EconPapers    
Economics at your fingertips  
 

A Genetic Algorithm for Investment–Consumption Optimization with Value-at-Risk Constraint and Information-Processing Cost

Zhuo Jin (), Zhixin Yang () and Quan Yuan ()
Additional contact information
Zhuo Jin: Centre for Actuarial Studies, Department of Economics, The University of Melbourne, Melbourne, VIC 3010, Australia
Zhixin Yang: Department of Mathematical Sciences, Ball State University, Muncie, IN 47306, USA
Quan Yuan: Department of Mathematical Sciences, Ball State University, Muncie, IN 47306, USA

Risks, 2019, vol. 7, issue 1, 1-15

Abstract: This paper studies the optimal investment and consumption strategies in a two-asset model. A dynamic Value-at-Risk constraint is imposed to manage the wealth process. By using Value at Risk as the risk measure during the investment horizon, the decision maker can dynamically monitor the exposed risk and quantify the maximum expected loss over a finite horizon period at a given confidence level. In addition, the decision maker has to filter the key economic factors to make decisions. Considering the cost of filtering the factors, the decision maker aims to maximize the utility of consumption in a finite horizon. By using the Kalman filter, a partially observed system is converted to a completely observed one. However, due to the cost of information processing, the decision maker fails to process the information in an arbitrarily rational manner and can only make decisions on the basis of the limited observed signals. A genetic algorithm was developed to find the optimal investment, consumption strategies, and observation strength. Numerical simulation results are provided to illustrate the performance of the algorithm.

Keywords: genetic algorithm; investment; Value-at-Risk; rational inattention (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 M2 M4 K2 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
https://www.mdpi.com/2227-9091/7/1/32/pdf (application/pdf)
https://www.mdpi.com/2227-9091/7/1/32/ (text/html)

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:gam:jrisks:v:7:y:2019:i:1:p:32-:d:212642

Access Statistics for this article

Risks is currently edited by Prof. Dr. J. David Cummins

More articles in Risks from MDPI, Open Access Journal
Bibliographic data for series maintained by XML Conversion Team ().

 
Page updated 2019-03-30
Handle: RePEc:gam:jrisks:v:7:y:2019:i:1:p:32-:d:212642