We derive a closed form portfolio optimization rule for an investor who is diffident about mean return and volatility estimates, and has a CRRA utility. Confidence is here represented using ellipsoidal uncertainty sets for the drift, given a (compact valued) volatility realization. This specification affords a simple and concise analysis, as the agent becomes observationally equivalent to one with constant, worst case parameters. The result is based on a max–min Hamilton–Jacobi–Bellman–Isaacs PDE, which extends the classical Merton problem and reverts to it for an ambiguity-neutral investor.

The robust Merton problem of an ambiguity averse investor / Biagini, Sara; Pınar, Mustafa Ç.. - In: MATHEMATICS AND FINANCIAL ECONOMICS. - ISSN 1862-9679. - 11:1(2017), pp. 1-24. [10.1007/s11579-016-0168-6]

The robust Merton problem of an ambiguity averse investor

BIAGINI, SARA
;
2017

Abstract

We derive a closed form portfolio optimization rule for an investor who is diffident about mean return and volatility estimates, and has a CRRA utility. Confidence is here represented using ellipsoidal uncertainty sets for the drift, given a (compact valued) volatility realization. This specification affords a simple and concise analysis, as the agent becomes observationally equivalent to one with constant, worst case parameters. The result is based on a max–min Hamilton–Jacobi–Bellman–Isaacs PDE, which extends the classical Merton problem and reverts to it for an ambiguity-neutral investor.
Ellipsoidal uncertainty on mean returns; Hamilton–Jacobi–Bellman–Isaacs equation; Merton problem; Robust optimization; Volatility uncertainty; Finance; Statistics and Probability; Statistics, Probability and Uncertainty
File in questo prodotto:
File Dimensione Formato  
11579_2016_168_Author-Sara-proofs.pdf

Solo gestori archivio

Tipologia: Documento in Post-print
Licenza: DRM non definito
Dimensione 543.27 kB
Formato Adobe PDF
543.27 kB Adobe PDF   Visualizza/Apri
Biagini-Pınar2017_Article_TheRobustMertonProblemOfAnAmbi.pdf

Solo gestori archivio

Tipologia: Versione dell'editore
Licenza: DRM non definito
Dimensione 564.95 kB
Formato Adobe PDF
564.95 kB Adobe PDF   Visualizza/Apri
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11385/171254
Citazioni
  • Scopus 35
  • ???jsp.display-item.citation.isi??? 39
social impact