Non-concave optimal investment and no-arbitrage: a measure theoretical approach
Mathematical Finance
2016-08-29 v3
Abstract
We consider non-concave and non-smooth random utility functions with do- main of definition equal to the non-negative half-line. We use a dynamic pro- gramming framework together with measurable selection arguments to establish both the no-arbitrage condition characterization and the existence of an optimal portfolio in a (generically incomplete) discrete-time financial market model with finite time horizon. In contrast to the existing literature, we propose to consider a probability space which is not necessarily complete.
Keywords
Cite
@article{arxiv.1602.06685,
title = {Non-concave optimal investment and no-arbitrage: a measure theoretical approach},
author = {Romain Blanchard and Laurence Carassus and Miklós Rásonyi},
journal= {arXiv preprint arXiv:1602.06685},
year = {2016}
}