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The purpose of this paper is to investigate the profitability of momentum investment strategy and the predictive power of trading volume for equities listed in the Australian Stock Exchange.

Following the Lee and Swaminathan's approach, portfolios on past returns and past trading volume is constructed. In this approach, all stocks are ranked independently on the basis of past returns and past trading volume. The stocks are then assigned to one of five portfolios based on past returns and one of three portfolios based on trading volume over the same period.

A strong momentum effect for the Australian market during the period 1988 through 2002 is observed. Further, momentum plays an important role in providing information about stocks. Past trading volume appears to predict both the magnitude and persistence of price momentum.

Substantial momentum observed in monthly stock returns has investment implications. Abnormal returns vary from 0.3 to 7 per cent per month in the intermediate horizon.

This study provides an out of sample evidence by examining the relationship between “trading volume” (measured by the turnover ratio) and “momentum” strategies in an Australian setting.

As the world's largest emerging market, the evidence of momentum effect in China is also mixed. Meanwhile, prior studies mainly examined individual stock momentum in China, with little concern for industry momentum and its relationship with trading volume. The motivation of this study is to investigate industry momentum in China and examine whether trading volume can enhance its profitability.

Firstly, the authors test the existence of industry momentum in China; secondly, the authors test the correlation between trading volume and momentum returns using the double ranking method; finally, the authors test whether trading volume enhances the momentum returns using Fama–French five-factor model.

The authors find that there is a significant industry momentum effect in China, and the momentum returns jointly come from winner and loser portfolios. The intervals between the formation and holding periods have an impact on the performance of momentum portfolios. In terms of trading volume, the authors find that high-volume industries have industry momentum effects while low-volume industries do not. The industry momentum strategies achieve higher excess returns in high-volume industries.

Prior literature found higher momentum returns in low-volume stocks in China, but the research in this study suggests that implementing an industry momentum strategy in low-volume industries will miss out on higher returns or even bring losses, and instead the investors should invest in high-volume industries to get the best performance.

This study extends existing research by focusing on industry momentum and its relationship with trading volume in the Chinese stock market and finds an interesting relationship between industry momentum returns and trading volume, which is different from related studies.

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.

To improve flow solutions on meshes with cells/elements which are distorted/ non‐orthogonal.

The cell‐centred finite volume (FV) discretisation method is well established in computational fluid dynamics analysis for modelling physical processes and is typically employed in most commercial tools. This method is computationally efficient, but its accuracy and convergence behaviour may be compromised on meshes which feature cells with non‐orthogonal shapes, as can occur when modelling very complex geometries. A co‐located vertex‐based (VB) discretisation and partially staggered, VB/cell‐centred (CC), discretisation of the hydrodynamic variables are investigated and compared with purely CC solutions on a number of increasingly distorted meshes.

The co‐located CC method fails to produce solutions on all the distorted meshes investigated. Although more expensive computationally, the co‐located VB simulation results always converge whilst its accuracy appears to grace‐fully degrade on all meshes, no matter how extreme the element distortion. Although the hybrid, partially staggered, formulations also allow solutions on all the meshes, the results have larger errors than the co‐located vertex based method and are as expensive computationally; thus, offering no obvious advantage.

Employing the ability of the VB technique to resolve the flow field on a distorted mesh may well enable solutions to be obtained on complex meshes where established CC approaches fail

This paper investigates a range of cell centred, vertex based and hybrid approaches to FV discretisation of the NS hydrodynamic variables, in an effort characterize their capability at generating solutions on meshes with distorted or non‐orthogonal cells/elements.

The purpose of this paper is to examine the short horizon stock behavior following large price shocks in the Indian stock market.

The author followed the methodology developed by Pritamani and Singhal (2001) to the short horizon stock behavior following large price shocks. Multivariate regression has also been used to test the robustness of the evidenced results.

The abnormal return following large one-day price changes were not found to be important. However, large price one-day changes, conditioned with volume, evidenced significant reversals and momentum over the following 20-day period. Large price changes accompanied by low volume exhibited significant reversals and suggests significant economic profits. The large price changes accompanied by high volume exhibited continuations.

Large price changes accompanied by low volume exhibited significant reversals and suggested significant economic profits. The large price changes with high volume exhibited continuations. The contrarian strategy of buying low-volume one-day losers and selling one-day winners produced significant short horizon economic profits in the Indian stock market directly contradicting the efficient market hypothesis and has behavioral implications.

In this paper, the author has unearthed significant simple profitable trading strategies based on reversals and continuation following large one-day price changes with potential for significant economic profits.

This paper provides a practical framework for profitable trading strategies based on reversals and continuation following large one-day price changes with a potential for significant economic profits. The analysis of short horizon stock behavior following large price shocks conditional on volume based on the chosen methodology has not been attempted so far in the Indian stock market.

We form portfolios based on return and liquidity and examine the effects of liquidity and other risk factors on asset pricing in the Chinese stock market. Our results show that the past loser-and-illiquid stock portfolios tend to outperform the past winner-and-liquid stock portfolios in the 1–12 months holding period. The excess return is significantly associated with the market-wide liquidity factor even when we control the three Fama-French and momentum factors. Cross-sectionally, the liquidity beta significantly affects the excess return even with control of other risk betas and other traditional liquidity proxies.

Momentum returns are considered an anomaly in the finance literature as their existence cannot be fully explained under the asset pricing paradigm. This study attempts to shed more light on this anomaly by investigating the determinants of momentum returns.

The panel data technique is applied to the sample of 40 countries worldwide from 1996 to 2018. The authors use the panel-corrected standard error (PCSE) model to estimate the coefficient of World Governance Indicators (WGI), whereas the fixed effect model is used to determine the coefficient for corporate governance indicators (CGIs). The choice of PCSE estimation methods is guided by the fact that WGI variables are subjected to serial correlation, heteroskedasticity and cross-sectional dependence problems while CGI variables are not. Furthermore, a composite WGI index is constructed using principal component analysis (PCA).

Regression analysis shows a negative and significant relationship between WGI index and momentum returns. The negative coefficient value of WGI supports the prediction of the overreaction hypothesis, which postulates a lower behavioral bias in the market with high governance quality. Breaking down of the WGI by their six indicators reveals that four of the indicators (control over corruption, government effectiveness, stability and avoidance of violence) are negative statistically significant with momentum returns while two indicators are not significant. As for CGIs, only one (strength of investor protection) of the four tested indicators is negative and significantly related to momentum returns.

The study fills the gap in economic literature by highlighting the association between governance quality at the country (WGI) and firm level (CGI) on stock momentum returns.

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 determinants of investors’ sentiment based on secondary stock market proxies in many empirical studies are reported. However, to the best of our knowledge, no study undertakes investor sentiment drivers developed from primary survey measures by constructing an investor sentiment index (ISI) in relation to market drivers to date. This study aims to fill this research gap by first developing the ISI for the Indian retail investors and then examining which of the stock market drivers impacts such sentiment.

The ISI is constructed using the mean scores of eight statements as formulated based on popular direct investor sentiment surveys undertaken across the world. Then, we use the multiple regression approach overall and for top 33.33% (high-sentiment) and bottom 33.33% (low-sentiment) investors based on the responses of 576 respondents on 18 statements (proxying eight study hypotheses) collected in 2016. Moreover, the demography-based classification based investors’ sentiment is examined to make our results more robust and in-depth.

On an overall basis, the IPO activities/issues and information certainty, trading volume and momentum and institutional investors’ investment activities market drivers significantly and positively impact retail investors is examined. However, only IPO activities/issues and information certainty influences both high- and low-sentiment investors. It is intriguing to report that nature of the stock markets show conflicting results for high- (negative significant) and low- (positive significant) sentiment investors.

The construction of the ISI from primary survey measure is for the first time in Indian context in relation to investigating the stock market drivers influential to retail investors’ sentiment. In addition, hypothesized market drivers are also unique, each representing different fundamental and technical characteristics associated with the Indian market.

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.