ELTE RiskLab

Diversity of Financial Risk 2024

29 November, 2024
ELTE TTK, Budapest

Speaker's bio

rasonyi_tablo
Miklós
Rásonyi
(Rényi Institute)
Miklos Rásonyi completed his PhD in 2002 and has been working at the Computer Institute of the Hungarian Academy of Sciences and at Péter Pázmány Catholic University till 2009. He was also member of the Financial and Actuarial Mathematics Research Group at Technical University, Vienna (2005-2007). From 2009 to 2013 he was at the University of Edinburgh, since 2013 he works at the Rényi Institute of Mathematics and, from 2021, at Eötvös Loránd University. In 2017 he obtained the degree of Doctor of the Hungarian Academy of Sciences. His current research concentrates on optimal investment, Markov chains in random environment and sampling algorithms for machine learning.
Portfolio choice for exponential investors when prices are mean-reverting
Several asset classes show mean-reverting features, e.g. commodities, commodity futures, long-term safe assets (gold). We investigate the portfolio choice problem for investors with exponential utilities (=high risk aversion) as the investment horizon T tends to infinity. It turns out that the optimal equivalent safe rate grows in a superlinear way, depending on the strength of the mean-reversion effect. We cannot find the exact optimisers but construct a family of simple, explicit strategies that are optimal asymptotically (they generate equivalent safe rates of the optimal order). Interestingly, the presence or absence of a drift leads to entirely different conclusions, the nonzero drift case spectacularly outperforming the driftless one. Time permitting, we also review some related results on fractional Brownian motion.