Luck or Technique? A Study on the Performance of the Stock Market in the Light of Different Forecasting Techniques

Abstract

Purpose: to examine the predictive performance of linear, non-linear, artificial intelligence, frequency domain and hybrid models to find an appropriate model for predicting the return on shares in developed, emerging and frontier markets. Methodology: the daily stock market returns of selected indices from developed, emerging and frontier markets in 24 countries for the period 2000–2019 were considered to assess the predictive performance of five existing models. Main Findings: the results indicated that none of the five models could be applied uniformly to all markets. However, traditional linear and non-linear models have outperformed artificial intelligence and models in the frequency domain by providing more accurate predictions. Academic and practical contributions: this study is particularly useful for international investors and foreign institutional investors who wish to minimize risks and diversify their portfolios, with the aim of maximizing profits.