Forecasting silver prices: a univariate ARIMA approach and a proposed model for future direction

The purpose of this study is to comprehensively examine and anticipate future silver prices in the Indian context. Given silver’s historical importance as a valuable material over 6000 years, this research sought to determine the intricate price movements impacted by a multitude of factors. While the research acknowledges the complexity of these patterns, its main goal is to shed light on the major reasons behind silver price changes. The Autoregressive Integrated Moving Average (ARIMA) was used in the study. Based on data stationarity, this model carefully integrates Auto regression and Moving Average components. The research process is divided into four separate phases: identification, estimation, diagnostics, and forecasting, which are all carried out using the ARIMA (p, d, q) model. The ARIMA model identified and explained around 26% of the observed silver price changes. This implies that there are more relevant elements than those addressed in the model. The research emphasizes the diverse character of silver price factors and emphasizes the need for a more comprehensive understanding. This study contributes to the area through the introduction of a suggested conceptual framework that incorporates Google trend analytics and an extensive literature review. This novel methodology is intended to study the main factors that influence silver prices and their complicated interrelationships. This study contributes to the evolving discussion on silver price analysis and predictions by providing the groundwork for further studies in this area.