Symbols
∀ | for all |
∃ | there exists |
∪ | union of two sets |
∩ | intersection of two sets |
* | convolution operator |
F(·) | probability distribution function |
C(u1, u2, . . . , ud) | d-dimensional Copula probability distribution function. |
tail function (x) = 1 − F(x) | |
f(·) | probability density function |
h(·) | hazard rate given by |
ΦX[θ] | characteristic function for random variable X |
MX(t) | moment-generating function of random variable X |
F(n)*(·) | n-fold convolution of distribution function with itself |
F−1(·) | inverse distribution function (quantile function) |
Q(α) | quantile function |
U(y) = Q(1 − 1/y) | tail quantile function |
F←(·) | generalized inverse |
g(·) ~ f(·) | function g is asymptotic equivalent to f at infinity (unless specified otherwise) |
X ~ F(·) | random variable X is distributed according to F |
X(k,n) | kth largest sample from n samples, that is, the kth order statistic |
VaRα[·] | value at risk for level α |
ESα[·] | expected shortfall for level α |
SRMα[·] | spectral risk measure for level α |
space of integers | |
real line | |
complex plane | |
e{·} | real component of complex number ... |
Get Advances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.