Selective Linear Segmentation For Detecting Relevant Parameter Changes

68 Pages Posted: 10 Oct 2019

See all articles by Arnaud Dufays

Arnaud Dufays

CeReFiM. Université de Namur.; Université Laval

Houndetoungan Aristide

Université Laval - Département d'Économique

Alain Coen

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

Date Written: August 20, 2019

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 Elysée Aristide, Houndetoungan and Coen, Alain, Selective Linear Segmentation For Detecting Relevant Parameter Changes (August 20, 2019). Available at SSRN: https://ssrn.com/abstract=3461554 or http://dx.doi.org/10.2139/ssrn.3461554

Arnaud Dufays (Contact Author)

CeReFiM. Université de Namur. ( email )

Rempart de la Vierge 8
Namur, Namur 5000
Belgium

Université Laval ( email )

2214 Pavillon J-A. DeSeve
Quebec, Quebec G1K 7P4
Canada

Houndetoungan Elysée Aristide

Université Laval - Département d'Économique ( email )

2325 Rue de l'Université
Ste-Foy, Quebec G1K 7P4 G1K 7P4
Canada

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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