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Interactive chart of historical data for real (inflation-adjusted) gold prices per ounce back to 1915. The series is deflated using the headline Consumer Price Index (CPI) with the most recent month as the base. The current month is updated on an hourly basis with today's latest value.
Monthly gold prices in USD since 1833 (sourced from the World Gold Council). The data is derived from historical records compiled by Timothy Green and supplemented by data provided by the World Bank...
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Gold, the yellow shiny metal, has been the fancy of mankind since ages. From making jewelry to being used as an investment, gold covers a huge spectrum of use cases. Gold, like other metals, is also traded on the commodities indexes across the world. For better understanding time series in a real-world scenario, we will work with gold prices collected historically and predict its future value.
Metals such as gold have been traded for years across the world. Prices of gold are determined and used for trading the metal on commodity exchanges on a daily basis using a variety of factors. Using this daily price-level information only, our task is to predict future price of gold.
For the purpose of implementing time series forecasting technique , i will utilize gold pricing from Quandl. Quandl is a platform for financial, economic, and alternative datasets. To access publicly shared datasets on Quandl, we can use the pandas-datareader library as well as quandl (library from Quandl itself). The following snippet shows a quick one-liner to get your hands on gold pricing information since 1970s.
import quandl gold_df = quandl.get("BUNDESBANK/BBK01_WT5511")
The time series is univariate with date and time feature
-Start with Fundamentals: TSA & Box-Jenkins Methods
This notebook is an overview of TSA and traditional methods
For this dataset and tasks, i will depend upon Quandl. The premier source for financial, economic, and alternative datasets, serving investment professionals. Quandl’s platform is used by over 400,000 people, including analysts from the world’s top hedge funds, asset managers and investment banks.
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In 2024, one troy ounce of gold had an annual average price of 2,388.98 U.S. dollars. Gold pricing determinants Gold is a metal that is considered malleable, ductile, and is known for its bright lustrous yellow color. This transition metal is highly valued as a precious metal for its use in coins, jewelry, and in investments. Gold was also once used as a standard for monetary policies between different countries. The price of gold is determined by daily fixings where participants agree to buy or sell at a set price or to maintain the price through supply and demand control. For gold, companies like Barclays Capital, Scotia-Mocatta, Sociétè Générale, HSBC, and Deutsche Bank are members in gold fixing at the London Bullion Market Association.
Vietnam gold price is daily data, collected from 01/01/2017 to 31/12/2021. However, the macro variables are monthly data. The monthly Vietnam gold price data are averaged of the days of the month and compiled from Sai Gon Joint Stock Commercial Bank (SCB). Deposit interest rate data are taken from the website of the International Monetary Fund (IMF). World gold price is taken from the average monthly price, data is taken from World Gold Council. The average interbank exchange rate between Vietnam Dong and US Dollar (USD/VND) data are averaged over the days of the month. Data of Vietnamese consumer price index by month is obtained from the website of the central bank of Vietnam and the General Statistics Office of Vietnam. Dummy variables have a value of 1 when it coincides with the epidemic wave and 0 when it is not.
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Historical daily prices of gold and silver since 1962 to now. Price per ounce in USD.
Data obtained from LBMA
You try different things on this dataset:
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Monthly gold prices (USD) in London from Bundesbank.
General: 1 ounce of fine gold = 31.1034768g. Method of calculation:
License: PDDL (Source indicates no restrictions on data).
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Accurate prediction of gold prices is crucial for investment decision-making and national risk management. The time series data of gold prices exhibits random fluctuations, non-linear characteristics, and high volatility, making prediction extremely challenging. Various methods, from classical statistics to machine learning techniques like Random Forests, Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN), have achieved high accuracy, but they also have inherent limitations. To address these issues, a model that combines Temporal Convolutional Networks (TCN) with Query (Q) and Keys (K) attention mechanisms (TCN-QV) is proposed to enhance the accuracy of gold price predictions. The model begins by employing stacked dilated causal convolution layers within the TCN framework to effectively extract temporal features from the sequence data. Subsequently, an attention mechanism is introduced to enable adaptive weight distribution according to the information features. Finally, the predicted results are generated through a dense layer. This method is used to predict the time series data of gold prices in Shanghai. The optimized model demonstrates a substantial improvement in Mean Absolute Error (MAE) compared to the baseline model, achieving reductions of approximately 5.47% in the least favorable case and up to 33.69% in the most favorable scenario across four experimental datasets. Additionally, the model is tested across different time steps and shows satisfactory performance in long sequence predictions. To validate the necessity of the model components, this paper conducts ablation experiments to confirm the significance of each segment.
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Time series of major commodity prices and indices including iron, cooper, wheat, gold, oil. Data comes from the International Monetary Fund (IMF).
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Data
Dataset contains Monthly prices for 53 commodities and 10 indexes, starting from 1980 to 2016, Last updated on march 17, 2016. The reference year for indexes are 2005 (meaning the value of indexes are 100 and all other values are relative to that year).
License
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For more information please visit: Copyright and Usage.
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Vietnam Gold Price Index: 1995=100 data was reported at 92.700 1995=100 in Jun 2001. This records an increase from the previous number of 91.900 1995=100 for May 2001. Vietnam Gold Price Index: 1995=100 data is updated monthly, averaging 94.350 1995=100 from Jan 1998 (Median) to Jun 2001, with 42 observations. The data reached an all-time high of 96.100 1995=100 in Mar 2000 and a record low of 86.800 1995=100 in Sep 1999. Vietnam Gold Price Index: 1995=100 data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.T029:Table VN.I029: Gold Price Index. Rebased from 1995p to 2000p. Replacement Series ID: 44230601.
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Vietnam Gold Price Index: 2005=100: HCMC data was reported at 267.770 2005=100 in Oct 2009. This records an increase from the previous number of 254.950 2005=100 for Sep 2009. Vietnam Gold Price Index: 2005=100: HCMC data is updated monthly, averaging 197.810 2005=100 from May 2006 (Median) to Oct 2009, with 41 observations. The data reached an all-time high of 267.770 2005=100 in Oct 2009 and a record low of 139.380 2005=100 in Oct 2006. Vietnam Gold Price Index: 2005=100: HCMC data remains active status in CEIC and is reported by Ho Chi Minh City Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.T029:Table VN.I029: Gold Price Index. Rebased from 2005=100 to 2009=100. Replacement series ID: 261395401
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Vietnam Gold Price Index: 2005=100 data was reported at 417.040 2005=100 in Aug 2013. This records an increase from the previous number of 415.710 2005=100 for Jul 2013. Vietnam Gold Price Index: 2005=100 data is updated monthly, averaging 306.700 2005=100 from May 2006 (Median) to Aug 2013, with 87 observations. The data reached an all-time high of 547.110 2005=100 in Sep 2011 and a record low of 137.400 2005=100 in Oct 2006. Vietnam Gold Price Index: 2005=100 data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.T029:Table VN.I029: Gold Price Index. Rebased from 2005=100 to 2009=100. Replacement series ID: 228445202
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
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Accurate prediction of gold prices is crucial for investment decision-making and national risk management. The time series data of gold prices exhibits random fluctuations, non-linear characteristics, and high volatility, making prediction extremely challenging. Various methods, from classical statistics to machine learning techniques like Random Forests, Convolutional Neural Networks (CNN), and Recurrent Neural Networks (RNN), have achieved high accuracy, but they also have inherent limitations. To address these issues, a model that combines Temporal Convolutional Networks (TCN) with Query (Q) and Keys (K) attention mechanisms (TCN-QV) is proposed to enhance the accuracy of gold price predictions. The model begins by employing stacked dilated causal convolution layers within the TCN framework to effectively extract temporal features from the sequence data. Subsequently, an attention mechanism is introduced to enable adaptive weight distribution according to the information features. Finally, the predicted results are generated through a dense layer. This method is used to predict the time series data of gold prices in Shanghai. The optimized model demonstrates a substantial improvement in Mean Absolute Error (MAE) compared to the baseline model, achieving reductions of approximately 5.47% in the least favorable case and up to 33.69% in the most favorable scenario across four experimental datasets. Additionally, the model is tested across different time steps and shows satisfactory performance in long sequence predictions. To validate the necessity of the model components, this paper conducts ablation experiments to confirm the significance of each segment.
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Experimental results of different time steps in Au(T+D).
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Long term dataset of daily platinum prices back to 1985. The price shown is in U.S. Dollars per troy ounce.
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Vietnam Gold Price Index: YoY: HCMC: 2009=100 data was reported at -5.840 % in Dec 2015. This records a decrease from the previous number of -4.900 % for Nov 2015. Vietnam Gold Price Index: YoY: HCMC: 2009=100 data is updated monthly, averaging 2.940 % from Nov 2009 (Median) to Dec 2015, with 74 observations. The data reached an all-time high of 66.450 % in Dec 2009 and a record low of -24.220 % in Dec 2013. Vietnam Gold Price Index: YoY: HCMC: 2009=100 data remains active status in CEIC and is reported by Ho Chi Minh City Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.I030: Gold Price Index: MoM & YoY Growth. Rebased from 2009p to 2014p. Replacement Series ID: 375313327.
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Long term historical dataset of daily COMEX copper prices back to 1971. The price shown is in U.S. Dollars per pound.
SPDR Gold Shares (GLD) This fund buys gold bullion. The only time it sells gold is to pay expenses and honor redemptions. Because of the ownership of bullion, this fund is extremely sensitive to the price of gold and will follow gold price trends closely.
One upside to owning gold bars is that no one can loan or borrow them. Another upside is that each share of this fund represents more gold than shares in other funds that do not buy physical gold. However, the downside is taxes. The Internal Revenue Service (IRS) considers gold a collectible, and taxes on long-term gains are high. (For more, see: The Most Affordable Way to Buy Gold: Physical Gold or ETFs?)
Fund overview: CategoryCommodities Precious Metals Fund familySPDR State Street Global Advisors
Yahoo Finance
Dataset will be helpful for people who are looking to start playing the Time Series Analysis. What always got my attention was, when Dollar goes down DowJones and Nasdaq goes up and vice-versa. Can this dataset be used for creating a Causal Model?
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Gold Price Index: MoM: 2009=100 data was reported at -2.800 % in Dec 2015. This records a decrease from the previous number of -0.612 % for Nov 2015. Gold Price Index: MoM: 2009=100 data is updated monthly, averaging -0.320 % from Nov 2009 (Median) to Dec 2015, with 74 observations. The data reached an all-time high of 13.140 % in Sep 2011 and a record low of -6.280 % in Jul 2013. Gold Price Index: MoM: 2009=100 data remains active status in CEIC and is reported by General Statistics Office. The data is categorized under Global Database’s Vietnam – Table VN.T030:Table VN.I030: Gold Price Index: MoM & YoY Growth. Rebased from 2009p to 2014p. Replacement Series ID: 373679557.
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Lithium traded flat at 60,200 CNY/T on June 6, 2025. Over the past month, Lithium's price has fallen 9.68%, and is down 40.69% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Lithium - values, historical data, forecasts and news - updated on June of 2025.
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Interactive chart of historical data for real (inflation-adjusted) gold prices per ounce back to 1915. The series is deflated using the headline Consumer Price Index (CPI) with the most recent month as the base. The current month is updated on an hourly basis with today's latest value.