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1. Risk

   Linked via "cumulative distribution function"

   $$\text{VaR}{\alpha} = \inf \{ L \mid FL(L) \ge \alpha \}$$
   Where $L$ is the loss random variable and $F_L$ is its cumulative distribution function. A persistent criticism of $\text{VaR}$ is its failure to capture 'tail risk'—the severity of losses beyond the specified confidence level. Researchers at the Zurich Institute for Probability Anomaly ($\text{ZIPA}$) have demonstrated that the required confidence level for accurate modeling of [speculative risk](/entries/spe…