This dataset contains the Gold Future prices (GC00: Gold Continuous Contract Futures, USD).

Data has been manually scrapped from MarketWatch website, and the dataset contains the data since Apr 24, 2009 to Feb 8, 2024 inclusive.

This dataset is good for those who would like to master his/her skills in Time Series Analytics (EDA, modelling etc.).

The cover image for this dataset is coutesy to Alex Grey (https://unsplash.com/photos/brown-dried-leaves-on-ground-yoWkkoUbG4E)

As of June 25, 2024, gold futures contracts to be settled in June 2030 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 June 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.

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.

Context

Gold is one of the world's most closely watched commodities, serving as a key indicator of economic health, a hedge against inflation, and a cornerstone of financial markets. Access to clean, reliable, and long-term historical data is essential for analysts, investors, and data scientists looking to understand its behavior, forecast future trends, and build robust financial models.

This dataset provides a comprehensive and daily-updated record of gold prices, specifically sourced from the Gold Futures (GC=F) market, which is the standard for long-term historical analysis.

Content

This dataset contains daily price information for Gold Futures (GC=F) in a clean, tabular format. Each row represents a single trading day and includes the following columns:

Date: The date of the trading session (YYYY-MM-DD).

Open: The price at which gold first traded for the day in USD.

High: The highest price reached during the trading day in USD.

Low: The lowest price reached during the trading day in USD.

Close: The closing price at the end of the trading day in USD.

Volume: The total number of futures contracts traded during the day.

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 statistic depicts the average annual prices for gold from 2014 to 2024 with a forecast until 2026. In 2024, the average price for gold stood at 2,388 U.S. dollars per troy ounce, the highest value recorded throughout the period considered. In 2026, the average gold price is expected to increase, reaching 3,200 U.S. dollars per troy ounce.

This dataset contains monthly gold prices from 1950-01 to 2020-07. Gold is a precious metal that has been used as a store of value and a medium of exchange for thousands of years, and is still widely traded in financial markets today. The gold price is influenced by a variety of factors, including global economic conditions, geopolitical events, and supply and demand dynamics.

The dataset includes a total of 847 data points, with each row representing the gold price for a particular month. The data was sourced from the World Gold Council and is in USD per troy ounce.

This dataset can be used for a variety of applications, including financial analysis, time series forecasting, and machine learning modeling. Potential use cases include predicting future gold prices based on historical trends, analyzing the relationship between gold prices and other economic indicators, and developing trading strategies for gold-related assets.

Data Source: World Gold Council

The average monthly prices for gold increased worldwide between January 2014 and May 2025, although with some fluctuations. In January 2014, the average monthly price for gold worldwide stood at ******** nominal U.S. dollars per troy ounce. Significant jumps in the gold prices were observed, especially in the periods of uncertainty, as the investors tend to see gold as a safe investment option. For instance, the Corona pandemic acted as a shock to the economy, resulting in substantial increases in gold prices in 2020. As of May 2025, gold valued at ******** U.S. dollars per ounce, the highest value reported during this period.

This data is the month-end data of the time series from January 2009 to March 2023 for four commodities such as gold soybean crude oil and natural gas. These time series data can be used to estimate the market's short-term interest rate along with the Vasicek model and joint radiation term structure model., , , # Short-term interest rate estimates based on futures markets

Abstract: This data is the month-end data of the time series from January 2009 to March 2023 for four commodities such as gold soybean crude oil and natural gas. These time series data can be used to estimate the market short-term interest rate together with the Vasicek model and the joint radiation term structure model

Usage: The data in Table 1 and Table 2 can be read into the established interest rate estimation model code using python to estimate the short-term interest rate

Data structure: month-end time series data; The xlsx tables mainly include Table 1 and Table 2

Source: Bloomberg Data Terminal

Specific variable definition:

• The gold futures price is the futures price data from the end of January 2009 to the end of March 2023, in ounces per dollar
• Soybean futures prices are futures price data from the end of January 2009 to the end of March 2023, in tons per dollar
• Natural gas futures price...

Index Time Series for MiraeAsset TIGER Gold Futures ETF(H). The frequency of the observation is daily. Moving average series are also typically included.

Content

Gold Futures Historical Data Periode data : Nov 01, 2017 - Oct 16,2020 Source :https://www.investing.com/commodities/gold-historical-data

Disclaimer: According to Fusion Media (https://www.investing.com/commodities/gold-historical-data) that the data contained in their website is not necessarily real-time nor accurate. All CFDs (stocks, indexes, futures), cryptocurrencies, and Forex prices are not provided by exchanges but rather by market makers, and so prices may not be accurate and may differ from the actual market price, meaning prices are indicative and not appropriate for trading purposes.

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]

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.

Gold Price Outlook: S&P GSCI Gold index Faces Uncertain Future

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

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.

China Settlement Price: Shanghai Future Exchange: Gold: 5th Month data was reported at 954.140 RMB/g in Nov 2025. This records an increase from the previous number of 921.900 RMB/g for Oct 2025. China Settlement Price: Shanghai Future Exchange: Gold: 5th Month data is updated monthly, averaging 269.800 RMB/g from Jan 2008 (Median) to Nov 2025, with 215 observations. The data reached an all-time high of 954.140 RMB/g in Nov 2025 and a record low of 159.600 RMB/g in Oct 2008. China Settlement Price: Shanghai Future Exchange: Gold: 5th Month data remains active status in CEIC and is reported by Shanghai Futures Exchange. The data is categorized under China Premium Database’s Financial Market – Table CN.ZB: Shanghai Futures Exchange: Commodity Futures: Settlement Price.

Index Time Series for Samsung KODEX Gold Futures Special Asset ETF Hedged. The frequency of the observation is daily. Moving average series are also typically included.

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.

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.

Gold–Silver Pair Trading Dataset and Visualization

Author: Vineet Kumar Mittal Version: 1.0 Date: November 2025 DOI: https://doi.org/10.5281/zenodo.17537028

Overview

This repository contains the full dataset and visual analytics used in the study: "Gold–Silver Pair Trading: Mean Reversion Strategy Using Machine Learning."

It includes: - Historical gold and silver futures data (raw) - Processed dataset with spreads, ratios, and Z-scores - Key analysis charts (hedge ratio, spread, equity curve, etc.) - Reproducibility and licensing information

Contents

1. Main Analytical Dataset

File: gold_silver_live_panel.csv
Description:
Processed data containing gold/silver prices, ratio, spread, rolling statistics, and Z-scores used for the study's analysis and backtesting.

Column Definitions: See below for detailed description of each field included in gold_silver_live_panel.csv.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F30232042%2F4b0cf366a892c352a775411296a97f02%2FScreenshot%202025-11-08%20083140.jpg?generation=1762608723135200&alt=media" alt="">

2. Raw Historical Data

Files: - Gold Futures Historical Data_2015_2025.csv
- Silver Futures Historical Data_2015_2025.csv

Description:
Raw daily closing prices used to compute the ratio, spread, and other derived features.
Data sourced from Investing.com (continuous Gold and Silver Futures contracts).

Covers 2015–2025, daily frequency (excluding weekends and market holidays).

3. Visualization Outputs (Figures)

Please use below DOI to see all the figures and data.

DOI: https://doi.org/10.5281/zenodo.17537028

4. Citation

If you use this dataset, please cite:

Mittal, V. K. (2025). Gold Silver Pair Trading - Mean Reversion Strategy Using Machine Learning (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.17537028

5. License

Creative Commons Attribution 4.0 International (CC BY 4.0)

You are free to use, distribute, and build upon this dataset for academic and non-commercial research purposes, provided proper attribution is given.

6. Contact

For queries, collaborations, or extended analysis: Vineet Kumar Mittal

Index Time Series for DB Gold Double Long ETN. The frequency of the observation is daily. Moving average series are also typically included. The index is intended to reflect changes in the market value of certain gold futures contracts and is comprised of a single unfunded gold futures contract.