Work

Not monotonically correlated, but dependent: A family of normal mode copulas

Year: 2025

Type: article

Abstract: When scholars study joint distributions of multiple variables, copulas are useful. However, if the variables are not monotonically correlated with each other yet are still not independent, most of the conventional copulas are not up to the task. Examples include (inversed) U-shaped relationships and heteroskedasticity. To fill this gap, this article sheds new light on a little-known copula, which I call the “normal mode copula.” I characterize the copula’s properties and show that the copula is asymmetric and non monotonic under certain conditions. I also apply the copula to a dataset about U.S. House vote share and campaign expenditure to demonstrate that the normal mode copula has better performance than other conventional copulas.

Source: Communication in Statistics- Theory and Methods

DOI: 10.1080/03610926.2025.2458193

Author: Kentaro Fukumoto

Institution: Gakushuin University

Language: English

Topic: Financial Risk and Volatility Modeling

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: green

Funder: Japan Society for the Promotion of Science

Award: G4698825166