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Predicting BRICS Stock Returns Using ARFIMA Models

Goodness Aye (), Mehmet Balcilar, Rangan Gupta, Nicholas Kilimani (), Amandine Nakumuryango () and Siobhan Redford ()
Additional contact information
Goodness Aye: Department of Economics, University of Pretoria
Nicholas Kilimani: Department of Economics, University of Pretoria
Amandine Nakumuryango: Department of Economics, University of Pretoria
Siobhan Redford: Department of Economics, University of Pretoria

No 201235, Working Papers from University of Pretoria, Department of Economics

Abstract: This paper 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 the different countries whose economies differ in size, nature and sophistication.

Keywords: Fractional integration; long-memory; stock returns; long-horizon prediction; ARFIMA; BRICS (search for similar items in EconPapers)
JEL-codes: C15 C22 C53 (search for similar items in EconPapers)
Pages: 24 pages
Date: 2012-12
New Economics Papers: this item is included in nep-afr, nep-cis and nep-for
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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