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The gold market is highly volatile and is considered the safest investment during economic uncertainties and inflationary pressures, and one must know its price movement. It is essential to know their prices because they can swing with the global financial markets around. Accurate prediction models allow the realization of profit based on insights derived from the model. The current study compares machine learning algorithms against econometric models in predicting gold prices in India. The efficiency of the models is evaluated based on RMSE, R-Square, AIC, BIC, and MAPE. Internal and external factors that affect the gold price were chosen for the study, they are historical gold prices, the demand and supply, exports and imports of gold, inflation, interest rates, the exchange rates (USD/INR), gold reserves, GDP, and BSE Sensex. Data is gathered for the period ranging from January 2010 to December 2023. From the analysis, it is evident that the econometric model outperforms traditional models in predicting gold prices.

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Comparing Econometric and Machine Learning Models for Gold Price Forecasting: A Comprehensive Approach

  • 章节

  • 发表日期：

    2025年

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  • M. Jahnavi,
  • Purushottam Bung,
  • N. Nagasubba Reddy,
  • Katari Santosh

摘要

The gold market is highly volatile and is considered the safest investment during economic uncertainties and inflationary pressures, and one must know its price movement. It is essential to know their prices because they can swing with the global financial markets around. Accurate prediction models allow the realization of profit based on insights derived from the model. The current study compares machine learning algorithms against econometric models in predicting gold prices in India. The efficiency of the models is evaluated based on RMSE, R-Square, AIC, BIC, and MAPE. Internal and external factors that affect the gold price were chosen for the study, they are historical gold prices, the demand and supply, exports and imports of gold, inflation, interest rates, the exchange rates (USD/INR), gold reserves, GDP, and BSE Sensex. Data is gathered for the period ranging from January 2010 to December 2023. From the analysis, it is evident that the econometric model outperforms traditional models in predicting gold prices.