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Momentum strategies exhibit quarterly seasonality, earning significantly higher average strategy returns in the third month of the quarter than the first month. The authors evaluate the magnitude of quarterly seasonality in various momentum strategies to examine the relation between quarterly seasonality and risk-adjusted monthly returns.

The authors construct long-short portfolios for various types of momentum strategies and calculate the average returns of these portfolios in the three months of the quarter. They also calculate the average changes in institutional ownership across the different portfolios.

The authors demonstrate that quarterly seasonality is directly associated with quarterly changes in net purchases by institutional investors. Additionally, they show that near-term price momentum exhibits more seasonality than other momentum strategies, consistent with institutional investor incentives.

Researchers studying momentum should understand that quarterly seasonality increases the standard deviation of monthly returns for different types of momentum strategies.

Individual investors and investment managers should consider whether it is early or late in the calendar quarter when implementing momentum strategies.

Quarterly seasonality explains several seemingly independent findings in the momentum literature. In cases where researchers show one momentum strategy outperforms another on a risk-adjusted basis, the authors find that the superior strategy exhibits less quarterly seasonality. This pattern holds across types of momentum strategies, strategy formation periods and asset classes.

Momentum is an unresolved puzzle for the financial economists. The purpose of this paper is to dissect the sources of momentum profits and investigate the possible role played by the macro-economic variables in explaining them.

The data for 493 companies that form part of Bombay Stock Exchange 500 index in India is used for calculating 6-6 momentum profits. Profits from the strategy are regressed on Capital Asset Pricing Model (CAPM) and Fama-French (FF) model to see whether they can explain these profits. Guided by prior research, three methodologies are used to see the possible role played by macro-economic variables in explaining momentum payoffs.

The empirical results show that momentum profits are persistent in the intermediate horizon. CAPM and FF three-factor model fail to explain these returns. Price momentum seems to be explained in one of the model by lagged macro-economic variables which lend an economic foundation to the Carhart factor. The “Winner minus Loser” factor explains about 37 percent of abnormal returns on the winner portfolio that are missed by the FF model. The unexplained momentum profits seem to be an outcome of investors’ over-reaction to past information. Hence, the sources of price momentum profits seem to be partially behavioral and partially rational.

The failure of risk models in fully explaining the momentum profits may be good news for portfolio managers who are looking out for stock market arbitrage opportunities.

This paper fulfills an identified need to study the sources behind price momentum profits in Indian context.

The purpose of this research is to study the extent to which various price and earnings momentum measures can be used to enhance portfolio performance by better timing entry into value stocks (and isolating those growth stocks that still have some period to run).

The paper uses the traditional methodology of ranking stocks on the basis of certain value and momentum measures (e.g. book‐to‐market, market return over some prior period), forming portfolios based on these rankings which are held for a specific period of time. The portfolios are formed on the basis of a single measure of multiple measures and the returns and associated p‐values are calculated with the objective of determining how these portfolios perform relative to a benchmark portfolio composed of all the companies in the universe. The analysis is conducted on a database consisting of approximately 8,000 companies drawn from 15 European countries over the period from January 1989 to May 2004.

It was found that a number of individual, and combinations of, price and earnings momentum factors are able to enhance value portfolios by identifying stocks that will not perform well in the immediate future. The best measure that was found for timing entry into value and growth stocks is a combination of price momentum and price acceleration where the difference in monthly performance between the “best” and “worst” value (growth) portfolios is 2.6 percent (2.4 percent) for holding periods of 12 months. It was found not only that this momentum measure can be used to enhance value and growth in portfolios consisting of all European stocks but also that it can be successfully deployed in the major individual markets and regions.

Most studies that evaluate the performance of value and growth portfolios do not consider the characteristics of the stocks held in these portfolios. However, it is these characteristics that determine the success of the portfolios formed on the basis of what can only be described as very crude valuation multiples. This paper demonstrates the potential of a closer evaluation of the stocks chosen to be included in a particular portfolio by being able to identify those stocks most likely to perform (and under‐perform). The findings in the paper have obvious implications for the investment processes of investment managers but they also provide useful insights into the efficiency of the European markets and the typical means of price formation within those markets.

This paper applies a volume-price probability wave differential equation to propose a conceptual theory and has innovative behavioral interpretations of intraday dynamic market equilibrium price, in which traders' momentum, reversal and interactive behaviors play roles.

The authors select intraday cumulative trading volume distribution over price as revealed preferences. An equilibrium price is a price at which the corresponding cumulative trading volume achieves the maximum value. Based on the existence of the equilibrium in social finance, the authors propose a testable interacting traders' preference hypothesis without imposing the invariance criterion of rational choices. Interactively coherent preferences signify the choices subject to interactive invariance over price.

The authors find that interactive trading choices generate a constant frequency over price and intraday dynamic market equilibrium in a tug-of-war between momentum and reversal traders. The authors explain the market equilibrium through interactive, momentum and reversal traders. The intelligent interactive trading preferences are coherent and account for local dynamic market equilibrium, holistic dynamic market disequilibrium and the nonlinear and non-monotone V-shaped probability of selling over profit (BH curves).

The authors will understand investors' behaviors and dynamic markets through more empirical execution in the future, suggesting a unified theory available in social finance.

The authors can apply the subjects' intelligent behaviors to artificial intelligence (AI), deep learning and financial technology.

Understanding the behavior of interacting individuals or units will help social risk management beyond the frontiers of the financial market, such as governance in an organization, social violence in a country and COVID-19 pandemics worldwide.

It uncovers subjects' intelligent interactively trading behaviors.

What explains patterns in stock prices is an important question. One such pattern, price momentum, is a well-known capital markets anomaly where recent stock price performance appears to continue into the future. This momentum is frequently thought to reflect delayed reaction by investors to unspecified information (i.e. underreaction). This study aims to provide a useful insight regarding momentum: potential mispricing related to accounting fundamentals appears to conceal longer-term reversals in price momentum. Controlling for these fundamentals reveals that price momentum reverses, indicating that investor overreaction is a potentially important source of stock price momentum. The evidence presented in this study emphasizes the importance of decoupling momentum and accounting fundamentals to achieve a more complete understanding of what explains stock price momentum.

This study explores this question by examining the longer-term performance of momentum stocks in the US market after decoupling it from performance related to accounting fundamentals using returns to fundamentals-based factors as controls in time series regressions.

This study finds evidence of clear reversals in the remaining price momentum. These reversals provide a new insight into the momentum effect because they imply that the component of price momentum not traceable to accounting fundamentals reflects investor overreaction rather than underreaction.

The findings indicate that the underlying nature of the information driving price movements is important to achieving a complete understanding of what explains price momentum. To the best of the author’s knowledge, no other study has examined the behavior of stock price momentum while controlling for accounting fundamentals.

The purpose of this paper is to assess trading strategies adopted by each large trader group and examine their effects on the volatility in the interest rate futures markets.

The Grinblatt et al.'s (1995) measure of momentum strategy is used to estimate the degree momentum and contrarian strategies. Then, regression analysis is used to determine the effects of trading strategies on volatility.

Up until 2005, the trades by non-clearing member firms in the futures market were separated from institutional traders providing us the opportunity to study trading strategies adopted by large distinct trading groups and its effects on volatility in the futures markets. It is found that individual traders use momentum strategy, whereas market makers and institutional traders use contrarian strategy. Momentum strategy adopted by individual traders increases volatility whereas contrarian strategy dampens volatility. Moreover, it is found that institutional traders engage more actively in contrarian trading when individual traders cause excessive volatility. The two distinct trading groups were separately tracked prior to 2005 giving us a unique window to determine the effect of the traders that conduct momentum trading as opposed to the ones that are contrarian traders. After the reclassification, the institutional trading group exhibited weaker contrarian strategy which can be attributed to the inclusion of non-clearing firm traders.

This study documents the first empirical evidence that shows off-exchange futures trader group is not composed of only pure noise makers, but there are short-term forecasters in its group. The authors also show a unique finding that noises caused by off-exchange group is from momentum strategy that they use, whereas contrarian strategy is used by institutional trader lower volatility.

We extend empirical evidence on the profitability of momentum trading to the realm of plain-equity ETFs.

We employ several ranking measures used in prior research, and for each we apply a traditional ranking based on total return, and a variation based only on the capital gain/loss portion of return.

While we find that past momentum is not a strong predictor of future performance in our overall sample period, 2007 to June 2018, we find that the percent off 52-week high price results in positive performance in the recovery years following the financial crisis of 2008–2009.

Our study is limited by the availability of ETF experience and data, and our test period covers just 2007 through June 2018. This period includes the financial crisis of 2008–2009, which previous research finding is associated with the momentum strategy's loss of profitability. When we exclude that period, we find evidence of a profitable momentum strategy based on the measure of percent off 52-week high price, enabling us to reject the null hypothesis that the momentum trading strategy is no longer profitable.

It is profitable based on both return measures used in the rankings. Our finding of a profitable momentum trading strategy suggests that the null hypothesis that the momentum strategy is no longer profitable can be rejected.

While perhaps not so strong as to reject the efficient markets hypothesis fully, our empirical findings are more consistent with a behavioral explanation and a market inefficiency. In view of the relative ease and low transactional costs of trading in ETFs, the markets have yet another opportunity to recognize an apparent mispricing and employ arbitrage based on it. To the extent that the relative ease of trading in ETFs makes momentum strategies easier to employ, the momentum anomaly might still be expected to disappear in an efficient market.

The purpose of this paper is to evaluate the profitability of investment strategies based on past price changes and trading volumes.

Data are employed from January 1998 to December 2011 for select emerging markets. Portfolios are formed on the basis of past information on prices and/or volumes. Unrestricted and risk adjusted returns for sample portfolios are analyzed. The risk models employed in study are Capital Asset Pricing Model (CAPM), Fama-French (F-F) Model and Fama-French augmented models.

Price momentum patterns are observed for Brazil, India, South Africa and South Korea, while there are reversals in Indonesia and China. Low-volume stocks outperform high-volume stocks for all sample countries except China. Further, volume and price based bivariate strategies do a better job than univariate strategies in case of India, South Africa and South Korea. The past price and volume patterns in stock returns are not fully explained by CAPM as well as the F-F Model. Price and volume momentum factors do play a role in explaining some of these return patterns. Finally, the unexplained returns seem to be an outcome of investor under or overreaction to past information. The sources of price and volume momentum seem to be partly risk based and partly behavioral.

The study analyzes combined role of price and volume in portfolio formation with post holding analysis. The work is useful for global portfolio managers, policy makers, market regulators and the academic community. The study contributes to asset pricing and behavioral finance literature for emerging markets.

The purpose of this paper is to analyze long-term prior return patterns in stock returns for India.

The methodology involves portfolio generation based on company characteristics and long-term prior return (24-60 months). The characteristic sorted portfolios are then regressed on risk factors using one factor (capital asset pricing model (CAPM)) and multi-factor model (Fama-French (FF) model and four factor model involving three FF factors and an additional sectoral momentum factor).

After controlling for short-term momentum (up to 12 months) as documented by Sehgal and Jain (2011), the authors observe that weak reversals emerge for the sample stocks. The risk model CAPM fails to account for these long-run prior return patterns. FF three-factor model is able to explain long-term prior return patterns in stock returns with the exception of 36-12-12 strategy. The value factor plays an important role while the size factor does not explain cross-section of average returns. Momentum patterns exist in long-term sector returns, which are stronger for long-term portfolio formation periods. Further, the authors construct sector factor and observe that prior returns patterns in stock returns are partially absorbed by this factor.

The findings are relevant for investment analysts and portfolio managers who are continuously tracking global markets, including India, in pursuit of extra normal returns.

The study contributes to the asset pricing and behavioral literature from emerging markets.

This paper aims to examine the impact of the dividend payout ratio on future stock returns and momentum strategies.

The author uses the portfolio sorting approach used in the momentum literature to examine this impact.

First, the author shows that the returns for the winner stocks tend to be the largest if no dividends are paid and then decrease with the dividend payout ratio; the returns for the loser stocks tend to have an inverted U-shaped relationship with the dividend payout ratio, but the zero-dividend loser stocks have the smallest return; and the returns for the stocks between the winners and the losers tend to remain similar, regardless of the dividend payout ratio. Second, the author shows that momentum profit is the largest for the stocks that do not make dividend payment but appear similar for the stocks that pay dividends. The author's empirical findings imply that stock price momentum is a function of the dividend payout ratio, growth stock momentum tends to be much stronger than value stock momentum and no-dividend stock momentum beats dividend stock momentum. In fact, when the dividend payout ratio is considered, momentum profit can be improved by up to 63 per cent.

This paper is the first one to examine the impact of dividend payout ratios on future stock returns and momentum profit, and it obtained many interesting empirical results. In addition, unlike most studies in the momentum literature that use behavioral theory to explain empirical findings, this paper uses the growth option idea to present a rational explanation for the empirical results in this paper.