An Insurance Market Simulation With Both Adverse and Advantageous Selection

2017 ◽  
Vol 20 (1) ◽  
pp. 133-146
Author(s):  
Leon Chen ◽  
Puneet Jaiprakash
Keyword(s):  
Insurance Market ◽  
Advantageous Selection ◽  
Market Simulation

scholarly journals Sources of Advantageous Selection: Evidence from the Medigap Insurance Market

2008 ◽  
Vol 116 (2) ◽  
pp. 303-350 ◽  
Author(s):  
Hanming Fang ◽  
Michael P. Keane ◽  
Dan Silverman
Keyword(s):  
Insurance Market ◽  
Advantageous Selection

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.

Prediction of Technical Reserves Based on Grey Model — GM(1,1): Evidence from Non-life Egyptian Insurance Market

2019 ◽  
Vol 10 (9) ◽  
pp. 852-860
Author(s):  
Mahmoud Elsayed ◽  
◽  
Amr Soliman ◽  
Keyword(s):  
System Theory ◽  
Grey System Theory ◽  
Insurance Market ◽  
Grey Model ◽  
Loss Ratio ◽  
Grey System ◽  
Mathematical Technique ◽  
Supervisory Authority ◽  
Error Ratio ◽  
Using Data

Grey system theory is a mathematical technique used to predict data with known and unknown characteristics. The aim of our research is to forecast the future amount of technical reserves (outstanding claims reserve, loss ratio fluctuations reserve and unearned premiums reserve) up to 2029/2030. This study applies the Grey Model GM(1,1) using data obtained from the Egyptian Financial Supervisory Authority (EFSA) over the period from 2005/2006 to 2015/2016 for non-life Egyptian insurance market. We found that the predicted amounts of outstanding claims reserve and loss ratio fluctuations reserve are highly significant than the unearned premiums reserve according to the value of Posterior Error Ratio (PER).

State Approaches to Premium Rate Reforms in the Individual Health Insurance Market

2014 ◽  
Author(s):  
Sabrina Corlette Corlette ◽  
Kevin W. Lucia Lucia ◽  
Justin Giovannelli Giovannelli
Keyword(s):  
Health Insurance ◽  
Insurance Market ◽  
Premium Rate ◽  
Individual Health ◽  
Health Insurance Market ◽  
The Individual
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