Tag Info

New answers tagged

3

Why not just do: $$ max \,\, \mu ^T w - \lambda w^T \Sigma w $$ s.t.: $$ w \leq V $$ $$ -w \leq V $$ $$ A w = 0 $$ Google for LP absolute value constraint transformations. Here is a helpful online tutorial. And if these are portfolio weights, don't forget that they should add up to 1.


1

One standard approach is to shrink your forecasts towards zero (or to some reasonable value as in the Black-Littermann model). Shrinking towards zero is done by: $$w^*=\underset{w}{\text{argmax}} \ \ \lambda_{\alpha} r^Tw - \lambda_r w^{T} \Sigma w - tradingCost(|w-w_0|)\\$$ $$0\leq\lambda_{\alpha}\leq1$$ Shrinkage coefficient $\lambda_{\alpha}$ is best ...



Top 50 recent answers are included