Stock market efficiency beyond the joint hypothesis: Reevaluating the Moroccan stock market Efficiency through ARFIMA-FIGARCH model
Abstract
In the context of an unstable international environment, the assessment of the state of stock market efficiency remains of paramount importance. For this reason, we intend to implement ARFIMA-FIGARCH modeling over the period from 2 January 2013 to 29 December 2023. This will enable us to reevaluate efficiency beyond the problem of its joint hypothesis in the context of the Moroccan stock market. The results of our study indicate the presence of substantial evidence supporting the existence of long memory in both returns and volatility of the Moroccan stock market. These findings call into question the foundations of the Efficient Market Hypothesis beyond the Joint hypothesis problem, while offering novel insights into the dynamics of an emerging market. The findings have a practical significance in the fields of forecasting and risk management, as the persistence of return and volatility dynamics directly affects investment strategies and policymaking. Methodologically, the employment of a rigorous ARFIMA-FIGARCH framework enhances the robustness of the analysis by accounting for non-normality and heteroskedasticity in daily financial data.
Fields of Study & Subjects
Financial Risk and Volatility Modeling
Financial Markets and Investment Strategies
Stock Market Forecasting Methods
Publication details
- Journal / source
- Multidisciplinary Science Journal
- Volume
- 8
- Issue
- 7
- Pages
- 2026449–2026449
- Publication date
- 15 January 2026
- Language
- EN