Predicting BRICS stock returns using ARFIMA models
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Date
2014
Journal Title
Journal ISSN
Volume Title
Publisher
Applied Financial Economics
Abstract
This article examines the existence of long memory in daily stock market returns
from Brazil, Russia, India, China and South Africa (BRICS) countries and also
attempts to shed light on the efficacy of autoregressive fractionally integrated
moving average (ARFIMA) models in predicting stock returns. We present
evidence which suggests that ARFIMA models estimated using a variety of
estimation procedures yield better forecasting results than the non-ARFIMA
(AR, MA, ARMA and GARCH) models with regard to prediction of stock
returns. These findings hold consistently for the different countries whose econo-
mies differ in size, nature and sophistication.
Description
Keywords
Fractional integration, Long memory, Stock returns, Long-horizon prediction, ARFIMA, BRICS
Citation
Goodness C. Aye, Mehmet Balcilar, Rangan Gupta, Nicholas Kilimani, Amandine Nakumuryango & Siobhan Redford (2014) Predicting BRICS stock returns using ARFIMA models, Applied Financial Economics, 24:17, 1159-1166, DOI: 10.1080/09603107.2014.924297