Numerical study of the stock market crises based on mean field games approach

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Nikolai V. Trusov

Abstract We present an approach to describe the stock market crises based on Mean Field Games (MFGs) and Optimal Control theory with a turnpike effect. The impact of the large amount of high-frequency traders (HFTs) can be modeled via a mean field term. We introduce the turnpike as a function that relies on the changes of the asset share price. An MFG is a coupled system of PDEs: a Kolmogorov–Fokker–Planck equation, evolving forward in time, and a Hamilton–Jacobi–Bellman equation, evolving backwards in time. The ill-posedness of this system comes from a turnpike effect. The numerical solution of an extremal problem that is dual to a PDE system is presented. We apply this approach to describe the Chinese stock market crash in 2015 considering the representative stock of CITIC Securities (ticker 600030). We consider HFTs that form a dominating bull and bear market. As a result, the bull strategy imitators do not make any profit.

2021 ◽  
Vol 16 (3) ◽  
pp. 495-520
Author(s):  
Lin Guo ◽  
◽  
Xufei Zhang ◽  
Songlei Chao ◽  
◽  
...  

The outbreak of the COVID-19 epidemic has had an adverse effect on China's economy. This paper uses the event study method to test and measure the impact of the open market reverse repo (OMRR) operation on the Chinese stock market. The results show that the OMRR operation generates a positive daily abnormal return and a positive daily cumulative abnormal return on average for all stocks. The impact is larger for non-state-owned enterprise (non-SOE) firms than for SOE firms, stocks of non-Hubei provinces than those of the Hubei province, and for stocks of the information transmission and technology industry than those of other industries. We suggest that our government implement more prudent monetary policies and more proactive fiscal policies.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xianbo Wu ◽  
Xiaofeng Hui

By calculating the mutual information of stock indexes of 10 primary industry sectors in China, this paper analyzes the dependence relationship among Chinese stock sectors during the COVID-19 and the dynamic evolution of the relationship by using the sliding window method. According to the actual situation of the development of COVID-19 in China, the samples were divided into three stages, namely, calm period, pandemic period, and post-pandemic period. The results show that the dependence relationship among Chinese stock sectors is significantly enhanced in the pandemic period, but it decreases in the post-pandemic period and the dependence structure is similar to that in the calm period. The industrials sector is most closely connected with other sectors in the pandemic period. The information technology sector and telecommunication services sector maintain strong dependence in the three periods and share little contact with other sectors. In the pandemic period, the dependence between the consumer staples sector and other sectors is significantly enhanced, and consumer staples sector and health care sector maintain a strong dependence. From the results of the sliding window, the Chinese stock market is sensitive to the impact of COVID-19, but the duration of the impact on the dependence among the stock sectors is not long.


2018 ◽  
Vol 10 (8) ◽  
pp. 77
Author(s):  
Ning Wu

With the continuous development of global economic integration and financial markets, international capital flows more and more frequently, the frequent flow of international capital will inevitably affect the yield of Chinese stock market. This article uses short-term international capital inflows SS and Shanghai composite index R as research objects. Based on monthly data from January 2002 to October 2017, VAR model was constructed using Eviews8.0 to study the impact of short-term international capital flows on Chinese stock market. Empirical studies have found that short-term international capital flow is the granger cause of changes in the Shanghai composite index yield, while the yield of Chinese stock market will not affect short-term international capital flows. At the end of this paper, relevant suggestions are put forward according to the conclusions.


2017 ◽  
Vol 43 (5) ◽  
pp. 545-566 ◽  
Author(s):  
Muhammad Zubair Tauni ◽  
Zia-ur-Rehman Rao ◽  
Hong-Xing Fang ◽  
Minghao Gao

Purpose The purpose of this paper is to investigate the impact of the key sources of information, namely, financial advice, word-of-mouth communication and specialized press, on trading behavior of Chinese stock investors. The study also analyzed if the association between the key sources of information and trading behavior is influenced by investor personality. Design/methodology/approach The authors adopted the Big Five personality framework and examined the survey results of individual stock investors (n=541) in China. Personality traits of investors were measured by the NEO-Five Factor Inventory (Costa and McCrae, 1989). The authors performed probit regression analysis to evaluate the moderating influence of investor personality traits on the association between sources of information and stock trading behavior. Findings The results of the study confirm the previous findings that the key sources of information used by investors as a foundation of their financial choices have a significant influence on their trading behavior. The study also provides empirical evidence that investor personality traits moderate the relationship between the key sources of information and trading behavior. Financial advisors tend to increase the frequency of trading in investors with openness, extraversion, neuroticism and agreeableness personality traits, and tend to decrease the intensity of trading in investors with conscientiousness trait. On the other hand, financial information acquired from word-of-mouth communication is more likely to enhance trading frequency in extraverted and agreeable investors, and is more likely to reduce trading frequency in investors with openness, conscientiousness and neuroticism traits. Finally, the use of specialized press leads to more adjustment in portfolios of the investors with openness and conscientiousness traits than those with other personality traits. An alternative mediated model was not supported. Originality/value This research contributes to information search literature and behavioral finance literature and provides empirical evidence that the psychological characteristics of investors are significant predictors of the variations in information-trading link. The study offers new theoretical insights of investors’ behavior due to the characteristics of Chinese stock market which are unique from other stock markets in the world. To the authors’ best knowledge, no previous study has been conducted so far in Chinese stock market to explore variations with regards to the impact of the key sources of information on trading behavior by the Big Five investor personality and this paper seeks to fill this gap.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Youngbum Kwon ◽  
T. Bettina Cornwell

PurposeGiven the public availability of secondary data on investments in events such as the Olympics, FIFA World Cup and professional sports, event studies that measure stock market response to these investments have grown. Previous findings are mixed, however, with some studies suggesting that the announcement of sponsorship contracts is a positive event and others finding detrimental effects of the announcement on shareholder value. This study aims to analyze the mixed findings from event studies in sport sponsorship to determine if sponsorship announcements influence stock market response.Design/methodology/approachThe meta-analysis examines more than 20 years of research on event studies in sponsorship (34 studies).FindingsThe overall results show a positive, but non-significant effect of partnership deal announcements on shareholder wealth. Further analysis considers the effects of sponsorship announcements by each type of event window to see the impact of the announcement relative to time (pre-announcement, announcement day, post-announcement and pre- to post-announcement). This closer examination of the event window shows that stock prices of sponsoring organizations increased in the pre-announcement window.Originality/valueQuantitative meta-analytic findings indicate that information about sponsorship deals appears to leak to share markets and positively influence share price. This finding suggests that sponsoring the sports and events found in these event studies is seen as value enhancing for sponsoring firms.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Binghui Wu ◽  
Yuanman Cai ◽  
Mengjiao Zhang

This paper uses the partial least squares method to construct the investor sentiment index in Chinese stock market. The Shanghai Stock Exchange 180 Index and the Shenzhen Stock Exchange 100 Index are used as samples. From the perspectives of holistic sentiment and heterogeneous sentiment, this paper studies the impact of investor sentiment on stock price crash risk. The results show that investor sentiment can significantly affect stock price crash risk in Shanghai and Shenzhen A-share markets, especially in the Shenzhen A-share market no matter from which perspective. And investor pessimism has a greater impact on stock price crash risk in the Shenzhen A-share market from the perspective of heterogeneous sentiment. Compared with the available researches, this paper makes two contributions: (i) the comparative analysis is adopted to discuss the differences between Shanghai and Shenzhen A-share markets, abandoning the research approach that takes the two markets as a whole in existing literature, and (ii) this paper not only studies the impact of investor holistic sentiment on stock price crash risk from a macro perspective, but also adds a more micro heterogeneous sentiment and conducts a comparative analysis.


2019 ◽  
Vol 5 (2) ◽  
pp. 34 ◽  
Author(s):  
Cordelia Onyinyechi Omodero ◽  
Sunday Mlanga

Stock market is an essential part of a nation’s economy and requires adequate evaluation of all factors that militate against its performance. This study investigates the role of macroeconomic variables in determining the stock market performance in Nigeria using annual time series data covering a period from 2009 to 2018. These data have been sourced from the World Bank Development Indicators, International Monetary Fund and CBN Statistical Bulletin. The results from the regression analysis indicate that exchange rate and interest rate do not have significant impact on share price index while inflation rate exerts a significant negative influence on share price index. On the contrary and in line with the concept of GDP and stock market performance, GDP significantly and positively impacts on share price index. The study among others suggests that the growth of the economy should be maintained to keep stock market flourishing while macroeconomic variables such as inflation, interest rate and exchange rate should be appropriately regulated by the relevant authorities to curtail all negative influences on stock market performance.


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