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Dynamic Connectedness among Australian Stock Market Sectors: A Time-Varying Parameter VAR Approach

Author

Listed:
  • Şerife Akıncı TOK

    (Zonguldak Bülent Ecevit University)

Abstract

This study investigates the dynamic connectedness among six key sectors in the Australian Stock Exchange (ASX) using a Time-Varying Parameter Vector Autoregressive (TVP-VAR) model. By examining the interactions among Consumer Staples, Energy, Financials, Industrials, Information Technology, and Metals & Mining indices, the analysis highlights how sectoral connectedness evolves, particularly during periods of economic crisis. The results reveal that specific sectors act as net transmitters or receivers of shocks. Energy, Metals, & Mining are more sensitive to global commodity prices, while Consumer Staples maintain stability. This approach offers a comprehensive view of sectoral risk transmission and its implications for market stability and risk management. The findings provide critical insights for investors and policymakers aiming to mitigate systemic risks and enhance portfolio diversification in response to market fluctuations.

Suggested Citation

  • Şerife Akıncı TOK, 2025. "Dynamic Connectedness among Australian Stock Market Sectors: A Time-Varying Parameter VAR Approach," Bingol University Journal of Economics and Administrative Sciences, Bingol University, Faculty of Economics and Administrative Sciences, vol. 9(1), pages 151-165, June.
    • Handle: RePEc:bgo:journl:v:9:y:2025:i:1:p:151-165
    DOI: https://doi.org/10.33399/biibfad.1651020
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    References listed on IDEAS

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    1. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    2. Diebold, Francis X. & Yilmaz, Kamil, 2012. "Better to give than to receive: Predictive directional measurement of volatility spillovers," International Journal of Forecasting, Elsevier, vol. 28(1), pages 57-66.
    3. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    4. Thomas J. Fisher & Colin M. Gallagher, 2012. "New Weighted Portmanteau Statistics for Time Series Goodness of Fit Testing," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(498), pages 777-787, June.
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    Keywords

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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