Risk aggregation and Extreme Events [32]

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Bullet points include: Aim is to characterise distributions of returns (movements) for each instrument (asset or liability) in a parsimonious manner Usually proceed as follows, for j’th instrument’s return in period t. Here j,k is the exposure (beta) of the instrument to the k’th factor, xk,t is the return on the k’th factor (for period t) and j,t are residual (idiosyncratic) components  Portfolio described by a vector of (active) weights a then has expected return of a. and (expected future) tracking error (expected future standard deviation of returns) as follows (where is matrix formed by j,k):

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