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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.

The purpose of this paper is to propose a type of hybrid bearing lubricated with supercritical carbon dioxide (S-CO₂) and to investigate the stiffness and damping characteristics of the bearing under hydrostatic status.

Established a test rig for radial bearings lubricated with S-CO₂ and used it to measure the dynamic coefficients by recording the relative and absolute displacements of bearing. Test bearing is mounted on a nonrotating, stiff shaft. Using static loading experiments to obtain structural stiffness. The dynamic coefficient regularities of the test bearing under hydrostatic status were revealed through dynamic loading experiments.

Experiment results indicate that test bearing displayed increased stiffness when subjected to high excitation frequencies and low excitation forces, as well as elevated damping when exposed to low excitation frequencies and low excitation forces. Additionally, an increase in either environmental pressure or hydrostatic recess pressure can elevate the dynamic coefficient. The effect of temperature on the dynamic coefficient is more pronounced around the critical temperature of S-CO₂.

Designed a type of hybrid bearing for use in the Brayton cycle that is lubricated with S-CO₂ and uses hydrostatic lubrication during start-stop and hydrodynamic lubrication during high-speed operation. The hybrid bearing reduces the wear and friction power consumption of gas bearing. However, few experimental analyses have been conducted by researchers in this field.

This study aims to improve the tribological properties of hydrodynamic journal bearing via surface texture, as well as the wear and antifriction mechanisms of textured bearing were represented. It provides a design direction for solving the tribological problem of rotor-bearing system.

In this paper, the variation of surface texture parameters (e.g. texture diameter, d; area density, sp; and depth, hp) were analyzed based on finite difference method. The optimal surface texture parameters were obtained by designing orthogonal experiments, and the relationship between friction and wear properties and microstructure was studied via combining electron probe microanalyzer, scanning electron microscope, X-ray diffractometer and friction and wear testing machine.

Dimensionless film pressure P increased as the d increased, whereas P first increased and then decreased as the sp and hp increased, and the maximum P was got as sp = 15% and hp = 25 µm, respectively. The friction coefficient of textured surface with suitable parameters was effectively reduced and the textured surface with the best antifriction effect was 5#. Orthogonal experimental design analysis showed that the influence order of factors on friction coefficient was as follows: sp > sp × d > d > d × hp > hp > sp × hp and the friction coefficient first decreased and then increased as the sp, d and hp increased. In addition, the friction and wear mechanism of textured bearing were three body friction and abrasive wear as the matrix structure and hard phase were a single β phase and Mn5Si3, respectively. While the antifriction mechanism of textured surface was able to store abrasive particles and secondary hydrodynamic lubrication was formed.

The sample with reasonable texture parameter design can effectively reduce friction and wear of hydrodynamic journal bearing without reducing the service life, which can provide a reference for improving the lubrication performance and mechanical efficiency of rotor-bearing system.

The purpose of this research is to study the dynamic behavior of hydrostatic squeeze film dampers made of four hydrostatic pads, fed through four capillary restrictors with micropolar lubricant.

The modified version of Reynolds equation is solved numerically by the finite differences and the Gauss–Seidel methods to determine the pressure field generated on the hydrostatic bearing flat pads. In the first step, the effects of the pad dimension ratios on the stiffness and damping coefficients are investigated. In the second step, the damping factor is evaluated with respect to the micropolar properties.

The analysis revealed that the hydrostatic squeeze film dampers lubricated with micropolar lubricants produces the maximum damping factor for characteristic length of micropolar lubricant less than 5, while the same bearing operating with Newtonian lubricants reaches its maximum damping factor at eccentricity ratios larger than 0.4.

The results obtained show that the effects of micropolar lubricants on the dynamic performances are predominantly affected by the pad geometry and eccentricity ratio.

This study aims to investigate the effects of irregular groove textures on the friction and wear performance of sliding contact surfaces. These textures possess multiple depths and asymmetrical features. To optimize the irregular groove texture structure of the sliding contact surface, an adaptive genetic algorithm was used for research and optimization purposes.

Using adaptive genetic algorithm as an optimization tool, numerical simulations were conducted on surface textures by establishing a dimensionless form of the Reynolds equation and setting appropriate boundary conditions. An adaptive genetic algorithm program in MATLAB was established. Genetic iterative methods were used to calculate the optimal texture structure. Genetic individuals were selected through fitness comparison. The depth of the groove texture is gradually adjusted through genetic crossover, mutation, and mutation operations. The optimal groove structure was ultimately obtained by comparing the bearing capacity and pressure of different generations of micro-convex bodies.

After about 100 generations of iteration, the distribution of grooved textures became relatively stable, and after about 320 generations, the depth and distribution of groove textures reached their optimal structure. At this stage, irregular texture structures can support more loads by forming oil films. Compared with regular textures, the friction coefficient of irregular textures decreased by nearly 47.01%, while the carrying capacity of lubricating oil films increased by 54.57%. The research results show that irregular texture structures have better lubrication characteristics and can effectively improve the friction performance of component surfaces.

Surface textures can enhance the friction and lubrication performance of metal surfaces, improving the mechanical performance and lifespan of components. However, surface texture processing is challenging, as it often requires multiple experimental comparisons to determine the optimal texture structure, resulting in high trial-and-error costs. By using an adaptive genetic algorithm as an optimization tool, the optimal surface groove structure can be obtained through simulation and modeling, effectively saving costs in the process.

For a lightweight and accurate description of bearing temperature, this paper aims to present an efficient semi-empirical model with oil–air two-phase flow and gray-box model.

First, the role of lubricant/coolant in bearing temperature was discussed separately, and the gray-box models on the heat convection inside a bearing cavity were also created. Next, the bearing node setting scheme was optimized. Consequently, a novel semi-empirical two-phase flow thermal grid for high-speed angular contact ball bearings was planned. With this model, the thermal network for the selected motored spindle was built, and the numerical solutions for bearing temperature rise were obtained and contrasted with the experimental values for validation. The polynomial interpolation on test data, meanwhile, was also performed to help us observe the temperature change trend. Finally, the simulations based on the current models of bearings were implemented, whose corresponding results were also compared with our research work.

The validation result indicates that the thermal prediction is more accurate and efficient when the developed semi-empirical oil–air two-phase flow model is employed to assess the thermal change of bearings. Clearly, we provide a more proper model for the thermal assessment of bearing and even spindle heating.

To the best of the authors’ knowledge, this paper introduced the oil–air separation and gray-box model for the first time to describe the heat exchange inside bearing cavities and accordingly presents an efficient semi-empirical oil–air two-phase flow model to evaluate the bearing temperature variation by using thermal network method.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2023-0180/

This study is the first to investigate the causal relationship between Bitcoin and equity price returns by sectors. Previous studies have focused on aggregated indices such as S&P500, Nasdaq and Dow Jones, but this study uses mixed frequency and disaggregated data at the sectoral level. This allows the authors to examine the nature, direction and strength of causality between Bitcoin and equity prices in different sectors in more detail.

This paper utilizes an Unrestricted Asymmetric Mixed Data Sampling (U-AMIDAS) model to investigate the effect of high-frequency Bitcoin returns on a low-frequency series equity returns. This study also examines causality running from equity to Bitcoin returns by sector. The sample period covers United States (US) data from 3 Jan 2011 to 14 April 2023 across nine sectors: materials, energy, financial, industrial, technology, consumer staples, utilities, health and consumer discretionary.

The study found that there is no causality running from Bitcoin to equity returns in any sector except for the technology sector. In the tech sector, lagged Bitcoin returns Granger cause changes in future equity prices asymmetrically. This means that falling Bitcoin prices significantly influence the tech sector during market pullbacks, but the opposite cannot be said during market rallies. The findings are consistent with those of other studies that have established that during market pullbacks, individual asset prices have a tendency to decline together, whereas during market rallies, they have a tendency to rise independently. In contrast, this study finds evidence of causality running from all sectors of the equity market to Bitcoin.

The findings have significant implications for investors and fund managers, emphasizing the need to consider the asymmetric causality between Bitcoin and the tech sector. Investors should avoid excessive exposure to both Bitcoin and tech stocks in their portfolio, as this may lead to significant drawdowns during market corrections. Diversification across different asset classes and sectors may be a more prudent strategy to mitigate such risks.

The study's findings underscore the need for investors to pay close attention to the frequency and disaggregation of data by sector in order to fully understand the true extent of the relationship between Bitcoin and the equity market.

This paper examines the relationship between sovereign credit default swaps (CDS) and several macroeconomic factors in an asymmetric setting and distinguishes between short-run and long-run impacts. Country-specific factors (e.g. equity index, international reserves, interest rate and industrial production) and global factors (e.g. US stock volatility [VIX], geopolitical risk and oil price) are the main explanatory variables.

This analysis uses a nonlinear autoregressive distributed lag approach that enables us to study both long-run and short-run dynamics.

This study results show that two country-specific factors (equity index and international reserves) and two global factors (VIX and oil price) are the most important factors and affect CDS asymmetrically.

The asymmetric relationships between sovereign CDS and variables in bull and bear markets can also be studied. Consideration of asymmetries in the variance could also be a fruitful step taken for further research.

The findings imply that investors and portfolio managers should design their investment and hedging decisions related to government bonds by taking into account the existence of an asymmetric relationship.

Moreover, policymakers can benefit from this asymmetric information in the timing of debt issuance.

This paper examines the relationship between sovereign CDS and several macroeconomic factors in an asymmetric setting and distinguishes between short-run and long-run impacts.

This study presents time-series data estimations on the association between the indicators of institutional environment and inward foreign direct investment (FDI) in India utilizing a comprehensive data set from 1996 to 2021.

The study employs the nonlinear autoregressive distributive lag (NARDL) model. The asymmetric ARDL framework evaluates the existence of cointegration among the factors under study and highlights the underlying nonlinear effects that may exist in the long and short run.

The significance of coefficients of negative shock to “control of corruption” and positive shock to “rule of law” is greater when compared to “government effectiveness, regulatory quality, political stability/absence of violence.” The empirical outcomes suggest the positive influence of rule of law, political stability and government effectiveness on FDI inflows. A high “regulatory quality” is observed to deter foreign investment. The “voice and accountability” index and negative shocks to the “rule of law” are exhibited to have no substantial impact on the amount of FDI that the country receives.

This study empirically examines the institutional determinants of FDI in India for a comprehensive period of 1996–2021. The study's findings imply that quality of the institutional environment has a significant bearing on India's inward FDI.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0375

The purpose of this study is to conduct a thorough empirical investigation of the intricate relationship between urban housing sales prices and land supply prices in China, with the aim of elucidating the underlying economic principles governing this dynamic interplay.

Using monthly data of China, the authors use the asymmetry nonlinear autoregressive distributed lag (NARDL) model to test for nonlinearity in the relationship between land supply price and urban housing prices.

The empirical results confirm the existence of an asymmetric relationship between land supply price and urban housing prices. The authors find that land supply price has a positive and statistically significant impact on urban housing prices when land supply is increasing. Policymakers should strive to strike a balance between safeguarding residents’ housing rights and maintaining market stability.

Although the asymmetric effect of land supply price has been identified as a significant contributor in this study, it is important to note that the research primarily relies on time series data and focuses on analysis at the national level. Although time series data offer a macroscopic perspective of overall trends within a country, they fail to adequately showcase the structural variations among different cities.

To ensure a stable housing market and meet residents’ housing needs, policymakers must reexamine current land policies. Solely relying on restricting land supply to control housing prices may yield counterproductive results. Instead, increasing land supply could be a more viable option. By rationally adjusting land supply prices, the government can not only mitigate excessive growth in housing prices but also foster the healthy development of the housing market.

First, the authors have comprehensively evaluated the impact of land supply prices in China on urban housing sales prices, examining whether they play a facilitating or mitigating role in the fluctuation of these prices. Second, departing from traditional linear analytical frameworks, the authors have explored the possibility of a nonlinear relationship existing between land supply prices and urban housing sales prices in China. Finally, using an advanced NARDL model, the authors have delved deeper into the asymmetric effects of land supply prices on urban housing sales prices in China.