Predicting BRICS stock returns using ARFIMA models
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 economies differ in size, nature and sophistication.
Year of publication: |
2014
|
---|---|
Authors: | Aye, Goodness C. ; Balcilar, Mehmet ; Gupta, Rangan ; Kilimani, Nicholas ; Nakumuryango, Amandine ; Redford, Siobhan |
Published in: |
Applied Financial Economics. - Taylor & Francis Journals, ISSN 0960-3107. - Vol. 24.2014, 17, p. 1159-1166
|
Publisher: |
Taylor & Francis Journals |
Saved in:
Saved in favorites
Similar items by person
-
Predicting BRICS Stock Returns Using ARFIMA Models
Aye, Goodness C., (2012)
-
Predicting BRICS stock returns using ARFIMA models
Aye, Goodness C., (2014)
-
Persistence in Precious Metal Prices: A Fractional Integration Approach with Structural Breaks
Gil-Alana, Luis A., (2014)
- More ...