Gold rose to 4,533.64 USD/t.oz on March 27, 2026, up 3.51% from the previous day. Over the past month, Gold's price has fallen 14.82%, but it is still 46.99% higher than a year ago, 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 March of 2026.

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.

This comprehensive dataset contains 10 years of historical gold futures prices (2016-2026) sourced from Yahoo Finance, along with advanced machine learning predictions extending through December 2026. Perfect for financial analysis, time series forecasting, and machine learning enthusiasts.

Keywords: gold price prediction, time series forecasting, XGBoost, financial analysis, commodity trading, investment analysis, machine learning finance, gold futures, technical analysis, price forecasting

Historical Data Columns:** - Date (index) - Open, High, Low, Close prices (USD) - Volume - Adjusted Close Machine Learning Projects - Time series forecasting - Regression modeling - Feature engineering practice - Model comparison studies

✅ Financial Analysis - Investment strategy backtesting - Risk assessment - Trend analysis - Portfolio optimization

✅ Educational Purposes - Learning technical analysis - Understanding commodity markets - Practicing data visualization - Exploring EDA techniques

Model Performance

🤖 XGBoost Regression Model: - R² Score: 0.99+ (99%+ variance explained) - MAPE: <1% (prediction error) - RMSE: ~$15-20 (typical error range) - Training Set: 2,000+ samples - Test Set: 500+ samples

Data Source & Citation

Primary Source: Yahoo Finance (yfinance Python API) Ticker Symbol: GC=F (Gold Futures - COMEX) API: https://pypi.org/project/yfinance/ License: Educational and research purposes

Discover the booming precious metal trading platform market! This in-depth analysis reveals a $15 billion market in 2025, projected to grow at an 8% CAGR through 2033. Learn about key drivers, trends, and top companies shaping this dynamic sector. Explore market segmentation, regional insights, and future opportunities.

CN: Commodity Trading Market over 100 M Yuan: Operating Area: Gold, Jeweller, Jade Market data was reported at 1,864.003 sq m th in 2023. This records a decrease from the previous number of 1,911.003 sq m th for 2022. CN: Commodity Trading Market over 100 M Yuan: Operating Area: Gold, Jeweller, Jade Market data is updated yearly, averaging 1,904.001 sq m th from Dec 2008 (Median) to 2023, with 16 observations. The data reached an all-time high of 2,556.300 sq m th in 2017 and a record low of 497.300 sq m th in 2008. CN: Commodity Trading Market over 100 M Yuan: Operating Area: Gold, Jeweller, Jade Market data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Wholesale, Retail and Catering Sector – Table CN.RJA: Commodity Trading Market over 100 Million Yuan: Operating Area.

Historical AI model predictions and analysis for Gold (spot) stock across multiple timeframes and confidence levels

As of December 1st, 2025, gold futures contracts to be settled in June 2031 were trading on U.S. markets at around ***** U.S. dollars per troy ounce. This is above the price of ******* U.S. dollars per troy ounce for contracts to be settled in December 2025, indicating that gold traders expect the price of gold to rise over the next five years. Gold futures are contracts that effectively lock in a price for an amount of gold to be purchased at a time in the future, which can then be traded on markets. Futures markets therefore provide an indicator of how investors think a commodities market will develop in the future.

CN: Commodity Trading Market over 100 M Yuan: Number of Booth: Gold, Jeweller, Jade Market data was reported at 17,926.000 Unit in 2023. This records an increase from the previous number of 15,622.000 Unit for 2022. CN: Commodity Trading Market over 100 M Yuan: Number of Booth: Gold, Jeweller, Jade Market data is updated yearly, averaging 16,182.000 Unit from Dec 2008 (Median) to 2023, with 16 observations. The data reached an all-time high of 22,017.000 Unit in 2019 and a record low of 6,688.000 Unit in 2008. CN: Commodity Trading Market over 100 M Yuan: Number of Booth: Gold, Jeweller, Jade Market data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Wholesale, Retail and Catering Sector – Table CN.RJA: Commodity Trading Market over 100 Million Yuan: Number of Booth.

View weekly updates and historical trends for COMEX Gold Futures Total Reportable Long Positions. Source: US Commodity Futures Trading Commission. Track e…

View weekly updates and historical trends for COMEX Gold Combined Open Interest. Source: US Commodity Futures Trading Commission. Track economic data with…

Gold prices in , February, 2026 For that commodity indicator, we provide data from January 1960 to February 2026. The average value during that period was 635.09 USD per troy ounce with a minimum of 34.94 USD per troy ounce in January 1970 and a maximum of 5019.97 USD per troy ounce in February 2026. | TheGlobalEconomy.com

View weekly updates and historical trends for COMEX Gold Futures Swap Dealers Long Positions. Source: US Commodity Futures Trading Commission. Track econo…

CN: Commodity Trading Market over 100 M Yuan: Number of Booth by Category: Gold, Silver and Jewellery data was reported at 27,519.000 Unit in 2023. This records an increase from the previous number of 25,194.000 Unit for 2022. CN: Commodity Trading Market over 100 M Yuan: Number of Booth by Category: Gold, Silver and Jewellery data is updated yearly, averaging 24,582.500 Unit from Dec 2008 (Median) to 2023, with 16 observations. The data reached an all-time high of 33,707.000 Unit in 2019 and a record low of 9,428.000 Unit in 2008. CN: Commodity Trading Market over 100 M Yuan: Number of Booth by Category: Gold, Silver and Jewellery data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Wholesale, Retail and Catering Sector – Table CN.RJA: Commodity Trading Market over 100 Million Yuan: Number of Booth by Category.

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

This dataset provides a comprehensive view of the financial landscape by combining three distinct asset classes: Cryptocurrency (Bitcoin), Commodities (Gold), and Macroeconomic Indicators (US Federal Reserve Data). It is designed for researchers, traders, and data scientists interested in analyzing correlations between digital assets, traditional safe-havens, and fundamental economic drivers.

The combination of high-frequency price data (1-minute intervals) and major economic indicators allows for deep learning model training, multi-timeframe analysis, and robust backtesting strategies.

Content Overview

The dataset consists of three primary components:

1. Bitcoin Historical Price (BTC/USDT)

   • Source: KuCoin Exchange.
   • Collection Method: Extracted using the ccxt Python library.
   • Timeframe: 1-minute (1m) granularity.
   • Period: January 1, 2018 – Present.
   • Columns: Timestamp, Open, High, Low, Close, Volume.

2. Gold Historical Price (XAU/USD)

   • Source: Dukascopy Bank.
   • Collection Method: Extracted using the third-party software Tickstory.
   • Timeframe: 1-minute (1m) granularity.
   • Period: January 1, 2017 – Present.
   • Columns: Timestamp, Open, High, Low, Close, Volume.

3. US Macroeconomic Indicators (The Fed Data)

   • Source: Federal Reserve Economic Data (FRED).
   • Collection Method: Extracted using the FRED API (Python).
   • Timeframe: Monthly.

Methodology

Crypto Data: Data was programmatically fetched from the KuCoin API using ccxt to ensure raw market accuracy without aggregation bias.

Commodity Data: High-quality tick data was sourced from Dukascopy via Tickstory and converted to 1-minute OHLCV bars.

Macro Data: Official economic figures were pulled directly from the St. Louis Fed database using the FRED library to align with major economic announcements.

Inspiration & Use Cases

Multimodal Time-Series Forecasting: Build LSTM or Transformer models that utilize both price action and economic fundamentals.

Correlation Analysis: Analyze how Bitcoin reacts to US Inflation (CPI) data or Interest Rate decisions compared to Gold.

Safe-Haven Studies: Investigate if Bitcoin behaves like Gold (Digital Gold) during economic downturns.

Algorithmic Trading: Backtest strategies that switch between risk-on (Crypto) and risk-off (Gold) assets based on Fed data.

Acknowledgements

KuCoin for the cryptocurrency market data

Dukascopy & Tickstory for the commodities data.

Federal Reserve Bank of St. Louis for the FRED economic data.

About the Author

This dataset was curated by Akmal Rizal, an undergraduate Data Science student. It is intended to support the community in building robust financial forecasting models using diverse data sources

View weekly updates and historical trends for COMEX Gold Futures Managed Money Spread Positions. Source: US Commodity Futures Trading Commission. Track ec…

United States - Producer Price Index by Commodity: Metals and Metal Products: Gold Ores was 444.72200 Index Jun 1985=100 in December of 2021, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Commodity: Metals and Metal Products: Gold Ores reached a record high of 515.90000 in August of 2020 and a record low of 78.40000 in April of 2001. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Commodity: Metals and Metal Products: Gold Ores - last updated from the United States Federal Reserve on March of 2026.

View weekly updates and historical trends for COMEX Gold Combined Managed Money Short Positions. Source: US Commodity Futures Trading Commission. Track ec…

CN: Commodity Trading Market over 100 M Yuan: Turnover: Wholesale: Gold, Jeweller, Jade Market data was reported at 82.605 RMB bn in 2023. This records a decrease from the previous number of 91.436 RMB bn for 2022. CN: Commodity Trading Market over 100 M Yuan: Turnover: Wholesale: Gold, Jeweller, Jade Market data is updated yearly, averaging 45.996 RMB bn from Dec 2008 (Median) to 2023, with 16 observations. The data reached an all-time high of 91.436 RMB bn in 2022 and a record low of 19.970 RMB bn in 2008. CN: Commodity Trading Market over 100 M Yuan: Turnover: Wholesale: Gold, Jeweller, Jade Market data remains active status in CEIC and is reported by National Bureau of Statistics. The data is categorized under China Premium Database’s Wholesale, Retail and Catering Sector – Table CN.RJA: Commodity Trading Market over 100 Million Yuan: Turnover: Wholesale.

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.