. However, the methodologies of any risk analysis must first adapt to the dynamics of the IoT system. This article seeks to shed …The increasing rate at which IoT technologies are being developed has enabled smarter and innovative solutions in the … compromised to attack. Naturally, risk analysis emerges, as it is one of many steps to provide a reliable security strategy …

This paper discusses different classes of loss models in non-life insurance settings. It then overviews the class of … Tukey transform loss models that have not yet been widely considered in non-life insurance modelling, but offer … opportunities to produce flexible skewness and kurtosis features often required in loss modelling. In addition, these loss models …

Value-at-Risk (VaR) is a well-accepted risk metric in modern quantitative risk management (QRM). The classical Monte … Carlo simulation (MCS) approach, denoted henceforth as the classical approach, assumes the independence of loss severity and … loss frequency. In practice, this assumption does not always hold true. Through mathematical analyses, we show that the …

The stability of the financial system is associated with systemic risk factors such as the concurrent default of … the case of large, overlapping credit portfolios. We analytically calculate the multivariate joint loss distribution of … obligations to protect the more senior tranches from high losses. We analytically corroborate the observation that an extreme loss …

role that occurrence losses (order statistics) play in pricing of catastrophe excess of loss (catXL) contracts. Our … framework enables one to analytically quantify the contribution of a given occurrence loss to the mean and covariance structure …

Optimal reinsurance problems under the risk measures, such as Value-at-Risk (VaR) and Tail-Value-at-Risk (TVaR), have … for catastrophic losses. In this paper, we propose a new family of flexible risk measures denoted by LVaR, which is a … weighted combination of VaR and TVaR. Based on the new risk measures, we deal with the optimal reinsurance problem by …

the loss aversion of a sponsor, who is assumed to be more sensitive to underfunding than overfunding. Through the lens of … prospect theory, we first set up a loss-aversion utility function for a sponsor whose utility depends on the funding ratio in … retirement. We also find that the equity portion of the portfolio increases when a sponsor is less loss-averse or the …

The interdependence between multiple lines of business has an important impact on determining loss reserves and risk …, we study rank-based methods using the Sarmanov distribution to adequately estimate the loss reserves and properly capture … robust estimation, and better captures the dependence between the risks. We also show that it generates smaller risk capital …

A vast majority of Loss Given Default (LGD) models are currently in use. Over all the years since the new Capital … selecting the risk drivers. …

profit and expected loss are the reward and risk metrics of such portfolios. An optimal portfolio can then be selected by … expected profit and expected loss that may be experienced for any portfolio of strikes of the call and put contracts. Expected … making the reward as high as possible under the risk tolerance set by the trader. Extensive back-testing applications to …