Pravin Kumar Agrawal | Mohit Kumar
pages: 1-14; JEL classification: G10, G11, G17, G32 ; Keywords: Nifty 50, Johansen Cointegration Test, Vector Error Correction Model, Variance Decomposition Analysis, Impulse Response Function, Augmented Dickey Fuller Test; Abstract: Globalization and liberalization have heightened the volatility and complexity of financial markets, prompting investors to diversify their portfolios across different asset classes. This study investigates the dynamic interrelationships among the Indian stock market benchmark index (Nifty 50), gold prices, oil prices (Brent and WTI), and the USD/INR exchange rate, using high-frequency daily data from January 2009 to March 2023. By employing a Vector Error Correction Model (VECM) and Variance Decomposition Analysis (VDA), the study explores both the short-term and long-term dynamics between these asset classes. The results reveal that a long-term equilibrium exists among the variables, with significant cointegration, indicating that investors may not benefit from diversifying their portfolios across these assets. The VECM analysis further shows that the stock market is influenced by changes in gold prices, exchange rates, and oil prices, with long-run causality running from these variables to the Nifty 50. Variance decomposition highlights the growing impact of gold, exchange rates, and oil prices on stock market fluctuations over time. These findings provide crucial insights for investors, portfolio managers, and policymakers, suggesting that external shocks in commodity prices and exchange rates can significantly affect stock market performance. The study concludes that understanding these dynamic linkages is essential for managing investment risks and formulating effective monetary and fiscal policies.