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The purpose of this paper is to empirically analyze the dynamic relationship between stock market and bond market based on the effect of different information shocks.

This paper decomposes the information of stock market and bond market into public information and private information. The characteristics of response of stock market and bond market to the information shocks are examined by SVAR model and modified BEKK model.

The study shows that the information shocks in financial market yield not only the effect on linear asset return but also the effect on nonlinear asset volatility. The public information mainly produces a short effect of return while the private information mainly produces a permanent effect on volume. The interactive relation between stock market and bond market is mainly reliant on the effect of the information shock volatility to market return volatility.

The paper empirically analyzes the influence characteristics of different information shocks, which has some reference value not only for deeply understanding the market microstructure but also for improving the construction of various capital markets.

With the launch of CSI 300 Index Futures trading on April 16, 2010, China's stock market presents a more diversified trend, such as arbitrage, trends strategy entering the market rapidly. Therefore, the liquidity demand also presents a higher frequency, and the change is more complex than the original situation. In recent years, many literatures are engaged in high-frequency trading (HFT) related research, and an important concern is the impact of HFT on market volatility and liquidity. Is it playing the role of stabilizing the market, or bringing more noise and turmoil? Based on this, the purpose of this study is trying to study what kind of impact the HFT have on market liquidity before and after the launch of the CSI 300 Index Futures.

The paper uses the simultaneous equations model of price and net order flow proposed by Deuskar and Johnson and for the first time introduces an asymmetric identification through heteroskedasticity (ITH) method. The paper applies the method to the high-frequency data of CSI 300 Index and the Futures and classifies the buying and selling orders through volume clock. The price risks are decomposed into a component driven by the impact of liquidity demand shocks (flow-driven risks (FDRs)) and a component driven by external information (information-driven risks (IDRs)).

The empirical results show that the flow-driven risk of CSI 300 Index Futures is about 20 percent. In addition, before the introduction of the Index Futures, there is no asymmetric effect between liquidity demand shocks and price shocks existing in either CSI 300 Index or CSI 300 Index Futures. While after the introduction of stock Index Futures, the asymmetric effect in the both two markets emerges. The impact of the buying net order flows on the price is less than the impact of the selling net order flows on CSI 300 Index, whereas the impact of the buying net order flows on the price is larger than the impact of the selling net order flows on CSI 300 Index Futures. The paper further analyzes the relationship between liquidity and FDR and gets the conclusion that the reasons for the deterioration of the liquidity level are caused by the impact of the external information shocks, rather than the liquidity demand shocks. And entries of HFTs like arbitrage traders and hedge traders play a positive role in improving the liquidity level in the market.

The paper introduces an asymmetric ITH method for the first time and finds asymmetric effect of the net order flow on the return in both CSI 300 Index market and the corresponding Index Futures market.

Does the history of the bureaucratic system, along with the establishment of the Great Wall during the Ming and Qing dynasties (1368–1911), affect firm behavior across the borderlands of the Great Wall?

The Ming and Qing dynasties built a centralized administrative system in the borderlands on the south side of the Great Wall, in contrast to the “feudal lordship” system on the north side. Employing a regression discontinuity analysis framework with the Great Wall as a geographical discontinuity, we examine the long-run effects of the Great Wall on firms’ earnings management.

Using a large sample of nonlisted firms in the central core frontier region, we show that the earnings management of firms in the region south of the Great Wall is significantly curtailed compared with firms in the north of it, and this effect is more pronounced for non-SOEs. Our findings are robust to a battery of tests to account for alternative explanations.

Overall, by emphasizing the role of institutions, like legal system, shaped in history on firms’ earnings management, this study sheds new light on institutional determinants of firms’ behaviors in earnings information disclosure.

First, we enrich our understanding of the institutional determinants of firms’ financial reporting outcomes. Second, our findings shed new light on the long-term effects of historical ruling styles on modern corporate behavior.

This study aims to explore the evolving field of physics-informed neural networks (PINNs) through an analysis of 996 records retrieved from the Web of Science (WoS) database from 2019 to 2022.

WoS database was analyzed for PINNs using an inhouse python code. The author’s collaborations, most contributing institutes, countries and journals were identified. The trends and application categories were also analyzed.

The papers were classified into seven key domains: Fluid Dynamics and computational fluid dynamics (CFD); Mechanics and Material Science; Electromagnetism and Wave Propagation; Biomedical Engineering and Biophysics; Quantum Mechanics and Physics; Renewable Energy and Power Systems; and Astrophysics and Cosmology. Fluid Dynamics and CFD emerged as the primary focus, accounting for 69.3% of total publications and witnessing exponential growth from 22 papers in 2019 to 366 in 2022. Mechanics and Material Science followed, with an impressive growth trajectory from 3 to 65 papers within the same period. The study also underscored the rising interest in PINNs across diverse fields such as Biomedical Engineering and Biophysics, and Renewable Energy and Power Systems. Furthermore, the focus of the most active countries within each application category was examined, revealing, for instance, the USA’s significant contribution to Fluid Dynamics and CFD with 319 papers and to Mechanics and Material Science with 66 papers.

This analysis illuminates the rapidly expanding role of PINNs in tackling complex scientific problems and highlights its potential for future research across diverse domains.

In the current literature, there is little systematic research on the relationship among adjustment of the income distribution, change in economic structure and improvement of macroeconomic efficiency.

This paper expands Marx's reproduction schema into the “Marx–Sraffa” three-department structure table comprising fixed capital, general means of production and means of consumption and employs China's input–output table from 1987 to 2015 to portray the relationship between income distribution and macroeconomic efficiency under investment-driven growth.

This paper calculates the wage–profit curve of China's economy and evaluates the space of macroeconomic efficiency improvement in China based on the deviation between actual and potential income distribution structure.

The results show that there is a downward trend of the profit rate, which meets Marx's theoretical prediction, and the decline in the profit rate is mainly attributed to an increase in the organic composition of capital arising from the rapid growth of fixed capital investment under extended growth. The analysis of macroeconomic efficiency shows that the space for improving macroeconomic efficiency is extremely limited under traditional growth pattern and that China must transform its economic development pattern and foster new economic growth drivers.