The dynamic interaction between investor attention and green security market: an empirical study based on Baidu index

PurposeThis paper aims to explore the interaction between investor attention and green security markets, including green bonds and stocks.Design/methodology/approachThis study takes the Baidu index of “green finance” as the proxy for investor attention and constructs several generalized prediction error variance decomposition models to investigate the interdependence. It further analyzes the dynamic interaction between investor attention and the return and volatility of green security markets using the rolling time window.FindingsThe empirical analysis and robustness test results reveal that the spillovers between investor attention and the return and volatility of the green bond market are relatively stable. In contrast, the spillover level between investor attention and the green stock market displays significant time-varying and asymmetric effects. Moreover, the volatility spillover between investor attention and green securities is vulnerable to major financial events, while the return spillover is extremely sensitive to market performance.Originality/valueThe conclusion further expands the practical application and theoretical framework of behavioral finance in green finance and provides a new reference for investors and regulators. Besides, this study also lays a theoretical basis for investors to focus on the practical application of volatility prediction and risk management in green securities.

COMPETITIVE DEVELOPMENT OF AGRICULTURAL AND ENTERPRISES OF THE REGION IN THE CONDITIONS OF TRANSFORMATION OF THEIR INDUSTRIAL STRUCTURE

In the process of balanced development of agriculture a particularly important role belongs to the optimization or correction of the sectoral structure, which allows the most effective use of available production and resource potential and ensure food security and independence of the state in competition in domestic and foreign agri-food markets. Keywords: agriculture, food security, markets, optimization, sectoral structure.

Sociology of Fear of Crime in Latin America

Independently of the varying national homicide indexes, the fear of crime affects all socio-political dimensions across Latin American countries and influences the agendas of political parties, security markets, and everyday life. This contribution presents an overview on the fear of crime and insecurity studies in the region, focusing on two main fields: fear of crime studies showcasing similarities and differences among Latin American countries in terms of the relationship between fear and victimization, gender, class, age, and community cohesion perceptions, and the socio-cultural dimension to this phenomenon, including media influences on the fear of delinquency, the role of the state, and the general climate of ontological insecurity.

THE IMBALANCES AND DISPRPORTIONS OF THE WORLD AND DOMESTIC SECURITY MARKETS

The modern structure of the world security market and peculiarities of domestic market development are investigated. The stock market imbalance was identified and clearly demonstrated. Imbalances in the development of securities markets in different regions of the world are manifested, both in market capitalization and in transaction volumes, in the nature of transactions, in the variety of financial instruments, etc. The assessment of the structure of the world market made it possible to identify regional peculiarities of the stock markets. Current trends in the development of leading stock exchanges are analyzed. There is a tendency to increase operations with financial derivatives and increase the value of international transactions The dynamics and structure of the Ukrainian stock market have been analyzed and a number of its features have been identified: insignificant volumes of securities transactions, predominance of government debt securities in the market structure, insignificant use of derivatives both for hedging and for speculative purposes. The problem of exit and stay of Ukrainian issuers and traders on international stock exchanges is investigated. It is a complicated listing process, requires significant investment and high standards. The signs of disproportionality and imbalance of world and domestic stock markets, which have different origin and causes, are revealed.

Identification of Insider Trading Using Extreme Gradient Boosting and Multi-Objective Optimization

Illegal insider trading identification presents a challenging task that attracts great interest from researchers due to the serious harm of insider trading activities to the investors’ confidence and the sustainable development of security markets. In this study, we proposed an identification approach which integrates XGboost (eXtreme Gradient Boosting) and NSGA-II (Non-dominated Sorting Genetic Algorithm II) for insider trading regulation. First, the insider trading cases that occurred in the Chinese security market were automatically derived, and their relevant indicators were calculated and obtained. Then, the proposed method trained the XGboost model and it employed the NSGA-II for optimizing the parameters of XGboost by using multiple objective functions. Finally, the testing samples were identified using the XGboost with optimized parameters. Its performances were empirically measured by both identification accuracy and efficiency over multiple time window lengths. Results of experiments showed that the proposed approach successfully achieved the best accuracy under the time window length of 90-days, demonstrating that relevant features calculated within the 90-days time window length could be extremely beneficial for insider trading regulation. Additionally, the proposed approach outperformed all benchmark methods in terms of both identification accuracy and efficiency, indicating that it could be used as an alternative approach for insider trading regulation in the Chinese security market. The proposed approach and results in this research is of great significance for market regulators to improve their supervision efficiency and accuracy on illegal insider trading identification.

The Three-factor Model and China’s Multiple Stock Markets

This paper aims at discussing the applicability of the three-factor model in China’s multiple security markets. The monthly returns of Shenzhen Main Board Market, Shanghai Stock Market, GEM Securities Market and Small and Medium Board Securities Market from January 2012 to December 2016 are selected as samples. The following conclusions are drawn: the three-factor model is applicable in Shenzhen Main Board Market, that is, the change of stock return is proportional to market factor, book-to-market ratio factor, and inversely proportional to scale factor. Moreover, in terms of the explanatory power of the change of stock return, the market factor is the highest, the scale factor is the second, and the book-to-market ratio factor is the lowest. But in the other three markets, the two-factors model that excludes the ratio of book market value can explain the change of stock return better. In addition, the explanatory power of market factor is better than scale factor.