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Can the Sharia-Based Islamic Stock Market Returns be Forecasted Using Large Number of Predictors and Models?

Rangan Gupta (), Shawkat Hammoudeh, Beatrice Desiree Simo-Kengne and Soodabeh Sarafrazi ()
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Soodabeh Sarafrazi: Lebow College of Business, Drexel University, Philadelphia, USA

No 201381, Working Papers from University of Pretoria, Department of Economics

Abstract: This study employs fourteen global economic and financial variables to predict the return of the Islamic stock market as identified by the Dow Jones Islamic stock market. It implements alternative forecasting methods and allows for nonlinearity in the multivariate predictive regressions by estimating time-varying parameter models. All the methods fail to forecast the returns of the Sharia-based DJIM index over the out-of-sample period. The forecasts are weak at best, with only four predictors the three-month Treasury bill rate, inflation, oil price and return on the S&P500 index outperforming the benchmark autoregressive model of order one. The study suggests that the DJIM return is best predicted by an AR(1) model, and that future research should aim at analysing whether the performance of the linear autoregressive model can be improved by using nonlinear methods.

Keywords: DJIM; forecasting methods; out-of-sample forecasts; benchmark model (search for similar items in EconPapers)
JEL-codes: C58 G11 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2013-12
New Economics Papers: this item is included in nep-for
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