Abstract
The concept of the lead-lag relationship in finance is instrumental in enhancing the understanding of price discovery and risk management, as it elucidates how different assets interact and influence each other’s price movements. This lead-lag relationship is used to understand market patterns, investor behavior, potential opportunities, and insightful information. This paper investigates the dynamics of the lead-lag relationship in financial market and its implications for investment decision-making. The study analyzes spot and futures prices (near, next, and far-month contracts) for agricultural commodities, including guar gum, guar seed, castor, cotton, cotton oilseed, and dhaniya, sourced from the National Commodities and Derivatives Exchange (NCDEX) spanning from April 2015 to September 2024 by employing Augmented Dickey-Fuller (ADF) test and granger causality test. The study revealed that guar gum, guar seed, castor, cotton, cotton oil seed and dhaniya commodity spot prices do not influence the future prices. There was no causal relationship between the selected agricultural commodities spot prices and future prices. This may be attributed to factors such as fluctuations in supply and demand, market news, seasonality, interest rates, and geopolitical developments. Finally, it helps policymakers to forecast economic conditions more accurately and design anticipatory measures. Central banks can use lead-lag analysis to anticipate inflation or economic downturns. If certain economic indicators (like consumer demand or industrial output) tend to inflation, the central bank can adjust interest rates proactively.
Keywords: Agricultural Commodities, Granger Causality Test, Lead-Lag Relationship, Spot and Future Prices.