The price of gold per troy ounce increased considerably between 1990 and 2024, despite some fluctuations. A troy ounce is the international common unit of weight used for precious metals and is approximately 31.3 grams. At the end of 2024, a troy ounce of gold cost 2,386.2 U.S. dollars. Price of – additional information In 2000 the price of gold was at its lowest since 1990, with a troy ounce of gold costing 274.5 U.S. dollars in that year. Since then gold prices have been rising and after the economic crisis of 2008 the price of gold rose at higher rates than ever before as the market began to see gold as an increasingly good investment. History has shown that time and time again, gold is seen as a good investment in times of uncertainty because it can or is thought to function as a good store of value against a declining currency as well as providing protection against inflation. However unlike other commodities, once gold is mined it does not get used up like other commodities (for example, such as gasoline). So while gold may be a good investment at times, the supply demand argument does not apply to gold. Nonetheless, the demand for gold has been mostly consistent.

Banking and stock markets consider gold to be an important component of their economic and financial status. There are various factors that influence the gold price trend and its fluctuations. Accurate and reliable prediction of the gold price is an essential part of financial and portfolio management. Moreover, it could provide insights about potential buy and sell points in order to prevent financial damages and reduce the risk of investment. In this paper, different architectures of deep neural network (DNN) have been proposed based on long short-term memory (LSTM) and convolutional-based neural networks (CNN) as a hybrid model, along with automatic parameter tuning to increase the accuracy, coefficient of determination, of the forecasting results. An illustrative dataset from the closing gold prices for 44 years, from 1978 to 2021, is provided to demonstrate the effectiveness and feasibility of this method. The grid search technique finds the optimal set of DNNs’ parameters. Furthermore, to assess the efficiency of DNN models, three statistical indices of RMSE, RMAE, and coefficient of determination (R2), were calculated for the test set. Results indicate that the proposed hybrid model (CNN-Bi-LSTM) outperforms other models in total bias, capturing extreme values and obtaining promising results. In this model, CNN is used to extract features of input dataset. Furthermore, Bi-LSTM uses CNN’s outputs to predict the daily closing gold price.

United States - Producer Price Index by Industry: Jewelry and Silverware Manufacturing: Jewelry, Gold and Platinum was 302.26900 Index Dec 1985=100 in February of 2025, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Industry: Jewelry and Silverware Manufacturing: Jewelry, Gold and Platinum reached a record high of 302.26900 in February of 2025 and a record low of 58.70000 in December of 1978. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Industry: Jewelry and Silverware Manufacturing: Jewelry, Gold and Platinum - last updated from the United States Federal Reserve on March of 2025.

Banking and stock markets consider gold to be an important component of their economic and financial status. There are various factors that influence the gold price trend and its fluctuations. Accurate and reliable prediction of the gold price is an essential part of financial and portfolio management. Moreover, it could provide insights about potential buy and sell points in order to prevent financial damages and reduce the risk of investment. In this paper, different architectures of deep neural network (DNN) have been proposed based on long short-term memory (LSTM) and convolutional-based neural networks (CNN) as a hybrid model, along with automatic parameter tuning to increase the accuracy, coefficient of determination, of the forecasting results. An illustrative dataset from the closing gold prices for 44 years, from 1978 to 2021, is provided to demonstrate the effectiveness and feasibility of this method. The grid search technique finds the optimal set of DNNs’ parameters. Furthermore, to assess the efficiency of DNN models, three statistical indices of RMSE, RMAE, and coefficient of determination (R2), were calculated for the test set. Results indicate that the proposed hybrid model (CNN-Bi-LSTM) outperforms other models in total bias, capturing extreme values and obtaining promising results. In this model, CNN is used to extract features of input dataset. Furthermore, Bi-LSTM uses CNN’s outputs to predict the daily closing gold price.

Gabon GA: International Liquidity: Total Reserves: Including Gold at Market Price data was reported at 848.419 USD mn in Mar 2018. This records a decrease from the previous number of 965.054 USD mn for Dec 2017. Gabon GA: International Liquidity: Total Reserves: Including Gold at Market Price data is updated quarterly, averaging 146.069 USD mn from Mar 1965 (Median) to Mar 2018, with 213 observations. The data reached an all-time high of 3.004 USD bn in Dec 2013 and a record low of -34.515 USD mn in Mar 1978. Gabon GA: International Liquidity: Total Reserves: Including Gold at Market Price data remains active status in CEIC and is reported by International Monetary Fund. The data is categorized under Global Database’s Gabon – Table GA.IMF.IFS: International Liquidity: Quarterly.