'The convex-concave algorithm applied to portfolio analysis

'The convex-concave algorithm applied to portfolio analysis

Zijdenbos, J.M.

de Klerk, E. (mentor)

Electrical Engineering, Mathematics and Computer Science

Delft Institute of Applied Mathematics

2016-07-01

Mathematical computations are widely used to give some insight into the stock market. We investigate the convex-concave algorithm for nonlinear optimization applied to portfolio analysis, one of its many applications. We will consider the Markowitz mean-variance model with higher order moments added, and look at the preferences for the investor to his odd and even moments. The nonlinear objective functions may not necessarily be convex nor concave. We write the objective function as the sum of a convex and concave function. Using the fact that it is easy to minimize convex functions on convex compact sets (under some assumptions), and linearizing the concave function at a fixed point, we optimize `easy' convex sub-problems at each iteration. This so-called convex-concave procedure is known to converge to a KKT point.

http://resolver.tudelft.nl/uuid:68593d9c-ba8d-407b-9d9c-5821dab5344f

Student theses

bachelor thesis

(c) 2016 Zijdenbos, J.M.