نوع مقاله : مقاله پژوهشی
نویسندگان
1 استادیار، گروه اقتصاد، دانشکده علوم اداری و اقتصادی، دانشگاه فردوسی مشهد، مشهد، ایران
2 دانشجوی کارشناسی ارشد اقتصاد، گروه اقتصاد، دانشکده علوم اداری و اقتصادی، دانشگاه فردوسی مشهد، مشهد، ایران
چکیده
کلیدواژه‌ها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
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.
کلیدواژه‌ها [English]
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