Optimal consumption and investment problems under GARCH with transaction costs

Zhiping Chen () and K. C. Yuen

Mathematical Methods of Operations Research, 2005, vol. 61, issue 2, 219-237

Abstract: General multiperiod optimal consumption and investment problems with proportional transaction costs are investigated in this paper, a GARCH-type process is used to model the risky asset’s return series so that its time-varying moments and conditional heteroskedasticity can be properly described. We model this kind of consumption and investment problems as dynamic stochastic optimization problems, which can easily cope with different utility functions and any number of time periods. The procedure to efficiently solve the resulting nonlinear stochastic optimization problem is discussed in detail and a parallelizable decomposition algorithm is devised. Numerical results show the suitability and promise of our methodology. Copyright Springer-Verlag 2005

Keywords: Consumption and investment problems; The GARCH model; Stochastic programming; Decomposition; The augmented Lagrangian (search for similar items in EconPapers)
Date: 2005
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1007/s001860400396 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:mathme:v:61:y:2005:i:2:p:219-237

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/00186

DOI: 10.1007/s001860400396

Access Statistics for this article

Mathematical Methods of Operations Research is currently edited by Oliver Stein

More articles in Mathematical Methods of Operations Research from Springer, Gesellschaft für Operations Research (GOR), Nederlands Genootschap voor Besliskunde (NGB)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().