minimizes the cost of the supply chain while the second objective function minimizes CO2 emission. Conditional Value at Risk … (CVaR) approach is adapted to deal with demand uncertainty and the stochastic CO2 emission level. Finally, the model outputs …

. Furthermore, the model allows exact (without Monte Carlo simulation error) calculation of risk measures and their sensitivities … risk model CreditRisk+. This allows exact risk aggregation via an efficient numerically stable Panjer recursion algorithm … with respect to model parameters for P&L distributions such as value-at-risk and expected shortfall. Numerous examples …

) the correlation among the risk factors, 2) the contractual obligations, which are assumed to follow popular contracts in …

, by incorporating the conditional value at risk (CVaR), the risk induced by uncertain demand is explicitly considered. The …

This paper characterizes higher order risk effects, such as prudence and temperance, via preferences that partially …

In the context of stochastic uncertainty and the increasing complexity of logistics processes in the retail sector … purpose of the present work is to assess the impact of risk events and unstable conditions on the level of quality of supply … chain services and economic indicators of the retail trade network. Using the anyLogistix software tool, a simulation model …

We present a stochastic simulation model for estimating forward-looking corporate probability of default and loss given … identify the default condition, and solve the model by Monte Carlo simulation. First, we present the model; then we show how to …

We present a stochastic simulation forecasting model for stress testing that is aimed at assessing banks’ capital …