Variance
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Variance is a peer-reviewed, open-access journal published by the Casualty Actuarial Society to disseminate original practical and theoretical research in casualty actuarial science. Variance aims to be a valuable and practical tool for new actuaries starting out as well as for more experienced actuaries looking to expand their skills. Topics will be relevant to P&C actuarial work, including..
Variance
5d ago
This paper introduces matrix variate regression for modeling three-way data responses and uses losses from natural hazards across space and time as an application example ..read more
Variance
5d ago
Based on the distances between structures on the same farm, we propose a new pricing approach that considers fire propagation ..read more
Variance
1w ago
Our paper introduces a sparse deep learning method to enhance the frequency-severity modeling. It allows for frequency-severity dependence and variable selection simultaneously in neural net based predictive models ..read more
Variance
2w ago
This paper describes how to apply fuzzy set theory to actuarial credibility problems when the information about the loss model or its parameters is imprecise or vague ..read more
Variance
1M ago
This paper proposes a modified Wiener process model with statistical test procedures to compare the risks of complex cyber networks in the cybersecurity insurance domain ..read more
Variance
3M ago
This letter responds to the inappropriate assessment published in Variance Vol. 14, Issue 1, 2021 ..read more
Variance
3M ago
We discuss the order statistics for frequency and severity models applied in reinsurance applications, also the sensitivity of the order statistic exceedance probabilities using examples with implications for pricing metrics ..read more
Variance
3M ago
We introduce a shared random effects model to capture unobserved heterogeneity in risks and induce a natural dependence structure among the multiple perils, which leads to multi-peril credibility premium formula ..read more
Variance
5M ago
This paper illustrates how variance reduction methods, such as importance sampling, conditioning and stratified sampling, and their combinations, can be applied to effectively simulate compound distributions ..read more
Variance
7M ago
We should adopt key ideas from Principal-Agent Theory into our foundations of insurance risk, resulting in a more expansive and more realistic framework for understanding insurance risk ..read more