Modeling the Forecast of Gold Price Fluctuations over Short-Term, Medium-Term and Long-Term Periods
محورهای موضوعی : Agriculture Marketing and CommercializationMahdieh Tavassoli 1 , مهناز ربیعی 2 , Kiamars Fathi 3
1 - Ph.D. student, Department of Information Technology Management, South Tehran Branch, Islamic Azad University, Tehran, Iran,
2 - معاون پژوهشی دانشگاه آزاد واحد الکترونیکی
3 - Islamic Azad University South Branch
کلید واژه: Gold price, macro factors, micro factors, GARCH, Bayesian model averaging.,
چکیده مقاله :
In the modern financial market, gold serves as a vital financial and monetary product, making it essential to examine its price fluctuations. In this regard, the present study aims to model the forecast of gold price fluctuations over short-term, medium-term, and long-term periods. The present study is applied exploratory research. Monthly data from 2010 to 2022 were utilized to estimate the model, evaluating 35 factors influencing gold price fluctuations. Three modeling approaches were employed: Bayesian Model Averaging (BMA), Principal Component Analysis (PCA), and Time-Varying Parameter (TVP) modeling to forecast gold price fluctuations over different periods. The BMA model exhibited the highest accuracy among the tested models. The findings identified 12 key variables impacting gold price fluctuations. Additionally, it was noted that both internal and external factors positively affect these fluctuations over time, with external factors demonstrating stronger influences. Nonlinear modeling approaches proved to be more accurate than linear ones. The analysis suggests that gold price fluctuations are trending upward over time, and the market will likely experience increased volatility in the future.
In the modern financial market, gold serves as a vital financial and monetary product, making it essential to examine its price fluctuations. In this regard, the present study aims to model the forecast of gold price fluctuations over short-term, medium-term, and long-term periods. The present study is applied exploratory research. Monthly data from 2010 to 2022 were utilized to estimate the model, evaluating 35 factors influencing gold price fluctuations. Three modeling approaches were employed: Bayesian Model Averaging (BMA), Principal Component Analysis (PCA), and Time-Varying Parameter (TVP) modeling to forecast gold price fluctuations over different periods. The BMA model exhibited the highest accuracy among the tested models. The findings identified 12 key variables impacting gold price fluctuations. Additionally, it was noted that both internal and external factors positively affect these fluctuations over time, with external factors demonstrating stronger influences. Nonlinear modeling approaches proved to be more accurate than linear ones. The analysis suggests that gold price fluctuations are trending upward over time, and the market will likely experience increased volatility in the future.
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