Stock Market Outlook: No Metamorphosis

1977 ◽  
Vol 33 (5) ◽  
pp. 25-28
Author(s):  
Arthur Zeikel
Keyword(s):  
1951 ◽  
Vol 7 (2) ◽  
pp. 49-59
Author(s):  
Richard W. Lambourne
Keyword(s):  

1998 ◽  
Vol 24 (2) ◽  
pp. 11-26 ◽  
Author(s):  
John Y. Campbell ◽  
Robert J. Shiller

1960 ◽  
Vol 16 (3) ◽  
pp. 65-66
Author(s):  
Edmund W. Tabell
Keyword(s):  

2021 ◽  
Vol 13 ◽  
pp. 419-426
Author(s):  
Zhiqiang Li

On the day of the outbreak, the Covid epidemic brought huge systemic risks in China stock market, which even offset the positive effects brought about by the epidemic. For example, industries such as medicine did not show the expected general rise on the day of the epidemic. After the outbreak, with the rapid intervention of the government, investor confidence regained and they had high hopes for the market outlook. The market rebounded quickly and returned to the pre-epidemic level in less than 10 days. However, the performance of various industries in this process is different. This paper examines the impact of Covid epidemic on various industries in China based on the event analysis method.


Author(s):  
Thomas Plieger ◽  
Thomas Grünhage ◽  
Éilish Duke ◽  
Martin Reuter

Abstract. Gender and personality traits influence risk proneness in the context of financial decisions. However, most studies on this topic have relied on either self-report data or on artificial measures of financial risk-taking behavior. Our study aimed to identify relevant trading behaviors and personal characteristics related to trading success. N = 108 Caucasians took part in a three-week stock market simulation paradigm, in which they traded shares of eight fictional companies that differed in issue price, volatility, and outcome. Participants also completed questionnaires measuring personality, risk-taking behavior, and life stress. Our model showed that being male and scoring high on self-directedness led to more risky financial behavior, which in turn positively predicted success in the stock market simulation. The total model explained 39% of the variance in trading success, indicating a role for other factors in influencing trading behavior. Future studies should try to enrich our model to get a more accurate impression of the associations between individual characteristics and financially successful behavior in context of stock trading.


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