Deep neural networks(DNNs)are effective in solving both forward and inverse problems for nonlinear partial differential equations(PDEs).However,conventional DNNs are not effective in handling problems such as delay di...Deep neural networks(DNNs)are effective in solving both forward and inverse problems for nonlinear partial differential equations(PDEs).However,conventional DNNs are not effective in handling problems such as delay differential equations(DDEs)and delay integrodifferential equations(DIDEs)with constant delays,primarily due to their low regularity at delayinduced breaking points.In this paper,a DNN method that combines multi-task learning(MTL)which is proposed to solve both the forward and inverse problems of DIDEs.The core idea of this approach is to divide the original equation into multiple tasks based on the delay,using auxiliary outputs to represent the integral terms,followed by the use of MTL to seamlessly incorporate the properties at the breaking points into the loss function.Furthermore,given the increased training dificulty associated with multiple tasks and outputs,we employ a sequential training scheme to reduce training complexity and provide reference solutions for subsequent tasks.This approach significantly enhances the approximation accuracy of solving DIDEs with DNNs,as demonstrated by comparisons with traditional DNN methods.We validate the effectiveness of this method through several numerical experiments,test various parameter sharing structures in MTL and compare the testing results of these structures.Finally,this method is implemented to solve the inverse problem of nonlinear DIDE and the results show that the unknown parameters of DIDE can be discovered with sparse or noisy data.展开更多
Internet companies usually have to rely on financing to grow, which puts their founders at risk of losing control. In this situation, the dual ownership structure arises at the historic moment and becomes a powerful w...Internet companies usually have to rely on financing to grow, which puts their founders at risk of losing control. In this situation, the dual ownership structure arises at the historic moment and becomes a powerful weapon for the founders to control. In order to maintain the right of control, most enterprises have chosen the typical structure of the dual ownership system-AB share system, and Alibaba Group has established an upgraded version of the dual ownership structure-partner system in view of its own development characteristics. This paper uses the method of case study, taking Alibaba Group as an example, from the perspective of control rights protection to study the Alibaba partnership system in depth. On the basis of combing and analyzing the protection mechanism of Alibaba's control rights, this paper further compares the AB share system with the partner system, sums up the advantages and limitations of the partner system, and puts forward some relevant solutions. This paper will provide some reference for the research on the dual ownership structure of Chinese Internet companies.展开更多
In a changing transition economy, Chinese government regulations that adopt the relatively simple bright line rule formula are enforceable in practice. Taking the early reform-oriented policies of the China Securities...In a changing transition economy, Chinese government regulations that adopt the relatively simple bright line rule formula are enforceable in practice. Taking the early reform-oriented policies of the China Securities Regulatory Commission(CSRC) as an example, we find that the CSRC did not consider local enthusiasm for reform when allocating IPO resources because of the high enforcement costs involved. We also find that CSRC listed company regulations were enforced due to the lower costs involved in verifying regulatory violations, and that listed companies that completed the reform process were given priority in public refinancing. We present empirical evidence supporting the theoretical basis for the hypotheses outlined above. We also conclude that companies that completed the reform process in 2005 were of significantly higher quality and that the SEO regulation did not affect stock market efficiency. These findings enhance our understanding of the efficiency of government regulation in a transition economy.展开更多
While the relationship between state ownership and firm performance has been widely researched, the empirical evidence has provided mixed results. This study applies panel data regression techniques to 10,639 firm-yea...While the relationship between state ownership and firm performance has been widely researched, the empirical evidence has provided mixed results. This study applies panel data regression techniques to 10,639 firm-year observations of nonfinancial Chinese listed firms during 2003–2010 to examine the relationship between state ownership and firm performance. The results show that state ownership has a U-shaped relationship with firm performance. The Split Share Structure Reform in2005–2006 played a positive role in enhancing the relationship between state ownership and firm profitability ratios. Although state ownership decreased significantly after 2006, it remains high in strategically important industry sectors such as the oil, natural gas and mining sector and the publishing, broadcasting and media sector. The findings reveal that a higher level of state ownership is superior to a dispersed ownership structure due to the benefits of government support and political connections. The Split Share Structure Reform made previously nontradable shares legally tradable, improving corporate governance and reducing the negative effect of non-tradable state shares.展开更多
文摘Deep neural networks(DNNs)are effective in solving both forward and inverse problems for nonlinear partial differential equations(PDEs).However,conventional DNNs are not effective in handling problems such as delay differential equations(DDEs)and delay integrodifferential equations(DIDEs)with constant delays,primarily due to their low regularity at delayinduced breaking points.In this paper,a DNN method that combines multi-task learning(MTL)which is proposed to solve both the forward and inverse problems of DIDEs.The core idea of this approach is to divide the original equation into multiple tasks based on the delay,using auxiliary outputs to represent the integral terms,followed by the use of MTL to seamlessly incorporate the properties at the breaking points into the loss function.Furthermore,given the increased training dificulty associated with multiple tasks and outputs,we employ a sequential training scheme to reduce training complexity and provide reference solutions for subsequent tasks.This approach significantly enhances the approximation accuracy of solving DIDEs with DNNs,as demonstrated by comparisons with traditional DNN methods.We validate the effectiveness of this method through several numerical experiments,test various parameter sharing structures in MTL and compare the testing results of these structures.Finally,this method is implemented to solve the inverse problem of nonlinear DIDE and the results show that the unknown parameters of DIDE can be discovered with sparse or noisy data.
文摘Internet companies usually have to rely on financing to grow, which puts their founders at risk of losing control. In this situation, the dual ownership structure arises at the historic moment and becomes a powerful weapon for the founders to control. In order to maintain the right of control, most enterprises have chosen the typical structure of the dual ownership system-AB share system, and Alibaba Group has established an upgraded version of the dual ownership structure-partner system in view of its own development characteristics. This paper uses the method of case study, taking Alibaba Group as an example, from the perspective of control rights protection to study the Alibaba partnership system in depth. On the basis of combing and analyzing the protection mechanism of Alibaba's control rights, this paper further compares the AB share system with the partner system, sums up the advantages and limitations of the partner system, and puts forward some relevant solutions. This paper will provide some reference for the research on the dual ownership structure of Chinese Internet companies.
基金supported by the National Natural Science Fund (grant no. 70602011)the National Social Science Fund (grant no. 08CJY009)+2 种基金the support we have received from the IAPHD Project of Nanjing Universitythe Institution of Accounting and Finance of Shanghai University of Finance and EconomicsResearch Project 985 of the Institution of Economic Transition and Development of Nanjing University
文摘In a changing transition economy, Chinese government regulations that adopt the relatively simple bright line rule formula are enforceable in practice. Taking the early reform-oriented policies of the China Securities Regulatory Commission(CSRC) as an example, we find that the CSRC did not consider local enthusiasm for reform when allocating IPO resources because of the high enforcement costs involved. We also find that CSRC listed company regulations were enforced due to the lower costs involved in verifying regulatory violations, and that listed companies that completed the reform process were given priority in public refinancing. We present empirical evidence supporting the theoretical basis for the hypotheses outlined above. We also conclude that companies that completed the reform process in 2005 were of significantly higher quality and that the SEO regulation did not affect stock market efficiency. These findings enhance our understanding of the efficiency of government regulation in a transition economy.
文摘While the relationship between state ownership and firm performance has been widely researched, the empirical evidence has provided mixed results. This study applies panel data regression techniques to 10,639 firm-year observations of nonfinancial Chinese listed firms during 2003–2010 to examine the relationship between state ownership and firm performance. The results show that state ownership has a U-shaped relationship with firm performance. The Split Share Structure Reform in2005–2006 played a positive role in enhancing the relationship between state ownership and firm profitability ratios. Although state ownership decreased significantly after 2006, it remains high in strategically important industry sectors such as the oil, natural gas and mining sector and the publishing, broadcasting and media sector. The findings reveal that a higher level of state ownership is superior to a dispersed ownership structure due to the benefits of government support and political connections. The Split Share Structure Reform made previously nontradable shares legally tradable, improving corporate governance and reducing the negative effect of non-tradable state shares.
