Araştırma Makalesi

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

Cilt: 9 Sayı: 1 26 Haziran 2025
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Dynamic Connectedness among Australian Stock Market Sectors: A Time-Varying Parameter VAR Approach

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.

Keywords

Kaynakça

  1. Abidin, S., Reddy, K., & Zhang, C. (2014). Intensity of price and volatility spillover effects in asia-pacific basin equity markets. Australasian Accounting, Business and Finance Journal, 8(5), 3–18. https://doi.org/10.14453/aabfj.v8i5.2
  2. Anscombe, F. J., & Glynn, W. J. (1983). Distribution of the kurtosis statistic b2 for normal samples. Biometrika, 70(1), 227–234. https://doi.org/10.1093/biomet/70.1.227
  3. Antonakakis, N., Chatziantoniou, I., & Gabauer, D. (2020). Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions. Journal of Risk and Financial Management, 13(4), 1–23. https://doi.org/10.3390/jrfm13040084
  4. Balcilar, M., Gabauer, D., & Umar, Z. (2021). Crude Oil futures contracts and commodity markets: New evidence from a TVP-VAR extended joint connectedness approach. Resources Policy, 73(April), 102219. https://doi.org/10.1016/j.resourpol.2021.102219
  5. Baruník, J., & Křehlík, T. (2018). Measuring the frequency dynamics of financial connectedness and systemic risk. Journal of Financial Econometrics, 16(2), 271–296. https://doi.org/10.1093/jjfinec/nby001
  6. Bissoondoyal-Bheenick, E., Brooks, R., Chi, W., & Do, H. X. (2018). Volatility spillover between the US, Chinese and Australian stock markets. Australian Journal of Management, 43(2), 263–285. https://doi.org/10.1177/0312896217717305
  7. Caldara, D., Fuentes-Albero, C., Gilchrist, S., & Zakrajšek, E. (2016). The macroeconomic impact of financial and uncertainty shocks. European Economic Review, 88, 185–207. https://doi.org/10.1016/j.euroecorev.2016.02.020
  8. Cao, G., & Xie, F. (2024). Extreme risk spillovers across energy and carbon markets: Evidence from the quantile extended joint connectedness approach. International Journal of Finance and Economics, 29(2), 2155–2175. https://doi.org/10.1002/ijfe.2781

Ayrıntılar

Birincil Dil

İngilizce

Konular

Ekonometri (Diğer)

Bölüm

Araştırma Makalesi

Yayımlanma Tarihi

26 Haziran 2025

Gönderilme Tarihi

4 Mart 2025

Kabul Tarihi

9 Mayıs 2025

Yayımlandığı Sayı

Yıl 2025 Cilt: 9 Sayı: 1

Kaynak Göster

APA
Akıncı Tok, Ş. (2025). Dynamic Connectedness among Australian Stock Market Sectors: A Time-Varying Parameter VAR Approach. Bingöl Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 9(1), 151-165. https://doi.org/10.33399/biibfad.1651020


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