Detecting Structural Breaks in Foreign Exchange Markets by using the group LASSO technique

TL;DR

This paper introduces a group LASSO-based method to identify structural breaks in foreign exchange market time series, accurately estimating the timing and magnitude of parameter changes.

Contribution

It presents a novel application of group LASSO for detecting sparse structural breaks in linear time series models.

Findings

Successfully detects breakpoints and their magnitudes

Estimates time-varying parameters effectively

Applicable to foreign exchange market data

Abstract

This article proposes an estimation method to detect breakpoints for linear time series models with their parameters that jump scarcely. Its basic idea owes the group LASSO (group least absolute shrinkage and selection operator). The method practically provides estimates of such time-varying parameters of the models. An example shows that our method can detect each structural breakpoint's date and magnitude.