The Co-Movement of JSE Size-Based Indices: Evidence from a Time–Frequency Domain

This research examines the time–frequency co-movement patterns among the Johannesburg Stock Exchange (JSE) size-based indices, utilizing daily data covering the period from November 2016 to December 2024. To conduct the analysis, three sophisticated wavelet techniques are applied: the Maximal Overlap Discrete Wavelet Transform (MODWT), the Continuous Wavelet Transform (WTC), and the Wavelet Phase Angle (WPA) model. Subsequently, the Multivariate Generalized Autoregressive Conditional Heteroscedasticity–Asymmetric Dynamic Conditional Correlation (MGARCH-DCC) model is employed to evaluate the robustness of the findings. The results reveal that the co-movement among the JSE size-based indices is influenced by investment holding periods and prevailing market conditions. Notably, a lead–lag relationship is identified, indicating that a single size-based index often drives the co-movement of the others. These findings carry important implications for investors, policymakers, and portfolio managers. Investors should account for optimal holding periods to avoid increased correlation and reduced diversification benefits. Policymakers are advised to mitigate financial market uncertainty, particularly during bearish phases, to manage excessive index co-movement. Portfolio managers must integrate both holding periods and market conditions into their investment strategies. This research offers a novel contribution to the South African investment landscape by providing practical and risk-mitigating insights into the role of JSE size-based indices within diversified portfolios—a topic that has received limited attention despite its growing relevance.

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Publication Details

Journal
Journal of risk and financial management
Published
2025-11-11
DOI
https://doi.org/10.3390/jrfm18110633
Citations
1
Primary Topic
Financial Risk and Volatility Modeling
Type
article
Field-Weighted Citation Impact
2.21
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article

The Co-Movement of JSE Size-Based Indices: Evidence from a Time–Frequency Domain

Fabian Moodley
1 citations
Journal of risk and financial management
Financial Risk and Volatility Modeling
2.21
article

The Co-Movement of JSE Size-Based Indices: Evidence from a Time–Frequency Domain

Fabian Moodley
article en
1 citations

Abstract

This research examines the time–frequency co-movement patterns among the Johannesburg Stock Exchange (JSE) size-based indices, utilizing daily data covering the period from November 2016 to December 2024. To conduct the analysis, three sophisticated wavelet techniques are applied: the Maximal Overlap Discrete Wavelet Transform (MODWT), the Continuous Wavelet Transform (WTC), and the Wavelet Phase Angle (WPA) model. Subsequently, the Multivariate Generalized Autoregressive Conditional Heteroscedasticity–Asymmetric Dynamic Conditional Correlation (MGARCH-DCC) model is employed to evaluate the robustness of the findings. The results reveal that the co-movement among the JSE size-based indices is influenced by investment holding periods and prevailing market conditions. Notably, a lead–lag relationship is identified, indicating that a single size-based index often drives the co-movement of the others. These findings carry important implications for investors, policymakers, and portfolio managers. Investors should account for optimal holding periods to avoid increased correlation and reduced diversification benefits. Policymakers are advised to mitigate financial market uncertainty, particularly during bearish phases, to manage excessive index co-movement. Portfolio managers must integrate both holding periods and market conditions into their investment strategies. This research offers a novel contribution to the South African investment landscape by providing practical and risk-mitigating insights into the role of JSE size-based indices within diversified portfolios—a topic that has received limited attention despite its growing relevance.

Journal of risk and financial managementVol. 18(11)
North-West University (ZA)
Openalex Percentile: Top 10%
Financial Risk and Volatility Modeling
2.21
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The Co-Movement of JSE Size-Based Indices: Evidence from a Time–Frequency Domain — Fabian Moodley · Journal of risk and financial management (2025) | TGRS Research Map | TGRS