An Explainable AI Regression Model For Gold Price Prediction

Gold is an important commodity that has a significant influence on important business sectors and the world economy. Its impact on the dynamics of the market reverberates through multiple channels, making it a highly desirable asset. Central banks in many nations utilize gold as a reserve asset, which they then exchange for national currencies to inject into markets. Its inherent value is recognized by both companies and gold traders, and it is especially evident during times of inflation and market turbulence. The development of a machine learning model to anticipate the price of gold has many potential applications for traders, businesses, investors, and even laypeople who want to make money on gold investments. By utilizing a variety of significant factors that affect gold prices throughout the world, a strong prediction model based on a ten-year market trend can be developed. This research paper aims to democratize gold investing opportunities by providing end users with feasible options so they may maximize profits while minimizing risks and losses. Positive results were obtained from our investigation into a variety of machine learning models. When Explainable AI approaches are applied, it becomes possible to fully comprehend how various algorithms rank different features as key contributors during model training.