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The authors provide a comprehensive empirical examination on the impact of earnings quality on stock price crash risk in China.

The authors acknowledge and distinguish two-dimensional proxies for earnings quality – accounting-based (earnings management degree) and market-based (earnings transparency) known in accounting and finance literature.

The authors find that both generally indicate that better earnings quality is associated with less crashes. However, extremely high earnings transparency interacted with insider trading profit can also actually exacerbate stock price crashes.

This study is the first to highlight the pertinence of accounting-based measures to proxy for earnings quality in a fast-growing emerging market environment such as China.

Man has been seeking an ideal existence for a very long time. In this existence, justice, love, and peace are no longer words, but actual experiences. How ever, with the American preemptive invasion and occupation of Afghanistan and Iraq and the subsequent prisoner abuse, such an existence seems to be farther and farther away from reality. The purpose of this work is to stop this dangerous trend by promoting justice, love, and peace through a change of the paradigm that is inconsistent with justice, love, and peace. The strong paradigm that created the strong nation like the U.S. and the strong man like George W. Bush have been the culprit, rather than the contributor, of the above three universal ideals. Thus, rather than justice, love, and peace, the strong paradigm resulted in in justice, hatred, and violence. In order to remove these three and related evils, what the world needs in the beginning of the third millenium is the weak paradigm. Through the acceptance of the latter paradigm, the golden mean or middle paradigm can be formulated, which is a synergy of the weak and the strong paradigm. In order to understand properly the meaning of these paradigms, however, some digression appears necessary.

Using the L. Bebchuk, Cohen, and Ferrell (2009) entrenchment index (E-index), the authors examine the relation between management entrenchment and the probability of a firm being implicated in the stock option backdating scandal. The authors conduct the analysis of this study using logistic regression, and they document a negative relation between the E-index and the probability of a firm being implicated in the stock option backdating scandal. The results of this study are consistent with the view that management entrenchment is advantageous to shareholders as it protects managers from short-term reporting pressures and egregious opportunistic behavior that can be detrimental to firm value.

This study aims to derive a novel spatial numerical method based on multidimensional local Taylor series representations for solving high-order advection-diffusion (AD) equations.

The parabolic AD equations are reduced to the nonhomogeneous elliptic system of partial differential equations by utilizing the Chebyshev spectral collocation method (ChSCM) in the temporal variable. The implicit-explicit local differential transform method (IELDTM) is constructed over two- and three-dimensional meshes using continuity equations of the neighbor representations with either explicit or implicit forms in related directions. The IELDTM yields an overdetermined or underdetermined system of algebraic equations solved in the least square sense.

The IELDTM has proven to have excellent convergence properties by experimentally illustrating both h-refinement and p-refinement outcomes. A distinctive feature of the IELDTM over the existing numerical techniques is optimizing the local spatial degrees of freedom. It has been proven that the IELDTM provides more accurate results with far fewer degrees of freedom than the finite difference, finite element and spectral methods.

This study shows the derivation, applicability and performance of the IELDTM for solving 2D and 3D advection-diffusion equations. It has been demonstrated that the IELDTM can be a competitive numerical method for addressing high-space dimensional-parabolic partial differential equations (PDEs) arising in various fields of science and engineering. The novel ChSCM-IELDTM hybridization has been proven to have distinct advantages, such as continuous utilization of time integration and optimized formulation of spatial approximations. Furthermore, the novel ChSCM-IELDTM hybridization can be adapted to address various other types of PDEs by modifying the theoretical derivation accordingly.

The purpose of this paper is to analyze volatility transmission between the Japanese stock and foreign exchange markets.

In contrast to the existing literature, industry‐level stock data are applied to a trivariate Baba, Engle, Kraft and Kroner‐generalised autoregressive conditional heteroscedasticity (BEKK‐GARCH) model that also includes comparable US industrial stocks returns as a control variable.

Using daily data over the study period 1994‐2007, it was found that news shocks in the Japanese currency market account for volatility transmission in eight of the ten industrial sectors considered. Evidence was also found of significant asymmetric effects in five of these industries.

While the BEKK‐GARCH model enables analysis of volatility transmission between the stock and foreign markets against a background of conditional correlation and asymmetries, the model requires the estimation of a large number of parameters, which can be problematic for a limited dataset.

The paper's findings have important implications for understanding international volatility transmission involving the stock and foreign exchange markets. This in turn can provide insight into investor behaviour.

Modelling accurately the transient behaviour of natural convection flow in enclosures been a challenging task because of a variety of numerical errors which have limited achieving the higher order temporal accuracy. A fourth-order accurate finite difference method in both space and time is proposed to overcome these numerical errors and accurately model the transient behaviour of natural convection flow in enclosures using vorticity–streamfunction formulation.

Fourth-order wide stencil formula with appropriate one-sided difference extrapolation technique near the boundary is used for spatial discretisation, and classical fourth-order Runge–Kutta scheme is applied for transient term discretisation. The proposed method is applied on two transient case studies, i.e. convection–diffusion of a Gaussian Pulse and Taylor Vortex flow having analytical solution.

Error magnitude comparison and rate of convergence analysis of the proposed method with these analytical solutions establish fourth-order accuracy and prove the ability of the proposed method to truly capture the transient behaviour of incompressible flow. Also, to test the transient natural convection flow behaviour, the algorithm is tested on differentially heated square cavity at high Rayleigh number in the range of 10³-10⁸, followed by studying the transient periodic behaviour in a differentially heated vertical cavity of aspect ratio 8:1. An excellent comparison is obtained with standard benchmark results.

The developed method is applied on 2D enclosures; however, the present methodology can be extended to 3D enclosures using velocity–vorticity formulations which shall be explored in future.

The proposed methodology to achieve fourth-order accurate transient simulation of natural convection flows is novel, to the best of the authors’ knowledge. Stable fourth-order vorticity boundary conditions are derived for boundary and external boundary regions. The selected case studies for comparison demonstrate not only the fourth-order accuracy but also the considerable reduction in error magnitude by increasing the temporal accuracy. Also, this study provides novel benchmark results at five different locations within the differentially heated vertical cavity of aspect ratio 8:1 for future comparison studies.

The purpose of this paper is to analyze and forecast the Chinese term structure of interest rates using functional principal component analysis (FPCA).

The authors propose an FPCA-K model using FPCA. The forecasting of the yield curve is based on modeling functional principal component (FPC) scores as standard scalar time series models. The authors evaluate the out-of-sample forecast performance using the root mean square and mean absolute errors.

Monthly yield data from January 2002 to December 2016 are used in this paper. The authors find that in the full sample, the first two FPCs account for 98.68 percent of the total variation in the yield curve. The authors then construct an FPCA-K model using the leading principal components. The authors find that the FPCA-K model compares favorably with the functional signal plus noise model, the dynamic Nelson-Siegel models and the random walk model in the out-of-sample forecasting.

The authors propose a functional approach to analyzing and forecasting the yield curve, which effectively utilizes the smoothness assumption and conveniently addresses the missing-data issue.

To the best knowledge, the authors are the first to use FPCA in the modeling and forecasting of yield curves.

The purpose of this paper is to numerically investigate steady, laminar natural and mixed convection heat transfer in a two-dimensional cavity by using a finite volume method with a fourth-order approximation of convective terms, with and without the presence of nanoparticles. Highly accurate benchmark results are also provided.

A finite volume method on a non-uniform staggered grid is used for the solution of two-dimensional momentum and energy conservation equations. Diffusion terms, in the momentum and energy equations, are approximated using second-order central differences, whereas a non-uniform four-point fourth-order interpolation (FPFOI) scheme is developed for the convective terms. Coupled mass and momentum conservation equations are solved iteratively using a semi-implicit method for pressure-linked equation method.

For the case of natural convection problem at high-Rayleigh numbers, grid density must be sufficiently high in order to obtain grid-independent results and capture reality of the physics. Heat transfer enhancement for natural convection is observed up to a certain value of the nanoparticle volume fraction. After that value, heat transfer deterioration is found with increasing nanoparticle volume fraction.

Developed a non-uniform FPFOI scheme. Highly accurate benchmark results for the heat transfer of Al₂O₃-water nanofluid in a cavity are provided.

This study used extended Unified Theory of Acceptance and Use of Technology (UTAUT) model to examine the effect of personal expectancy (PE), efforts expectancy (EE), social influence (SI), facilitating conditions (FC), hedonic motivation (HM), price value (PV) and habit (H) on behavioural intention (BI) to use Chat Generative Pre-Trained Transformer (ChatGPT) in higher education for an Indian context. The study also examined moderating effects of students’ self-innovativeness (SIN) and integrity (INT) on the relationship between BI and use behaviour (UB) for ChatGPT.

A sample of 311 students has been selected from Northern states of India by applying stratified proportionate random sampling method and four disciplines – engineering, business administration, science and fine arts were used as different strata in the sample selection process. Partial least squares structural equation modelling (PLS-SEM) approach has been used in data analysis to assess proposed theoretical model.

The study found PE, FC, PV and H significantly account for students’ BI and actual use of ChatGPT, whereas EE, SI and HM showed a negligible impact on BI. The BI was also found non-significant in predicting the usage behaviour for ChatGPT. The moderation effects of SIN and INT of students were also found non-significant on the relationship between BI and UB.

A limited sample size of study and its focus on Northern states of India constrain the generalizability of findings to the other parts of world.

The study helps to understand the nuances associated with advanced artificial intelligence (AI)-driven tool such as ChatGPT in higher education for the application of best-practices. Therefore, this study aims to bridge this gap by examining determinants of ChatGPT usage with extended version of UTAUT model in Indian context by using additional constructs such as SIN and INT.