Results 51 to 60 of about 5,176 (265)

Causal analysis of extreme risk in a network of industry portfolios

Canadian Journal of Statistics, EarlyView.
Abstract We provide a detailed review of causal dependence within the framework of max‐linear structural models. Such models express each node variable as a max‐linear function of its parental node variables in a directed acyclic graph (DAG) and some exogenous innovation.
Claudia Klüppelberg, Mario Krali
wiley   +1 more source

A goodness‐of‐fit test for regression models with discrete outcomes

Canadian Journal of Statistics, EarlyView.
Abstract Regression models are often used to analyze discrete outcomes, but classical goodness‐of‐fit tests such as those based on the deviance or Pearson's statistic can be misleading or have little power in this context. To address this issue, we propose a new test, inspired by the work of Czado et al.
Lu Yang, Christian Genest, Johanna G. Nešlehová   +2 more
wiley   +1 more source

Risk Measures Associated With Automobile Insurance Claim Losses With an Underlying Probabilistic Mixture Distribution

International Journal of Mathematics and Mathematical Sciences
Loss data may often exhibit features such as multimodality and skewness that render single distributions incapable of capturing all these features. Insurance data often comprise of extremely large losses, of which single distributions may inadequately ...
Williams Kumi, Henry Otoo, Charles Kwofie, Sampson Takyi Appiah   +3 more
doaj   +1 more source

Optimal Market Share in Automobile Insurance Auction Markets

Mathematics
The automobile insurance industry plays a pivotal role in the financial system, fostering economic stability through effective risk management and consumer confidence.
Manuel Rodriguez, Rolando Rubilar-Torrealba, Cristóbal Fernandez-Robin, Diego Yáñez, Bernardo Pincheira   +4 more
doaj   +1 more source

An empirical study for ranking insurance firms using a hybrid of data envelopment analysis and neural network [PDF]

Management Science Letters, 2012
One of the primary concerns with data envelopment analysis arises when the number of inputs and outputs increases. In such a case, required computations will become time consuming and there is a concern on developing some hybrid methods to increase the ...
Ahmad Makui, M. Emrani Noushabadi
doaj  

Market Perceptions of ESG Reputational Risk in the US Pharmaceutical Industry

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Negative ESG‐related reputational events generate significant corporate risks, particularly within sensitive sectors such as the pharmaceutical industry. Using novel reputational data, this research investigates investor perceptions of the consequences of experienced ESG breaches among US pharmaceutical firms.
Erdinc Akyildirim, Shaen Corbet, Jose Antonio Muñiz, Frank Scrimgeour   +3 more
wiley   +1 more source

Landscape of Research on Accounting Scope 3 Emissions: A Review of Methodologies and Data

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Scope 3 emissions have been proposed as a critical metric for evaluating corporate carbon footprint, identifying emission sources, and developing mitigation solutions. Yet, widespread corporate reporting of Scope 3 emissions remains limited, highlighting a critical gap in both research and practice.
Zeyu Wang, Klaus Hubacek, Xin Sun, Franco Ruzzenenti   +3 more
wiley   +1 more source

Association Rules for Understanding Policyholder Lapses

Risks, 2018
For automobile insurance, it has long been implied that when a policyholder made at least one claim in the prior year, the subsequent premium is likely to increase.
Himchan Jeong, Guojun Gan, Emiliano A. Valdez   +2 more
doaj   +1 more source

Factors influencing the use of health services by trauma patients according to insurance type and injury severity score in South Korea: Based on Andersen's behavioral model.

PLoS ONE, 2020
This study aims to understand the difference in trauma patients' use of health services in Korea according to insurance type and the Injury Severity Score.
Hyunju Kim, Younkyoung Kim
doaj   +1 more source

Big Data and Actuarial Science

Big Data and Cognitive Computing, 2020
This article investigates the impact of big data on the actuarial sector. The growing fields of applications of data analytics and data mining raise the ability for insurance companies to conduct more accurate policy pricing by incorporating a broader ...
Hossein Hassani, Stephan Unger, Christina Beneki   +2 more
doaj   +1 more source