Gold Price Prediction using ARIMA model

The most valuable metal in the world is gold. It is the most sought-after commodity available. The study and forecasting of the daily gold price rate and the future gold price rate using machine learning algorithms and methodologies. Due to the multifactorial and nonlinear structure of the gold market, it is impossible to anticipate the gold price, which is influenced by a variety of external variables like marketing conditions, economic crises, oil price rate hikes, tax benefits, and interest rates. Using machine learning to enhance the performance of certain types of activities. It is used to the forecasting of financial variables, with an emphasis on equities rather than commodities. It focuses on how predictions are made utilising datasets and statistical analysis. Using ensemble-based machine learning methods such as Linear Regression, ARIMA Model, Random Forest Regression. The predictions are derived from a dataset of gold price rates. The performance measurements are MAE and RMSE. In Linear Regression values are 19.82,24.41. ARIMAA model 0.040, 0.046 and Random Forest is 0.150, 0.156. The results suggest ARIMAA model predict value in high accuracy.