Dynamic Relationship between the Iranian Stock Market and Commodity Markets: A TVP-VAR Approach and Portfolio Optimization

Articles in Press

Document Type : Research Paper

Authors

1 Assistant Professor, Department of Economics, Faculty of Economics and Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, Iran

2 Master student in Economics, Department of Economics, Faculty of Economics and Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, Iran

Abstract

This study employs the Time-Varying Parameter Vector Autoregression (TVP-VAR) model to investigate the dynamic relationships between various commodity markets—including copper, aluminum, nickel, tin, zinc, lead, gold, and crude oil—and the Iranian stock market over the period from June 16, 2014, to May 21, 2024. The results indicate that cross-market interactions account for approximately 42.69% of the forecast error variance, revealing significant spillovers among these markets. By utilizing pairwise connectedness indices, an optimal asset portfolio is constructed using the minimum connectedness approach (MCoP) and is subsequently compared with traditional methods such as the Minimum Variance Portfolio (MVP) and the Minimum Correlation Portfolio (MCP). The analysis demonstrates that optimal portfolio weights differ across investment strategies, with gold and the Iranian stock index consistently exhibiting the highest weights in the optimal portfolios. Furthermore, an examination of optimal weights in two-asset portfolios underscores a preference for increased investments in copper and gold. Hedging strategies also prove effective in mitigating asset volatility, particularly in the nickel and Brent oil markets. These findings carry important implications for policymakers and investors alike.

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Journal of Asset Management and Financing

Articles in Press, Accepted Manuscript
Available Online from 01 February 2025

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