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The purpose of this paper is to bridge the gap between the existing theoretical and empirical studies by examining the asymmetric return–volume relationship. Indeed, the authors aim to shed light on the return–volume linkages for French-listed small and medium-sized enterprises (SMEs) compared to blue chips across different market regimes.

This study includes both large capitalizations included in the CAC 40 index and listed SMEs included in the Euronext Growth All Share index. The Markov-switching (MS) approach is applied to understand the asymmetric relationship between trading volume and stock returns. The study investigates also the causal impact between stock returns and trading volume using regime-dependent Granger causality tests.

Asymmetric contemporaneous and lagged relationships between stock returns and trading volume are found for both large capitalizations and listed SMEs. However, the causality investigation reveals some differences between large capitalizations and SMEs. Indeed, causal relationships depend on market conditions and the size of the market.

This paper explains the asymmetric return–volume relationship for both large capitalizations and listed SMEs by incorporating several psychological biases, such as the disposition effect, investor overconfidence and self-attribution bias. Future research needs to deepen the analysis especially for SMEs as most of the literature focuses on large capitalizations.

This empirical study has fundamental implications for portfolio management. The findings provide a deeper understanding of how trading activity impact current returns and vice versa. The authors’ results constitute an important input to build and control trading strategies.

This paper fills the literature gap on the asymmetric return–volume relationship across different regimes. To the best of the authors’ knowledge, the present study is the first empirical attempt to test the asymmetric return–volume relationship for listed SMEs by using an accurate MS framework.

This study investigates firms' innovation behaviour under environmental change. Therefore, it examines the effect of trade disputes on corporate technological innovation and how product market competition moderates this relationship.

This research tests the hypotheses using the fixed effects model based on panel data of publicly listed enterprises in China from 2007–2020.

The empirical results validate the positive association between trade disputes and corporate research and development (R&D) intensity as well as the U-shaped relationship between trade disputes and radical innovation. Additionally, the moderating effect of product market competition is verified: a concentrated market with less competition flattens the U-shaped curve of radical innovation induced by trade disputes; as the market becomes more concentrated and less competitive, the U-shaped relationship eventually turns into an inverted U.

First, this study contributes to the corporate innovation and trade dispute literature by expanding the environmental antecedents of technological innovation and the firm-level consequences of trade disputes. Second, this study enriches the theoretical framework of the environment–innovation link through an integrated perspective of contingency theory and dynamic capabilities view. Third, instead of the traditional linear mindset which had led to contradictory results, this study explores a curvilinear effect in the environment–innovation relationship.

This paper aims to examine the customer-based and supplier-based trade credit gaps for USA firms from 1970 to 2020.

The authors' study examines USA companies from 1970 to 2020. The authors begin with an analysis of the trends in aggregate working capital, the capital's components and the trade credit gaps. Various regression models are used to estimate the impacts of identified firm characteristics and unidentified sources on customer-based and supplier-based trade credit gaps over time. The authors then decompose the impacts of firm characteristics to further understand whether changing firm characteristics and/or changing sensitivity to firm characteristics drive the variation in trade credit gaps.

There is a gradual reduction in the customer-based trade credit gap and a substantial expansion in the supplier-based trade credit gap. Though identified firm characteristics have dominant impacts on observed trade credit gaps, there is evidence of the effects of time and unobservable factors. The main source of changes in customer-based and supplier-based trade credit gaps lies in changes in sensitivity to firm characteristics. In addition, the authors find that firm age is the factor with the largest average effect on both trade credit gaps when examining the full sample period. However, different firm characteristics appear to be the key driver of variations in trade credit gaps over time and across the two types of trade credit gaps. The authors also find that financial distress has the least impact on both customer-based and supplier-based trade gaps. There are variations in the firm characteristics with the largest impacts when evaluating decade-long evaluation periods.

To the authors' knowledge, this is the first paper to examine the customer-based and supplier-based trade credit gaps. The connection between trade credit and the trade credit's corresponding inventory (INV) component extends prior literature on the joint management of trade credit and INV. The authors analyze both identified firm characteristics and unidentified sources in the search for explanations of the trade credit gaps. Furthermore, the authors' study explores the channels through which firm characteristics affect different types of trade credit gaps. The authors' findings help identify relevant and irrelevant risk factors of corporate working capital policy.

The experience of rising trade imbalance between Nigeria and its key trading partners in recent years motivated this study. Previous studies on this issue either ignored bilateral level or assumed that the effect of crude oil price and/or exchange rate changes on trade balance is symmetric. Consequently, this study investigates whether Nigeria's bilateral trade balance with Belgium, China, United Kingdom (UK) and USA is responding symmetrically or asymmetrically to changes in oil price and exchange rate.

The authors used nonlinear autoregressive-distributed lag (NARDL) model that decomposed oil price and exchange rate into partial sum processes of positive and negative changes over the period 1999Q1–2019Q4.

The study finds that the effects of oil price hike and plunge asymmetrically influence Nigeria's trade balance with the UK and USA. Further evidence indicated that oil price plunge exerts greater influence than price hike in all the cases, except the UK in the long run. Furthermore, Nigeria's trade balance responds asymmetrically and significantly to changes in exchange rate with China in the long run and with China and the UK in the short run. Specifically, the depreciation effect is more prominent than appreciation.

Significant contributions to the existing literature in Nigeria include the recognition that the effects of oil price and exchange rate changes on trade are asymmetric and the disaggregation of trade into bilateral level to identify country-specific effect.

This study investigates the impact of simultaneously replacing both midday single-price call auction and lunch break with multi-price continuous trading on intraday volatility–volume patterns as well as the intraday volatility–volume nexus.

The analysis utilises 150 m tick-by-tick transaction data related to 333 stocks traded on Borsa Istanbul Equity Market covering a period of 2 months prior to and following the change. In addition to graphic comparisons, the study uses difference in mean tests, panel-fixed generalized least squares (GLS), panel-random GLS and random-effects linear models with AR(1) disturbance regression estimations.

The results show that intraday volatility and trading volume form an inverse J-shape and are positively correlated. It is observed that the implementation of the regulation change decreased intraday volatility and increased trading volume. Additionally, the results indicate a negative volatility–liquidity and a positive volume–liquidity relationship, supporting the mixture of distribution hypothesis.

Enhanced market efficiency provides greater opportunity for investment and risk management. Investors can benefit from the findings on the intraday volatility–volume nexus, which is an indicator of informed trading, and regulatory authorities can use volume to oversight volatility.

This very rare regulation change of the simultaneous replacement of the lunch break and midday call auction with continuous trading is investigated in the context of intraday volume and volatility. This study also expands upon some important findings on the volume–volatility nexus for the Turkish Stock Market.

This paper explores the empirical relationship between population age structure and bilateral trade.

The author includes age structure in both log and Poisson pseudo-maximum likelihood (PPML) formulations of the gravity equation of trade. The author studies relative age effects, using differences in the demographic structure of each country-pair.

The author finds that a relatively larger share of population in working age increases bilateral exports. This is robust to various estimation models, as well as to changes in the method of specifying the demographic controls. Old-age shares have a negative, but less robustly estimated impact on trade. Estimating instead the balance of trade between trading partners produces similar results, with positive effects of age structure peaking later in working life.

Global populations are poised to undergo a massive transition. Trade a crucial way that the demographic deficits of one country may be offset by the dividends of another as comparative advantages shift along with the size and strength of their underlying workforce.

The author’s work is among the first to quantify the effect of relative age structure between two countries and their bilateral trade flows. Focusing on the aggregate flows, relative age shares and PPML estimates of the trade relationship, this paper provides the most comprehensive picture to date on how age structure affects trade.

The purpose of this research is to systematically scrutinize the influence of macroeconomic determinants on trade openness, through the lens of various trade theories, with a particular focus on the economies of the GIPSI countries – Greece, Ireland, Portugal, Spain and Italy.

This study investigates the macroeconomic factors influencing trade openness in the GIPSI economies from 1995 to 2020. Methods include stepwise regression (SR) for model selection, Pedroni panel cointegration test and panel regression results. The analysis uses advanced panel regressions, including FMOLS, Panel OLS and FEM. The long-term dynamics were tested using Pedroni cointegration, while Granger causality testing was used to examine the causal direction between the trade openness ratio and trade determinant.

The results show both long-term and short-term relationships between trade openness and (1) foreign direct investment, (2) labor force participation rate, (3) trade reserves and (4) trade balance. The researchers also detected unidirectional and bidirectional causality relationships between trade openness and these four factors. The study also revealed that trade reserves (TR) emerge as the most influential determinant of trade openness, and per capita income does not exhibit economic significance concerning the trade openness of GIPSI economies.

This research is conducted within the context of the GIPSI nations (Greece, Ireland, Portugal, Spain and Italy). As such, the outcomes may not be universally applicable to other economic systems due to the distinct institutional settings and governance structures across different economic groups. Future investigations may explore the relationship between trade openness and its determinants by incorporating different variables.

To the best of the authors' knowledge, this is the first study investigating the theory that suggested trade drivers drive the trade openness of GIPSI countries context. By focusing on GIPSI countries, the study offers a unique perspective on the dynamics of trade openness in economies that have experienced financial crises and stringent austerity measures.

The purpose of this study is to analyze the dynamic changes of the arms trade network not only from the network structure but also the influence mechanism from the aspects of the economy, politics, security, strategy and transaction costs.

The study employs the Temporal Exponential Random Graph Model and the Separable Temporal Exponential Random Graph Model to analyze the endogenous network structure effect, the attribute effect and the exogenous network effect of 47 major arms trading countries from 2015 to 2020.

The results show that the international arms trade market is unevenly distributed, and there are great differences in military technology. There is a fixed hierarchical structure in the arms trade, but the rise of emerging countries is expected to break this situation. In international arms trade relations, economic forces dominate, followed by political, security and strategic factors.

Economic and political factors play an important role in the arms trade. Therefore, countries should strive to improve their economic strength and military technology. Also, countries should increase political mutual trust and gain a foothold in the industrial chain of arms production to enhance their military power.

The contribution of this paper is to analyze the special trade area of arms trade from a dynamic network perspective by incorporating economic, political, security, strategic and transaction cost factors together into the TERGM and STERGM models.