Work

Data-driven Multiperiod Robust Mean-Variance Optimization

Year: 2023

Type: preprint

Abstract: We study robust mean-variance optimization in multiperiod portfolio selection by allowing the true probability measure to be inside a Wasserstein ball centered at the empirical probability measure. Given the confidence level, the radius of the Wasserstein ball is determined by the empirical data. The numerical simulations of the US stock market provide a promising result compared to other popular strategies.

Source: RePEc: Research Papers in Economics

DOI: 10.48550/arxiv.2306.16681

Authors: Hai, Xin, Loeper, Gregoire, Nam, Kihun

Institution: Monash University

Language: English

Topic: Risk and Portfolio Optimization

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W4382765663

Cites:

Cited by:

Related to: 10