volume winners and selling low-volume losers

Cognitive Dissonance, Sentiment, and Momentum

AbstractWe consider whether sentiment affects the profitability of momentum strategies. We hypothesize that news that contradicts investors’ sentiment causes cognitive dissonance, slowing the diffusion of such news. Thus, losers (winners) become underpriced under optimism (pessimism). Short-selling constraints may impede arbitraging of losers and thus strengthen momentum during optimistic periods. Supporting this notion, we empirically show that momentum profits arise only under optimism. An analysis of net order flows from small and large trades indicates that small investors are slow to sell losers during optimistic periods. Momentum-based hedge portfolios formed during optimistic periods experience long-run reversals.

Explaining Momentum and Value Simultaneously

This paper proposes a unified risk-based explanation for momentum profits and the value premium in a neoclassical investment-based model. Winner firms have higher short-term profitability and investment commitment, and hence more negative exposure to the price of investment goods than loser firms. Value firms have lower long-term profitability and higher operating leverage, and hence higher sensitivity to neutral productivity shocks than growth firms. The model reproduces the coexistence of momentum profits and the value premium, the failure of the unconditional CAPM, the predictability of momentum profits by market states, and the long-term reversal of momentum profits.

Cross-asset Style Momentum

Previous studies have demonstrated style momentum within equity markets. This paper reports significant momentum profits among style portfolios of multiple asset classes, showing that style momentum is not merely an equity market phenomenon, but a cross-asset phenomenon. A decomposition of profits reveals that profits are mostly attributable to positive autocorrelations of style returns. We interpret this result as being more consistent with underreaction models than with excess comovement and performance chasing models.

Does Sentiment Risk Persist as Priced Risk Factor? A Multifactor Approach for Stock Return

Much of the academic debate has gone in to exploring the better asset pricing model that can explain the quantification of the trade-off between risk and expected return for the cross section of stock return. Nevertheless this intimidating task becomes more pragmatic given the market structure of emerging markets, liquidity effects, market inefficiency, and more significantly the presence of inherent imperfect rationality or sentiment. The basic objective of this paper is to evaluate the pricing implication of unconditional five factor model to explain the cross sectional stock return behaviour in the context of Indian stock market. Our analysis also aims to examine the pricing nature of aggregate market wide sentiment risk in the presence of other risk factors. We employ Fama and French time series regression approach to examine the impact of market risk premium, size, book-to-market equity, momentum and liquidity as risk factors on stock return. Our empirical results show that given the multidimensional nature of risk the choice of a five factor model is apparently persuasive for consideration in investment decisions. However, inconsistent with prior literature book-to-market equity fails to explain the average return in case of large stocks, and pricing evidence of momentum profits fades in case of winner stocks and momentum strategy retains its value only for the sell side transactions i.e., loser portfolios. With the presence of liquidity factor in the five factor model specification, the results suggest that liquidity is priced and explains a cross sectional variation in stock returns. Our results also suggest that it is naive to argue for the universal pricing implication of sentiment risk in a multifactor model framework, and market wide risk factors resume their importance as rational source of priced risk.

Momentum profitability: the pre-CRSP evidence

There is tremendous interest and research on the existence and sources of momentum profitability. This article is the first to examine momentum strategy in the pre-Center for Research in Security Prices (CRSP) era. The results show that momentum is profitable during the period of 1815 to 1925. Moreover, the profits are negative in January and positive in non-January months.

The Role of Shorting, Firm Size, and Time on Market Anomalies

We examine the role of shorting, firm size, and time on the profitability of size, value, and momentum strategies. We find that long positions comprise almost all of size, 60% of value, and half of momentum profits. Shorting becomes less important for momentum and more important for value as firm size decreases. The value premium decreases with firm size and is weak among the largest stocks. Momentum profits, however, exhibit no reliable relation with size. These effects are robust over 86 years of U.S. equity data and almost 40 years of data across four international equity markets and five asset classes. Variation over time and across markets of these effects is consistent with random chance. We find little evidence that size, value, and momentum returns are significantly affected by changes in trading costs or institutional and hedge fund ownership over time.

Momentum, Risk, and Underreaction

Momentum profits can be explained by exposure to risks omitted from common factor models (distress risk, idiosyncratic risk, and covariance with corporate bonds) and underreaction to innovations in these risks. Momentum strategies tend to go long risky stocks with high expected returns. Consistent with risk as a partial explanation of momentum profits, long formation period momentum strategies earn higher returns and are more highly correlated with risk factors than short formation period momentum strategies. Momentum strategies also tend to go short stocks with recent increases in risk; these stocks have low expected returns because investors underreact to risk innovations.

Weekly momentum by return interval ranking

Existing research does not find significant momentum profits in many emerging markets including China. We propose an alternative momentum strategy which groups stocks into return intervals rather than percentiles. We apply the method to the China A-share market and find economically significant momentum profits in weekly returns, but not in monthly returns. The weekly momentum lasts for about 1year. More than half of the profit is realized in the first 3weeks. We apply the method to other Asian equity markets and find significant weekly momentum in Hong Kong, Taiwan, Korea, Thailand, and Indonesia. These findings suggest that momentum may exist in different formats in different markets. Existence of momentum in a closed equity market like China supports momentum is pervasive in short-term stock returns.

Aggregate Volatility Risk and Momentum Returns

Momentum profits are generated by winners' exposure to aggregate volatility risk. A proxy for aggregate volatility shock (AVS) which comes from an EGARCH (1,1) model of monthly market excess returns is a priced risk factor in cross-sectional regressions and commands a negative risk premium. Winners have negative AVS loadings thereby earning higher average returns than do losers. Event time analyses reveal important insights about the temporary nature of momentum profits. For example, I find that winners have lower AVS loadings than do losers over the first 6 months of the holding period and that the difference in loadings becomes mostly insignicant thereafter. Another event-time study shows that the profitability of momentum strategies after up-market states can also be attributed to the difference in aggregate volatility risk. I explain the negative AVS loadings of winners with a real option argument. Over the evaluation period winner firms develop growth options and their market values become sensitive to aggregate demand conditions. AVS is a negative demand shock that causes investment cuts and downward revisions in future earnings. The decline in investment growth and thereby the loss in market value is more pronounced for winners. Moreover, the reversal of momentum returns one year after portfolio formation is partly explained by the negative cross-sectional relation between real investment and average returns. Additional robustness checks and comparison with conditional CAPM suggest that the ICAPM with aggregate volatility risk is an important multifactor model that accounts for the cross-sectional return variation of momentum stocks.

Momentum and Aggregate Default Risk

In this paper, we explain momentum profits using innovations in aggregate economy-wide default risk. First, we show that momentum returns are positive only during high default shocks and nonexistent otherwise. Second, we present evidence suggesting that a conditional default shock factor is priced in the cross-section and can explain a large portion of the total momentum returns. According to our results, winners have potentially higher risk than losers during periods of high default shocks. We confirm this finding in alternate sub-periods where momentum is generally not observed and as well as in international data. We also provide an explanation for this finding by linking momentum profits to potential shareholder recovery during financial distress. We find that winners tend to have relatively higher risk in worsening aggregate default conditions due to lower shareholder bargaining power. These results indicate that momentum profits contain a systematic component related to aggregate default and can be explained in a rational framework.

Sources of Momentum in Bonds

This paper documents that momentum profits in corporate bonds prevail during weakening aggregate credit conditions, and are driven by losers. Consistent with this, we find that a conditional default factor explains the cross-section returns of corporate bond portfolios sorted by past performance. Based on the evidence, we develop a model connecting bond momentum returns to the ability of bondholders to recover value when firms default. Specifically, we propose that firms with more (less) intangible capital and growth options are more (less) costly to liquidate and, therefore, they have lower (higher) recovery value. In this case, the bond momentum can exist, because the “recovery premium” becomes more important when firm default becomes highly probable. We provide strong empirical support to these predictions. Related, the U.S. government bonds display no momentum, yet it emerges in sovereign bond returns. Time-varying aggregate default shocks and firm characteristics determining the growth and liquidation of issuers are the main sources of momentum in bonds.

Positive‐feedback trading activity and momentum profits

PurposeThe purpose of this paper is to examine positive‐feedback (PF) behavior and its relationship to momentum profitability and information uncertainty.Design/methodology/approachUsing the behavioral function of rational traders and feedback traders, the authors jointly estimate the mean and conditional variance equations of the GARCH model to derive the positive‐ and non‐positive‐feedback coefficients, respectively. In each six‐month period, the number of PF stocks were then calculated as a fraction of the total number of stocks in that period. The authors then investigate whether day‐to‐day PF trading activities vary across different momentum portfolios by calculating the percentage of PF stocks in each decile portfolio.FindingsThis study finds that about 9.4 per cent of stocks exhibit PF trading activities and that these activities have a more profound effect on stocks with a higher level of information uncertainty. The finding shows that the percentage of stocks with PF trading is higher in the portfolios of extreme losers than in the portfolios of extreme winners. The evidence suggests that stocks exhibiting PF trading activities subsequently experience significantly higher momentum returns.Originality/valueThis paper presents evidence to test whether a relationship exists between short‐term PF trading and future momentum profitability. Since PF traders tend to chase price movements, PF trading is more likely to cause stock prices to further diverge from the firm's fundamentals and, therefore, give rise to stock return momentum. This phenomenon appears to be more profound in this study when there is a higher level of information uncertainty.