Gold fell to 4,199.97 USD/t.oz on December 2, 2025, down 0.75% from the previous day. Over the past month, Gold's price has risen 4.93%, and is up 58.92% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Gold - values, historical data, forecasts and news - updated on December of 2025.

Gold prices in , October, 2025 For that commodity indicator, we provide data from January 1960 to October 2025. The average value during that period was 615.3 USD per troy ounce with a minimum of 34.94 USD per troy ounce in January 1970 and a maximum of 4058.33 USD per troy ounce in October 2025. | TheGlobalEconomy.com

This dataset contains historical price data for seven essential metals traded on the Multi Commodity Exchange (MCX) India: Gold, Silver, Lead, Zinc, Copper, Nickel, and Aluminum. The data is meticulously collected to support prediction models, trend analysis, and statistical exploration of metal price movements.

The dataset includes: - Daily price data for 7 metals - Open price, high/low values, and closing prices - Data across multiple periods, useful for preliminary exploration, model training, and analysis

Description for each column in the dataset: 1. Date: The date on which the market data was recorded (format: DD-MM-YYYY). 2. Price: The closing price of Copper on the given date, reflecting the last traded price of the day. 3. Open: The opening price of Copper at the start of trading on the given date. 4. High: The highest price Copper reached during the trading day. 5. Low: The lowest price Copper traded at during the day. 6. Vol. (Volume): The total volume of Copper traded on the given day, typically in thousands (K). 7. Change %: The percentage change in the closing price from the previous trading day.

Dataset Card for Sentiment Analysis of Commodity News (Gold)

This is a news dataset for the commodity market which has been manually annotated for 10,000+ news headlines across multiple dimensions into various classes. The dataset has been sampled from a period of 20+ years (2000-2021). The dataset was curated by Ankur Sinha and Tanmay Khandait and is detailed in their paper "Impact of News on the Commodity Market: Dataset and Results." It is currently published by the authors on… See the full description on the dataset page: https://huggingface.co/datasets/SaguaroCapital/sentiment-analysis-in-commodity-market-gold.

Ghana Commodity Price: Gold data was reported at 1,281.100 USD/Fine oz in Jun 2018. This records a decrease from the previous number of 1,303.000 USD/Fine oz for May 2018. Ghana Commodity Price: Gold data is updated monthly, averaging 1,182.900 USD/Fine oz from Dec 2003 (Median) to Jun 2018, with 175 observations. The data reached an all-time high of 1,770.130 USD/Fine oz in Aug 2011 and a record low of 384.730 USD/Fine oz in May 2004. Ghana Commodity Price: Gold data remains active status in CEIC and is reported by Bank of Ghana. The data is categorized under Global Database’s Ghana – Table GH.P001: Commodity Price.

Graph and download economic data for Producer Price Index by Commodity: Metals and Metal Products: Gold Ores (WPU10210501) from Jun 1985 to Dec 2021 about ore, gold, metals, commodities, PPI, inflation, price index, indexes, price, and USA.

Content

Daily gold prices (2014-01-01 to 2025-01-06)

Acknowledgements

Raw Data Source: MCX Market This data frame is pre-processed to time series analysis and forecasting

Inspiration

Forecast, Predict Prices, Time Series Forecasting

Note

Prices are in INR (Indian Rupee) for 10gm of Gold 24K.

Gold Prices in this dataset makes no guarantee or warranty on the accuracy or completeness of the data provided.

This DataSet includes the real time gold prices(in USD) from 2012 to 2022. Date - Date on which Price is Noted Close - Close Price of the Gold in USD Volume - Sum of buy's and sell's of Gold Commodity open - open price of a Gold on that particular day High - High price of Gold on that particular day Low - Low price of Gold on that particular day

Context

Gold. A precious item with its own duality. In one side, it's a popular investment asset. In another side, it's a commodity. Whether you buy it as an asset or as commodity, the price for gold is always influenced by two things, as similar as other commodities in market: supply and demand. It's not easy to combine many aspects in supply and demand into a single dataset without making it into wall of columns. And also aggregating the data might not easy to do, since the data might not available publicly. But it doesn't mean we can't learn the historical pattern of gold market. At least some gold price historical data are available for public. And we can use that to analyze the market pattern, and, maybe, learn something from them.

Content

This dataset was based on gold price historical data from macrotrends.net. I added one new column, 'Year Range Price', to see how wide the spread of the price annually.

Acknowledgements

The base data for this dataset was retrieved from https://www.macrotrends.net/1333/historical-gold-prices-100-year-chart.

Inspiration

What variable have the biggest correlation with annual Average Closing Price? What information can we see from the graphic? Are there any reasons why the price drop and rise? What happened on those years? Many things can be learn and explore by historical data. Having historical data is like having a kaleidoscope to see the past, learn from them, and use it as information to walk on our future path.

Germany Commodity Price: Precious Metals: Gold data was reported at 4,210.511 USD/Troy oz in 02 Dec 2025. This records a decrease from the previous number of 4,237.295 USD/Troy oz for 01 Dec 2025. Germany Commodity Price: Precious Metals: Gold data is updated daily, averaging 1,408.274 USD/Troy oz from Jan 2013 (Median) to 02 Dec 2025, with 3278 observations. The data reached an all-time high of 4,377.784 USD/Troy oz in 20 Oct 2025 and a record low of 1,050.717 USD/Troy oz in 17 Dec 2015. Germany Commodity Price: Precious Metals: Gold data remains active status in CEIC and is reported by Deutsche Börse Group. The data is categorized under Global Database’s Germany – Table DE.P: Commodity Prices. [COVID-19-IMPACT]

Silver fell to 57.28 USD/t.oz on December 2, 2025, down 1.22% from the previous day. Over the past month, Silver's price has risen 19.11%, and is up 84.81% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Silver - values, historical data, forecasts and news - updated on December of 2025.

Graph and download economic data for Producer Price Index by Commodity: Miscellaneous Products: Jewelry, Gold and Platinum (WPU15940222) from Dec 2011 to Sep 2025 about platinum, jewelry, miscellaneous, gold, commodities, PPI, inflation, price index, indexes, price, and USA.

View monthly updates and historical trends for US One-Year Ahead Commodity Price Change Expectations - Gold. from United States. Source: Federal Reserve B…

Copper rose to 5.19 USD/Lbs on December 2, 2025, up 0.35% from the previous day. Over the past month, Copper's price has risen 3.22%, and is up 25.36% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Copper - values, historical data, forecasts and news - updated on December of 2025.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Philadelphia Gold and Silver Index: The Future of Precious Metals?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Belgium Gold Price Per Kg: EUR data was reported at 115,180.000 EUR in 26 Nov 2025. This records an increase from the previous number of 114,645.000 EUR for 25 Nov 2025. Belgium Gold Price Per Kg: EUR data is updated daily, averaging 34,090.000 EUR from Jan 1999 (Median) to 26 Nov 2025, with 6722 observations. The data reached an all-time high of 118,645.000 EUR in 17 Oct 2025 and a record low of 28,055.000 EUR in 31 Dec 2013. Belgium Gold Price Per Kg: EUR data remains active status in CEIC and is reported by National Bank of Belgium. The data is categorized under World Trend Plus’s Commodity Market – Table BE.P: Gold Price: National Bank of Belgium. [COVID-19-IMPACT]

This Dataset contains Historical Price of Gold in Indian Commodity Market . The data has been collected from https://in.investing.com/commodities/ using web scrapping . The script can be customized to suit the needs (like customizing frequency interval , commodity type etc ) Link to web scrapping script - https://github.com/Pritam3355/web_scrapping/blob/master/stock_price.py

Column contains - Date, Price ,Open , High ,Low ,Volume ,Chg% these columns can be sorted first in the website then use the url in script to download the data according to your need

Context

Historically, gold had been used as a form of currency in various parts of the world including the USA. In present times, precious metals like gold are held with central banks of all countries to guarantee re-payment of foreign debts, and also to control inflation which results in reflecting the financial strength of the country. Recently, emerging world economies, such as China, Russia, and India have been big buyers of gold, whereas the USA, SoUSA, South Africa, and Australia are among the big seller of gold.

Forecasting rise and fall in the daily gold rates can help investors to decide when to buy (or sell) the commodity. But Gold prices are dependent on many factors such as prices of other precious metals, prices of crude oil, stock exchange performance, Bonds prices, currency exchange rates, etc.

The challenge of this project is to accurately predict the future adjusted closing price of Gold ETF across a given period of time in the future. The problem is a regression problem, because the output value which is the adjusted closing price in this project is continuous value.

Content

Data for this study is collected from November 18th 2011 to January 1st 2019 from various sources. The data has 1718 rows in total and 80 columns in total. Data for attributes, such as Oil Price, Standard and Poor’s (S&P) 500 index, Dow Jones Index US Bond rates (10 years), Euro USD exchange rates, prices of precious metals Silver and Platinum and other metals such as Palladium and Rhodium, prices of US Dollar Index, Eldorado Gold Corporation and Gold Miners ETF were gathered.

The dataset has 1718 rows in total and 80 columns in total. Data for attributes, such as Oil Price, Standard and Poor’s (S&P) 500 index, Dow Jones Index US Bond rates (10 years), Euro USD exchange rates, prices of precious metals Silver and Platinum and other metals such as Palladium and Rhodium, prices of US Dollar Index, Eldorado Gold Corporation and Gold Miners ETF were gathered.

The historical data of Gold ETF fetched from Yahoo finance has 7 columns, Date, Open, High, Low, Close, Adjusted Close, and Volume, the difference between Adjusted Close and Close is that the closing price of a stock is the price of that stock at the close of the trading day. Whereas the adjusted closing price takes into account factors such as dividends, stock splits, and new stock offerings to determine a value. So, Adjusted Close is the outcome variable which is the value you have to predict.

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Acknowledgements

The data is collected from Yahoo finance.

Inspiration

Can you predict Gold prices accurately using traditional machine learning algorithms

The Gold – Sample Data dataset captures structured insights into how sentiment, macroeconomic drivers, and market events influence gold prices. Covering multiple themes such as monetary policy, institutional buying, consumer demand, and supply dynamics, the dataset provides a transparent view of narrative flows that act as leading indicators for price direction. For the period 10–17 May 2025, the dataset highlights: Bearish sentiment from U.S. dollar strength and rising mining output. Bullish sentiment from central bank reserve purchases, jewellery demand recovery, and safe-haven flows amid geopolitical tensions. Policy influence with the Federal Reserve’s rate decisions directly impacting gold’s relative attractiveness. Each entry records timestamped events, directional sentiment (up/down), topic classification, and narrative detail, allowing systematic traders and analysts to test correlations between sentiment shifts and subsequent gold price action. This data helps quants and commodity desks integrate structured sentiment into models, evaluate thematic drivers of gold volatility, and identify predictive signals ahead of market moves.

The global precious metal trading platform market is experiencing robust growth, driven by increasing investor interest in gold, silver, platinum, and palladium as safe-haven assets and diversification tools. The market size in 2025 is estimated at $15 billion, exhibiting a Compound Annual Growth Rate (CAGR) of 8% from 2025 to 2033. This growth is fueled by several key factors. Technological advancements, including the rise of mobile trading apps and sophisticated charting tools, are making precious metal trading more accessible to a wider range of investors. Furthermore, the increasing volatility in global financial markets is prompting investors to seek refuge in precious metals, bolstering demand for platforms facilitating their trading. Regulatory changes aiming to improve market transparency and investor protection are also indirectly supporting market expansion. However, challenges remain, including potential regulatory hurdles in specific regions and the inherent risks associated with volatile commodity markets. The market is segmented by platform type (web-based, mobile-based), trading style (spot, futures, options), and investor type (retail, institutional). Key players like GAIN Global Markets Inc., AxiTrader Limited, LMAX Global, IG Group, and CMC Markets are vying for market share through innovation, strategic partnerships, and expansion into new geographic markets. Competition is intense, forcing providers to continuously enhance their offerings and improve customer experience to retain a competitive edge. The forecast period of 2025-2033 presents significant opportunities for expansion, particularly in emerging markets with growing retail investor bases. The continued growth of the precious metal trading platform market is projected to be influenced by several ongoing trends. The increasing adoption of artificial intelligence (AI) and machine learning (ML) for algorithmic trading and risk management is expected to further enhance the efficiency and sophistication of trading platforms. The integration of blockchain technology for improved security and transparency is also gaining traction. However, potential restraints include cybersecurity threats, the need for robust compliance frameworks, and the ongoing evolution of investor preferences which necessitate platform adaptation. The expanding availability of educational resources and improved investor awareness about precious metals trading is expected to positively impact market growth. Furthermore, strategic mergers and acquisitions within the industry are likely to reshape the competitive landscape. Geographic expansion into underpenetrated regions, coupled with the development of tailored products to meet the specific needs of diverse investor segments, will be crucial for achieving sustained growth in the coming years.