Xiaonong Zhang, Sakthi Mahenthiran and Henry He Huang
The purpose of this paper is to examine governance and earnings management implications of the delisting regulation in China, which designates firms with two consecutive losses as…
Abstract
Purpose
The purpose of this paper is to examine governance and earnings management implications of the delisting regulation in China, which designates firms with two consecutive losses as Special Treatment (ST) firms and delists such firms, should two more years of consecutive losses occur.
Design/methodology/approach
Samples were selected using the matching‐sampling method, and interrupted time‐series Logit regression analyses was used to test the determinants of ST firms using corporate governance factors and earnings quality.
Findings
It was found that firms which subsequently become ST firms have greater agency problems, as indicated by divergence of ownership and less independent boards, as measured by the number of independent directors. The ST firms subsequently reduce their agency costs by increasing ownership concentration and increasing the number of independent directors. Additionally, the results suggest that ST firms engage in earnings management after the first year of loss.
Practical implications
The paper suggests that agency problems play an important role in financial performance, and the Chinese delisting regulation does lead to improvements in governance; nevertheless, it might force firms to engage in earnings manipulation.
Originality/value
Distinct from previous empirical research that has examined earnings management, the authors study it in the context of the delisting regulation in China. Additionally, it is a longitudinal study examining how delisting regulations affect the governance of the firm under financial distress.
Details
Keywords
Henry Huang, Quanxi Wang and Xiaonong Zhang
The purpose of this paper is to investigate whether managerial ownership affects the association between shareholder rights and the cost of equity capital.
Abstract
Purpose
The purpose of this paper is to investigate whether managerial ownership affects the association between shareholder rights and the cost of equity capital.
Design/methodology/approach
Prior literature has shown that strong shareholder rights are associated with a lower level of cost of equity capital. This paper empirically tests the interaction between managerial ownership and shareholder rights on affecting the cost of equity capital, using Gompers et al.'s governance score and Ohlson and Juettner‐Nauroth's estimate of cost of equity capital. To mitigate the endogeneity arising from other governance variables affecting both shareholder rights and the cost of equity capital, the paper adopts both OLS and two‐stage regression.
Findings
The results indicate that managerial ownership aligns managers' interests with those of shareholders, leading to a lesser degree of agency problems and lower cost of equity capital. Furthermore, the evidence suggests that managerial ownership could substitute for shareholder rights in affecting the cost of equity capital, making strong shareholder rights less important in a high managerial ownership setting.
Research limitations/applications
Findings in this paper suggest that firms need to consider the interaction between managerial ownership and shareholder rights in designing their governance structure to minimize their cost of equity capital.
Originality/value
This paper reveals the interaction between two major governance variables in affecting firm valuation.
Details
Keywords
Youcheng Zhou, Bin Zhong, Tao Fang, Jiming Liu, Xiaonong Zhou and Shiwu Zhang
This paper aims to construct a central pattern generator (CPG) network that comprises coupled nonlinear oscillators to implement diversified locomotion gaits of robot AmphiHex-I…
Abstract
Purpose
This paper aims to construct a central pattern generator (CPG) network that comprises coupled nonlinear oscillators to implement diversified locomotion gaits of robot AmphiHex-I. With the gaits, AmphiHex-I will have a strong locomotion ability in an amphibious environment, which is motivated by a novel public health application to detect the amphibious snail, Oncomelania hupensis, the snail intermediate host of Schistosoma japonicum, as an amphibious robot-based tool for schistosomiasis surveillance and response in the future.
Design/methodology/approach
First, the basis neural network was built by adopting six Hopf nonlinear oscillators which corresponded to six legs. Then, the correlation between the self-excited harmonic output signals generated from CPGs and various gaits was established. In view of requirements on its field application, the authors added a telecontrol system and an on-board battery to support the real-life remote control and a high-definition camera and a global positioning system module to acquire images and position information. Finally, the authors conducted the testing experiments on several tasks, e.g. detecting the distribution of Oncomelania hupensis snails.
Findings
The results demonstrate that the CPG is effective in controlling the robot’s diversified locomotion gaits. In addition, the robot is capable of fulfilling several testing tasks in the experiments.
Originality/value
The research provides a method based on CPG to control a hexapod robot with multiple motion patterns, which can effectively overcome the difficulty of motion control simply by changing certain mathematical parameters of a nonlinear equation, such as frequency, phase difference and offset angle, so as to realize the gait transitions. Also, using such a robot to probe the distribution of snails offers another way to tackle this laborious job, especially in some odious terrains, which will hence broaden the application of AmphiHex-I to vector surveillance in the fields of public health.
Details
Keywords
Zhanglin Peng, Tianci Yin, Xuhui Zhu, Xiaonong Lu and Xiaoyu Li
To predict the price of battery-grade lithium carbonate accurately and provide proper guidance to investors, a method called MFTBGAM is proposed in this study. This method…
Abstract
Purpose
To predict the price of battery-grade lithium carbonate accurately and provide proper guidance to investors, a method called MFTBGAM is proposed in this study. This method integrates textual and numerical information using TCN-BiGRU–Attention.
Design/methodology/approach
The Word2Vec model is initially employed to process the gathered textual data concerning battery-grade lithium carbonate. Subsequently, a dual-channel text-numerical extraction model, integrating TCN and BiGRU, is constructed to extract textual and numerical features separately. Following this, the attention mechanism is applied to extract fusion features from the textual and numerical data. Finally, the market price prediction results for battery-grade lithium carbonate are calculated and outputted using the fully connected layer.
Findings
Experiments in this study are carried out using datasets consisting of news and investor commentary. The findings reveal that the MFTBGAM model exhibits superior performance compared to alternative models, showing its efficacy in precisely forecasting the future market price of battery-grade lithium carbonate.
Research limitations/implications
The dataset analyzed in this study spans from 2020 to 2023, and thus, the forecast results are specifically relevant to this timeframe. Altering the sample data would necessitate repetition of the experimental process, resulting in different outcomes. Furthermore, recognizing that raw data might include noise and irrelevant information, future endeavors will explore efficient data preprocessing techniques to mitigate such issues, thereby enhancing the model’s predictive capabilities in long-term forecasting tasks.
Social implications
The price prediction model serves as a valuable tool for investors in the battery-grade lithium carbonate industry, facilitating informed investment decisions. By using the results of price prediction, investors can discern opportune moments for investment. Moreover, this study utilizes two distinct types of text information – news and investor comments – as independent sources of textual data input. This approach provides investors with a more precise and comprehensive understanding of market dynamics.
Originality/value
We propose a novel price prediction method based on TCN-BiGRU Attention for “text-numerical” information fusion. We separately use two types of textual information, news and investor comments, for prediction to enhance the model's effectiveness and generalization ability. Additionally, we utilize news datasets including both titles and content to improve the accuracy of battery-grade lithium carbonate market price predictions.