Stochastic optimization models for portfolio selection and risk management<BR>

<P>
Alexei A. Gaivoronski,
Norwegian University of Science and Technology
<BR>

<p>
Abstract: <BR>

<p>
We consider here several interrelated optimization models for portfolio selection and risk management which can be broadly classified as belonging to stochastic optimization models. In particular we consider
<DT>
<DD>-	Selection of VaR-optimal portfolios where we design numerical approach and software tools for computing mean-Value-at-Risk efficient portfolios starting from historic data. The underlying theory is presented together with the results of extensive in-sample and out of sample experiments with the data sets of interest to institutional investor.
</DD> <BR>
<DD>-	Risk budgeting models where investor faces the problem of portfolio selection from a set of financial instruments which are exposed to partially commeasurable risks. The typical example is budgeting of risk exposure between passive and active portfolio management strategies.
</DD>
</DT>
<p>
We show that the modern stochastic optimization methodology provides efficient solutions to risk management problems in context of portfolio selection.