Saved in:
Bibliographic Details
Main Authors: Chen, Bo, Liu, Jia
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2410.12570
Tags: Add Tag
No Tags, Be the first to tag this record!
Table of Contents:
  • We introduce a robo-advisor system that recommends customized investment portfolios to users using an expected utility model elicited from pairwise comparison questionnaires. The robo-advisor system comprises three fundamental components. First, we employ a static preference questionnaire approach to generate questionnaires consisting of pairwise item comparisons. Next, we design three optimization-based preference elicitation approaches to estimate the nominal utility function pessimistically, optimistically, and neutrally. Finally, we compute portfolios based on the nominal utility using an expected utility maximization optimization model. We conduct a series of numerical tests on a simulated user and a number of human users to evaluate the efficiency of the proposed model.