Selective Linear Segmentation For Detecting Relevant Parameter Changes

Arnaud Dufays, Elysee Aristide Houndetoungan, Alain Coën, Selective Linear Segmentation for Detecting Relevant Parameter Change s, Journal of Financial Econometrics, Volume 20, Issue 4, Fall 2022, Pages 762–805

72 Pages Posted: 10 Oct 2019 Last revised: 8 Feb 2024

See all articles by Arnaud Dufays

Arnaud Dufays

EDHEC Business school

Aristide Houndetoungan

Cy Cergy Paris Université - THEMA

Alain Coen

Université du Québec à Montréal (UQÀM) - Graduate School of Business (ESG)

Date Written: June 6, 2020

Abstract

Change-point processes are one flexible approach to model long time series. We propose a method to uncover which model parameter truly vary when a change-point is detected. Given a set of breakpoints, we use a penalized likelihood approach to select the best set of parameters that changes over time and we prove that the penalty function leads to a consistent selection of the true model. Estimation is carried out via the deterministic annealing expectation-maximization algorithm. Our method accounts for model selection uncertainty and associates a probability to all the possible time-varying parameter specifications. Monte Carlo simulations highlight that the method works well for many time series models including heteroskedastic processes. For a sample of 14 Hedge funds (HF) strategies, using an asset based style pricing model, we shed light on the promising ability of our method to detect the time-varying dynamics of risk exposures as well as to forecast HF returns.

Keywords: change-point, structural change, time-varying parameter, model selection, Hedge funds

JEL Classification: C11, C12, C22, C32, C52, C53

Suggested Citation

Dufays, Arnaud and Houndetoungan, Aristide and Coen, Alain, Selective Linear Segmentation For Detecting Relevant Parameter Changes (June 6, 2020). Arnaud Dufays, Elysee Aristide Houndetoungan, Alain Coën, Selective Linear Segmentation for Detecting Relevant Parameter Change s, Journal of Financial Econometrics, Volume 20, Issue 4, Fall 2022, Pages 762–805, Available at SSRN: https://ssrn.com/abstract=3461554 or http://dx.doi.org/10.2139/ssrn.3461554

Arnaud Dufays (Contact Author)

EDHEC Business school ( email )

24 Avenue Gustave Delory
Roubaix, 59100
France

Aristide Houndetoungan

Cy Cergy Paris Université - THEMA ( email )

33 boulevard du Port
Cergy, 95011
France

HOME PAGE: http://ahoundetoungan.com

Alain Coen

Université du Québec à Montréal (UQÀM) - Graduate School of Business (ESG) ( email )

P.O. Box 8888, Downtown Station
Succursale Centre Ville
Montreal, Quebec H3C 3P8
Canada
514-987-3000 (Phone)
418-681-2501 (Fax)

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