Work

An L-Moment Approach for Portfolio Choice under Non-Expected Utility

Year: 2024

Type: article

Abstract: We develop and apply a novel semi-parametric estimation method based on L-moments. Unlike conventional moments, L-moments are linear in the data and therefore robust to outliers. The estimation method provides a series expansion that quickly converges to the underlying return distribution and can be used when conventional moments do not exist. An extensive empirical analysis of portfolio choice under non-expected utility demonstrates the effectiveness of our approach. Empirical results show that our method copes well with estimation risk, yields stable portfolio returns, and reaps the information content of moment returns beyond order four.

Source: Journal of Financial Econometrics

DOI: 10.1093/jjfinec/nbae027

Authors: Hasan Fallahgoul, Loriano Mancini, Stoyan Stoyanov

Institutions: Monash University, Swiss Finance Institute, Università della Svizzera italiana, Charles Schwab Corporation (United States)

Language: English

Topic: Risk and Portfolio Optimization

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: hybrid

Estimated APC paid: $5,094

Funder: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung