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Abstract
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This paper introduces a new extension of exponentiated standard logistic distribution. Some important statistical properties of the novel family of distributions are discussed.
A simulation study is also conducted to observe the behavior of the estimated parameter
using several estimation methods. The adaptability as well as the flexibility of the new
model is checked through two real-life applications. A comprehensive financial risk assessment is conducted using multiple actuarial risk measures: Peaks Over Random Threshold
Value-at-Risk, Value-at-Risk, Tail Value-at-Risk, the risk-adjusted return on capital and
the Mean of Order P. These indicators offer a nuanced view of risk by capturing different
aspects of tail behavior, which are critical in understanding potential extreme losses. These
risk indicators are applied to analyze actuarial financial claims data, providing a robust
framework for assessing financial stability and decision-making in the face of uncertainty
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