Unit root modeling for trending stock market series

Salisu, Afees A. and Ndako, Umar B. and Oloko, Tirimisiyu F. and Akanni, Lateef O. (2016) Unit root modeling for trending stock market series. Borsa Istanbul Review, 16 (2). pp. 82-91. (https://doi.org/10.1016/j.bir.2016.05.001)

[thumbnail of Salisu-etal-BIR-2016-Unit-root-modeling-for-trending-stock-market-series]
Preview
 Text. Filename: Salisu_etal_BIR_2016_Unit_root_modeling_for_trending_stock_market_series.pdf
Final Published Version
License: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 logo
Download (482kB)| Preview

Abstract

In this paper, we examine how the unit root for stock market series should be modeled. We employ the Narayan and Liu (2015) trend GARCH-based unit root and its variants in order to more carefully capture the inherent statistical behavior of the series. We utilize daily, weekly and monthly data covering nineteen countries across the regions of America, Asia and Europe. We find that the nature of data frequency matters for unit root testing when dealing with stock market data. Our evidence also suggests that stock market data is better modeled in the presence of structural breaks, conditional heteroscedasticity and time trend.

CORE (COnnecting REpositories)