Can the Sharia-based Islamic stock market returns be forecasted using large number of predictors and models?
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Date
Authors
Gupta, Rangan
Hammoudeh, Shawkat
Simo-Kengne, Beatrice Desiree
Sarafrazi, Soodabeh
Journal Title
Journal ISSN
Volume Title
Publisher
Taylor & Francis
Abstract
This study employs 14 global economic and financial variables to predict the return of the Islamic stock market as identified by the Dow Jones Islamic Stock Market (DJIM). 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 3-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 autocorrelation(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.
Description
Keywords
Forecasting methods, Out-of-sample forecasts, Benchmark model, Dow Jones Islamic Stock Market (DJIM)
Sustainable Development Goals
Citation
Gupta, R, Hammoudeh, S, Simo-Kengne, BD & Sarafrazi, S 2014, 'Can the Sharia-based Islamic stock market returns be forecasted using large number of predictors and models?', Applied Financial Economics, vol. 24, no. 17, pp. 1147-1157.