Derivatives and Internal Models pp 430-461 | Cite as

# The Variance — Covariance Method

## Abstract

The *variance-covariance method* makes use of covariances (volatilities and correlations) of the risk factors and the sensitivities of the portfolio values with respect to these risk factors with the goal of approximating the value at risk. This method leads directly to the final result, i.e., the portfolio’s value at risk; no information regarding market scenarios arises. The variance-covariance method utilizes linear approximations of the risk factors themselves throughout the entire calculation, often neglecting the .drift as well. In view of Equation 19.24, we have

The main idea characterizing this method, however, is that the portfolio value *V* is expanded in its Taylor series as a function of its risk factors S_{i}, *j = 1,…s, n, and approximated by breaking off after the first or second order term. Let*

denote the vector of risk factors. The Taylor expansion for the change in portfolio value δ*V*(**S**) up to second order is

The first “approximately equal” sign appears due to having broken off the Taylor series of the portfolio value, the second as a result of the linear approximation of the risk factors in accordance with Equation 20.1, and finally, in the last step, because the drift has been neglected. The last line in 20.2 is referred to as the *delta-gamma approximation*. An analogous approach leads to the *delta approximation*, for which the Taylor series in the above derivation is taken up to linear order only, resulting in an approximation solely consisting of the first of the two sums appearing in the last equation in 20.2.

## Keywords

Internal Model Moment Generate Function Individual Risk Factor Short Position Single Risk Factor## Preview

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