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The purpose of this paper is to study merger momentum and its driving factors in China by sampling 376 listed bidders from 2008 to 2013.

The empirical model captures the dependency of market reaction on recent merger and stock market states. The independent variables are designed from two dimensions, i.e. at the level of market-wide as an integral and bidder-specific as individuals. Furthermore, both the market and bidding firms contain merger momentum and market momentum, respectively.

The empirical results show that there is merger momentum in the market. Particularly, merger momentum is significant both in short run and long run for the mergers with cash payment, which supports the synergy effect. It also implicates the mergers with stock driven by investor sentiment. Besides, investors’ over-optimism is significant in the bull markets while managerial hubris is found in the bear markets.

The driving factors for merger momentum in China are complex. Three impacts with different effects interact with one another. They are investor sentiment and managerial hubris with negative effects resulting in reversal abnormal return in the long run, and synergies with positive shocks resulting in no reverse at all. The limitation of the paper is insufficient analysis of the mergers financed by stocks, which will be the focus for future study.

The conclusions of the study help to intensify the understanding of the immature and unnormalized capital market in China. The empirical analyses give some inspiration and suggestions to three parties in the market, i.e. investors, bidding firms and regulators, respectively.

There are three contributions. The first one is to provide a novel model to identify how these different effects work on the merger momentum. The second one is the measurement of investor sentiment from different perspectives. The last but most important one is the new findings with novel explanations, which proves that the impacts on merger momentum are complex.

The purpose of this paper is to examine positive‐feedback (PF) behavior and its relationship to momentum profitability and information uncertainty.

Using 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.

This 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.

This 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.

This paper examines the impact of macroeconomic and risk factors on the profitability and volatility of professional momentum portfolios for the US, the UK, Japan and Germany, for the period 1998–2018. Many of the factors employed, such as energy price changes and economic policy uncertainty, have been largely neglected in the relevant literature.

Regression analysis, VECTOR AUTOREGRESSION (VAR), Panel-VAR, Variance Decomposition Analysis

The results indicate that, since the financial crises in the US and the EU, energy prices and economic-policy uncertainty have become important return determinants, along with market-related uncertainty that seems to have a stable impact over time, especially for the U.S. and U.K. portfolios.

Economic policy uncertainty significantly affects contemporaneous momentum returns in the US, UK and Japan, mainly between 2007 and 2018, while market-related uncertainty affects all markets during all subperiods. In addition, the variance of market-related uncertainty (VIX) explains a large percentage of the variance in the momentum returns for the US, UK and Germany.

The main implication of the findings for portfolio managers is that a manager may increase (decrease) exposure to the momentum factor during optimistic (pessimistic) periods and during periods of rising energy prices (high economic policy and market-related uncertainty).

The paper examines the impact of factors, such as energy prices and economic policy uncertainty, which have been largely neglected in the relevant literature on the possible drivers of the momentum strategies. It employs professional portfolios that are often used in practice as benchmark indexes.

The purpose of this paper is to examine the relationship between a stock market's index returns and its subsequent firm‐level momentum profits. This relationship is analysed for each of ten individual European stock markets between 1973 and 2010.

Using firm‐level data, intra‐market momentum returns are analysed, using various ranking and holding period combinations. Standard t‐tests as well as pooled and country‐specific regressions are employed to determine the significance of the non‐linear relationship between one‐, two‐ and three‐year index returns and subsequent momentum returns.

Momentum returns following a bull market are positive for all ten stock markets; statistical significance is reached by nine of those ten. Per contrast, momentum returns following a bear market are insignificant for all ten stocks markets, and the average return is negative. Further, in all ten stock markets the momentum profits are lowest following the greatest drops in the index; this effect is significant in eight countries. These results are consistent with the behavioural theories on investors' overconfidence and undue self‐attribution.

The paper's findings suggest that investors should refrain from pursuing a momentum strategy in European stock markets shortly after a severe bear market.

This is the first study to investigate the temporal dependence of firm‐level momentum returns on preceding index movements in European stock markets.

Previous literature in the Korean stock market has shown that the momentum effect is not observed during pre-2000 period while it is observed during post-2000 period. Given that market illiquidity has substantially decreased during post-2000 period, we examine whether the level of market illiquidity affect the momentum profits. The central findings are summarized as follows. First, our full-sample analysis shows that market liquidity is positively associated with momentum profits, meaning that the observed momentum effect during post-2000 period is related to the decrease in market illiquidity. Second, during pre-2000 period, when the market illiquidity is very high, the illiquidity of past losers is extremely high compared to that of past winners. However, there is no significant difference in illiquidity between winners and losers during post-2000 period. Third, based on this result, we conjecture that the momentum effect is related to the different compensation for liquidity risk between past losers and winners, and test whether this is indeed the case. We find significant momentum profits over the whole period when we consider the compensation for the liquidity risk of past losers and winners. In addition, during pre-2000 period, the return on momentum strategy that controls the liquidity risk is substantially higher than the actually observed momentum profits. In sum, our study suggests that the difference in compensation for liquidity risk between past losers and winners is very important in understanding the momentum effect in the Korean stock market.

This paper aims to extend an earlier analysis of the profitability of an individual firm operating in the professional services industry from the perspective of the triple‐entry framework of the momentum accounting theory of Yuji Ijiri.

The paper presents a “common‐size‐format” model of balance‐sheet momentum, an approach typical of financial statements' mathematical analysis.

Common‐size‐format momentum ratios offer an alternative measurement of (the change of) business performance. They model stabilizing phenomena that might develop very differently from ratios like return on total assets or return on equity and thus provide important informational signals to the analyst of financial statements. The common‐size‐format ratio of net wealth momentum herein discussed is proposed as a supplemental measurement for business performance analysis.

The paper discusses a new method for performance measurement and risk analysis.

The purpose of this paper is to examine the added value of combining a momentum indicator with a value indicator in varying stock market conditions.

A comprehensive sample of Finnish non‐financial stocks is first divided into three‐quantile portfolios based on valuation multiples and composite value measures. The value and glamour portfolios are divided further into two‐sextile portfolios based on the price momentum indicator. The performance of portfolios is evaluated on the basis of their raw and risk‐adjusted returns. Moreover, the impact of the stock market cycle on relative performance of quantile portfolios is examined.

Taking account of price momentum beside relative valuation criteria enhances the performance of most of the value‐only portfolios during the full sample period (1993‐2009). During bullish conditions, the inclusion of a momentum criterion somewhat adds value to an investor, but during bearish conditions this added value is negative.

The sample of stocks is not large in spite of its comprehensiveness from the local stock market aspect. Future studies can apply the approach to other stock markets.

The paper provides useful implications in portfolio management. The combination of the value and momentum criteria has paid off to the investor, despite the fact that its added value during bearish periods is negative, on an average.

This is the first time that the impact of the stock market cycle on the added value of combining price momentum with composite value measures as a portfolio‐formation criterion is examined.

This paper aims to evaluate the influence of economic policy uncertainty (EPU) on the momentum effect, analysing its influence depending on the economic cycle and in different quantiles.

To determine the influence of EPU in the momentum effect taking into account the economic cycle and the level of the quantile, linear regression and quantile regression have been applied for the period from 2 January 1985 to 30 April 2019 for the US stock market.

It is shown that an increased feeling of insecurity associated with EPU reduces the momentum effect, especially in times of recession. Distinguishing by quantiles, an asymmetry in the impact of EPU in the momentum effect is discovered, finding that EPU reduces (increases) the profits of momentum strategies in the lowest (highest) quantiles. In the highest quantiles, an investor can obtain higher extraordinary returns with this strategy. For example, in the highest quantile, a one-point increase in the EPU levels would have increased the daily profitability by 12.7 basis points. These findings have important implications for investors and policymakers.

To the best of the authors’ knowledge, this is the first paper that evaluates the influence of EPU on the momentum effect by conducting an analysis based on the economic cycle and different quantiles, demonstrating how these factors are relevant in the influence of this uncertainty in the momentum anomaly.

The purpose of this paper is to critically review the literature on contrarian and momentum trading strategies and identify areas for future research.

Critical review and discussion of the literature.

The extant literature is dynamic and is typified by a number of open questions.

The open questions in the literature relate mainly to the driving forces of investment performance, and the role of risk and asset pricing as well as behavioral human traits. The literature is vast and therefore difficult to classify, cover and discuss.

The paper indicates the possible need for: the development of different asset pricing models and propositions that can have practical implications at a more international context.

The paper provides a critical review of the literature and identifies open issues for future research.

The analysis aims to explore how momentum return changes with alternative computational methods and the extent to which the portfolio structure is important in the momentum context.

The focus reflected in the prior research emphasises the method used by Jegadeesh and Titman and various extensions to test whether momentum returns exist. This study uses alternative methods of buying previous Winners and short‐selling previous Losers to determine if this significantly changes the returns.

The current study clarifies the impact of several contributory factors that impact upon estimated momentum returns. The large sample of cleaned data upon which this study is based provides a higher degree of confidence that the findings are sound and not just a statistical anomaly.

The research is important from a practitioner perspective as details of momentum return are presented for each country using different methods, providing information regarding the most profitable country in which to invest and whether the momentum return is sustainable under different formative approaches.

One of the important contributions of this study is a detailed empirical analysis, presenting results in a global context rather than on a single country basis.