Design Principles for Robust Fraud Detection: The Case of Stock Market Manipulations

2021 ◽  
Vol 22 (1) ◽  
pp. 156-178
Author(s):  
Michael Siering ◽  
◽  
Jan Muntermann ◽  
Miha Grčar ◽  
◽  
...  
Keyword(s):  
Stock Market ◽  
Fraud Detection ◽  
Design Principles

scholarly journals Stock Market Fraud Detection, A Probabilistic Approach

2020 ◽  
Vol 17 (1) ◽  
pp. 3-14
Author(s):  
Seyed Javad Kazemitabar ◽  
Majid Shahbazzadeh ◽  
◽  
Keyword(s):  
Stock Market ◽  
Probabilistic Approach ◽  
Fraud Detection

A peek in the micro-sized world: a review of design principles, engineering tools, and applications of engineered microbial community

2020 ◽  
Vol 48 (2) ◽  
pp. 399-409
Author(s):  
Baizhen Gao ◽  
Rushant Sabnis ◽  
Tommaso Costantini ◽  
Robert Jinkerson ◽  
Qing Sun
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Environmental Remediation ◽  
Real Life ◽  
Design Principles ◽  
Microbial Interactions ◽  
Potential Applications ◽  
New Gene ◽  
Global Biogeochemical Cycles ◽  
Synthetic Microbial Communities

Microbial communities drive diverse processes that impact nearly everything on this planet, from global biogeochemical cycles to human health. Harnessing the power of these microorganisms could provide solutions to many of the challenges that face society. However, naturally occurring microbial communities are not optimized for anthropogenic use. An emerging area of research is focusing on engineering synthetic microbial communities to carry out predefined functions. Microbial community engineers are applying design principles like top-down and bottom-up approaches to create synthetic microbial communities having a myriad of real-life applications in health care, disease prevention, and environmental remediation. Multiple genetic engineering tools and delivery approaches can be used to ‘knock-in' new gene functions into microbial communities. A systematic study of the microbial interactions, community assembling principles, and engineering tools are necessary for us to understand the microbial community and to better utilize them. Continued analysis and effort are required to further the current and potential applications of synthetic microbial communities.

Predicting Stock Market Performance

2020 ◽  
pp. 1-10
Author(s):  
Thomas Plieger ◽  
Thomas Grünhage ◽  
Éilish Duke ◽  
Martin Reuter
Keyword(s):  
Stock Market ◽  
Risk Taking ◽  
Life Stress ◽  
Price Volatility ◽  
Individual Characteristics ◽  
Self Report ◽  
Financial Behavior ◽  
Market Simulation ◽  
Stock Market Performance ◽  
Risk Taking Behavior

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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