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Recent studies suggested the ratio of option to stock volume reflected the private information. Informed traders were drawn to the options market for its leverage effect and relatively low transaction costs. Informed traders use different intervals of option moneyness to execute their strategies. The question is which types of option moneyness were traded by informed traders and what information was reflected in the market. In this study, the authors focused on this question and constructed a method for capturing the activity of informed traders in the options and stock markets.

The authors constructed the daily measure, moneyness option trading volume to stock trading volume ratio (MOS), to capture the activity of informed traders in the market. The authors formed quintile portfolios sorted with respect to the moneyness option to stock trading volume ratio and provided the capital asset pricing model and Fama–French five-factor alphas. To determine whether MOS had predictive ability on future stock returns after controlling for company characteristic effects, the authors formed double-sorted portfolios and performed Fama–Macbeth regressions.

The authors found that the firms in the lowest moneyness option trading volume to stock trading volume ratio for put quintile outperform the highest quintile by 0.698% per week (approximately 36% per year). The firms in the highest moneyness option trading volume to stock trading volume ratio for call quintile outperform the lowest quintile by 0.575% per week (approximately 30% per year).

The authors first propose the measures, moneyness option trading volume to stock trading volume ratio, that combined with the trading volume and option moneyness. The authors provide evidence that the measures have the predictive ability to the future stock returns.

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.

In this study, we investigate what drives the MAX effect in the South Korean stock market. We find that the MAX effect is significant only for overpriced stocks categorized by the composite mispricing index. Our results suggest that investors' demand for the lottery and the arbitrage risk effect of MAX may overlap and negate each other. Furthermore, MAX itself has independent information apart from idiosyncratic volatility (IVOL), which assures that the high positive correlation between IVOL and MAX does not directly cause our empirical findings. Finally, by analyzing the direct trading behavior of investors, our results suggest that investors' buying pressure for lottery-like stocks is concentrated among overpriced stocks.

The study examines the relationship between news intensity, media sentiment and market microstructure invariance-implied measures of trading activity and liquidity of Chinese property developer stocks during the 2020–2022 Chinese property sector crisis.

The authors adopt the extension of the news article invariance hypothesis, which is a generalization of the market microstructure invariance conjecture, from January 2020 to January 2022 to test specific quantitative relationships between the arrival rate of public information, trading activity and a nonlinear function of a proxy for the probability of informed trading. Empirical tests are based on a dataset of 22,412 firm-day observations and two count-data models to correct for overdispersion and the excess number of zeros. Seventy-five stocks of Chinese companies from the property development industry (including the China Evergrande Group) were included in the sample.

The authors reject the news article invariance hypothesis but document a positive and significant relationship between the flow of public information and risk liquidity. Additionally, the authors find that the proxy for informed trading activity is positively related to the arrival rates of public information from October 2021 to January 2022.

The findings support the hypothesis that negative (positive) media sentiment induces significant deterioration (insignificant improvement) in stock liquidity. The authors find that an increase in the number of news articles about a company corresponds to a higher liquidity of Chinese property developers' stocks after controlling for media sentiment.

The abnormality of the month-of-the-year and Ramadan effects has extensively existed in the stock and other markets. The commercial strategy pattern and the computation of such predictable patterns in the market allow investors to make money. By using anomalies such as the month-of-the-year and the Ramadan effects on earnings management (EM), it is possible to achieve such a goal. This study aims to investigate the month-of-the-year effect and the Ramadan effect on the relationship between accrual earnings management and real earnings management (AEM and REM, respectively) and liquidity in the Iranian capital market.

This empirical analysis comprises a panel data set of 80 listed firms (400 observations) on the Tehran Stock Exchange from 2016 to 2020.

The findings exhibit that when AEM and REM increase, information asymmetry also increases. The simultaneous increase of these variables leads to a decrease in stock liquidity. Furthermore, the results indicate that the month-of-the-year and Ramadan effects intensify the negative relationship between AEM and REM with stock liquidity. Therefore, EM is affected by the investor’s behavior in specific months.

Anomalies caused by the Ramadan effect and the month-of-the-year effect on reducing liquidity in the Iranian stock market were confirmed. Investors can use these anomalies to identify predictable patterns, exchange securities according to those patterns and earn abnormal returns.

To the best of the authors’ knowledge, this is the first study that empirically examined the simultaneous effect of Gregorian and Islamic calendar anomalies on the relationship between EM and liquidity, and while helping managers and other readers, it can be the basis for future research.

The authors empirically examined the theoretically recognized industrial linkages between manufacturing and services from the trade perspective. In particular, they confirmed the trade effect of manufacturing on services, given that global value chain fragmentation pervades and splits manufacturing and services segments separately in developed and developing countries.

Based on observations of 47 countries with manufacturing and service trade data from 1990 to 2020 and with gravity model specification, the authors primarily used the Poisson pseudo-maximum likelihood (PPML) estimation with multiple levels of fixed effects. Considering that many zero values are included in the dependent variable and potential endogeneity, other methods such as Tobit regression, Heckman estimation and two-stage least squares estimation (2SLS) are used. Subsample estimation also supplemented the empirical research.

The results showed that manufacturing trade is a stepping-stone rather than an obstacle to service trade. This finding exhibited significant robustness under different model specifications, instrumental variable estimation and subsample checks. Moreover, in contrast to the north–north country ties, manufacturing trade between northern and southern countries has played a prominent stepping-stone role; meanwhile, manufacturing trade among core–peripheral countries has a considerably more significant impact than the outcomes of core–core and peripheral–peripheral countries.

The authors provided direct clarification and revealed that trade in manufacturing remains the demand basis for service trade. As trade in manufacturing and services are typical phenomena of transnational production linkages, the authors suggested exploring the underlying role of global value chain (GVC) fragmentation and the offset and even barrier effect of biased institutional arrangements on GVC fragmentation.

This study aims to provide empirical evidence on the impact of foreign share ownership on the liquidity of the Tunisian Stock Exchange (TSE).

The authors hypothesize in the first strand that stock liquidity could be positively affected by foreign ownership based on the real friction channel. The authors then hypothesize in the second strand, based on the information friction channel, that foreign ownership's impact on stock liquidity could be insignificant or negative and that foreign investors raise the level of information asymmetry. A sample of 318 firm-year observations from Tunisia over the 2012–2017 period and a random-effects estimation were used. Moreover, using the 2SLS estimator, a robustness check framework was applied in order to address any potential reverse causality concerns.

The authors find strong evidence that higher foreign ownership improves stock liquidity. More specifically, firms with higher foreign ownership engender a lower bid-ask spread, a better stock ability to absorb a large amount of trading volume, and a larger depth. These findings are still valid when reverse causality concerns are addressed through the use of the 2SLS estimator.

The paper contributes to the existing literature by focusing on the ownership–liquidity relationship on a frontier market. It provides further empirical support that higher corporate governance quality reduces the information asymmetry problem and enhances stock market liquidity.

There is widespread belief that intermediaries in African agri-food value chains have disproportionate market power. In this paper, the authors examine this belief by uncovering the purchasing and selling prices, costs and profit margins by farmers, intermediaries and retailers in the matooke (cooking banana) value chain in Uganda, and by analysing the prevailing value chain and market structures, seasonal entry and exit dynamics and the trading relationships in the chain.

Data for this study were collected along the trading routes from the main matooke producing districts in South-West Uganda (Kabarole, Bunyangabo, Bushenyi, Isingiro and Mbarara) to the main urban markets around the capital Kampala. A structured survey was administered with 383 producers, 172 collectors and wholesalers and 71 retailers. In addition, key informant interviews and focus group discussions were held.

The authors find that price mark-ups by intermediaries (selling prices minus purchasing prices) vary with the type of intermediary, season and location but generally reflect the costs of moving matooke down the value chain to the urban consumer. The authors do not find evidence for disproportionate market power among the intermediaries in the chain. Intermediaries enter and exit the market in peak and off-peak season, such that profits are kept in check. This seasonality does imply a small shift in market power in favour of farmers in off-peak season and in favour of intermediaries in the peak season.

The investigation concentrated on an important and relatively homogenous staple crop along its main trade route. More remote areas, where there is less of an abundance of matooke, might still be characterised by local monopsonies where intermediaries have more market power due to high search and transport costs. Similarly, (local) monopsonies might exist for products for which there is a smaller market (segment), for products with a stronger seasonal variation in supply and for more perishable products.

While there is an important literature on the role of intermediaries in African agri-food value chains, the evidence on intermediary market power is scant. Beliefs on intermediary market power are largely based on anecdotal evidence from farmers or inferred from observed prices or market structures. The paper contributes in addressing this important knowledge gap by studying the matooke value chain in Uganda.

The study endeavors to explore whether the financialization of agricultural commodities, traditionally viewed as a catalyst for price volatility, has any repercussions on food security in BRICS economies.

The empirical analysis employs the examination of three agricultural commodities, namely wheat, maize and soybean. Utilizing data from the Chicago Board of Trade on futures trading for these commodities, we focus on parameters such as annual trading volume, annual open interest contracts and the ratio of annual trading volume to annual open interest contracts. The study spans the period 2000–2021, encompassing pre- and post-financial crisis analyses and specifically explores the BRICS countries namely the Brazil, Russia, India, China and South Africa. To scrutinize the connections between financialization indicators and food security measures, the analysis employs econometric techniques such as panel data regression analysis and a moderating effects model.

The results indicate that the financialization of agricultural products contributes to the heightened food price volatility and has adverse effects on food security in emerging economies. Furthermore, the study reveals that the impact of the financialization of agricultural commodities on food security was more pronounced in emerging nations after the global financial crisis of 2008 compared to the pre-crisis period.

This paper seeks to draw increased attention to the financialization of agricultural commodities by presenting empirical evidence of its potential impact on food security in BRICS economies. The findings serve as a valuable guide for policymakers, offering insights to help them safeguard the security and availability of the world’s food supply.

Very few studies have explored the effect of financialization of agricultural commodities on food security covering a sample of developing economies, with sample period from 2000 to 2021, especially at the individual agriculture commodity level. Understanding the evolving effects of financialization is further improved by comparing pre and post-financial crisis times.

Investor sentiment (optimism or pessimism) may influence investors to follow others (herding) while taking their investment decisions. Herding may result in bubbles and crashes in the financial markets. The purpose of the study is to examine the presence of herding and the effects of investor sentiment on herding in China and Pakistan.

The investor sentiment is captured by five variables (trading volume, advance/decline ratio, weighted price-to-earnings ratio, relative strength index and interest rates) and a sentiment index developed through principal component analysis (PCA). The study uses daily prices of 2,184 firms from China and 568 firms from Pakistan for the period 2005 to 2018.

The study finds that herding prevails in China while reverse herding prevails in Pakistan. Interestingly, as investors become optimistic, herding in China and reverse herding in Pakistan decrease. This indicates that herding and reverse herding are greater during pessimistic periods. Further, the increase in herding in one market reduces herding in the other market. Moreover, optimistic sentiment in the Chinese market increases herding in the Pakistani market but the reverse is not true.

Considering the greater global financial liberalization, and better opportunities for emotion sharing, this study has important implications for regulators and investors. Market participants need to understand the prevalent irrational behavior before trading in the markets.

Since individual proxies may depict different picture of the relationship between sentiment and herding therefore the study also develops a sentiment index through PCA and incorporates this index in the analysis. Further, this study examines cross-country effects of herding and investor sentiment.