Gold rose to 3,320.86 USD/t.oz on July 1, 2025, up 0.53% from the previous day. Over the past month, Gold's price has fallen 1.80%, but it is still 42.51% 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 July of 2025.

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 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.

What happens to gold if CPI increases?

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

The average gold price increased by 1.7% to $1800 per troy ounce in 2021. This year, it was forecast to ease, but rising political uncertainty may reverse the forecast.

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 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.

Machine Learning Models for Gold Price Prediction

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

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.

The size of the Gold Market was valued at USD 3.2 Trillion in 2023 and is projected to reach USD 4.5 Trillion by 2032, with an expected CAGR of 7.38% during the forecast period. It is one of the crucial financial assets with a liquid market, intrinsic value, and diversified uses in jewelry, electronics, and for investment purposes. Gold includes both the physical bullion and ETF markets. Mining and refining technological innovations enhance efficiency and sustainability.Gold provides economic stability and security of investments since it is durable, widely accepted, and one that diversifies portfolios. Hence, gold holds a very significant place both in consumer markets and financial systems through its support for industries ranging from luxury goods to technology. Recent developments include: March 2023: Pan American Silver Corporation acquired all the issued and outstanding common shares of Yamana Gold Inc., as part of the arrangement, which includes its mines and increased the geographical operations of the company in Latin America., February 2023: Barrick Gold, the world's second-biggest gold producer, announced a 10% increase in attributable proved and probable gold mineral reserves to 76 million ounces net of depletion in 2022 while maintaining current reserves.. Key drivers for this market are: Demand for Gold in the form of Jewelry and Long-term Savings, Increasing Consumption in High-End Electronics Applications; Other Drivers. Potential restraints include: Declining Ore Grades and Other Technical Challenges, Other Restraints. Notable trends are: Jewelry Segment to Dominate the Demand.

Gold prices have surged past $3,300, driven by US-China trade tensions, central bank purchases, and anticipated interest rate cuts, setting new records in the market.

Gold Bullion Market Outlook

According to our latest research, the global gold bullion market size reached USD 248.5 billion in 2024, and it is expected to grow at a CAGR of 4.7% during the forecast period, reaching approximately USD 373.4 billion by 2033. This healthy growth trajectory is primarily attributed to the increasing demand for safe-haven assets amid global economic uncertainties, rising geopolitical tensions, and a persistent appetite for portfolio diversification among both institutional and individual investors. The gold bullion market continues to benefit from its reputation as a reliable store of value, particularly during periods of inflation and currency depreciation, as per our comprehensive market analysis for 2025.

One of the most significant growth factors for the gold bullion market is the heightened volatility and uncertainty in global financial markets. Investors, both retail and institutional, are increasingly turning towards gold bullion as a hedge against inflation, currency fluctuations, and geopolitical risks. The persistent low-interest-rate environment, coupled with concerns over sovereign debt and fiscal imbalances in major economies, has further fueled the demand for physical gold. Central banks, especially in emerging markets, have been augmenting their gold reserves to diversify away from the US dollar and other fiat currencies, providing a strong and sustained impetus to the gold bullion market.

Another key driver propelling the gold bullion market is the growing accessibility and innovation in distribution channels. The proliferation of online platforms and digital gold investment products has democratized access to gold bullion, enabling a broader base of individual investors to participate in the market. This trend is further amplified by the introduction of fractional gold ownership, secure storage solutions, and transparent pricing mechanisms, which have collectively enhanced investor confidence and convenience. Additionally, the rise of gold-backed exchange-traded funds (ETFs) and other financial instruments has expanded the avenues for gold investment, reinforcing the market’s growth momentum.

Sustainability and ethical sourcing concerns are also shaping the gold bullion market landscape. Increasing awareness about responsible mining practices and the environmental and social impact of gold extraction has led to the emergence of certified, conflict-free bullion products. Regulatory initiatives and industry-led standards, such as the London Bullion Market Association (LBMA) Responsible Gold Guidance, are driving transparency and traceability across the supply chain. These developments are not only addressing investor concerns but also attracting a new segment of environmentally and socially conscious buyers, further supporting market expansion.

From a regional perspective, the Asia Pacific region remains the dominant force in the gold bullion market, driven by robust demand in countries like China and India, where gold holds deep cultural and economic significance. North America and Europe also represent substantial market shares, supported by strong institutional investment and central bank activity. Meanwhile, the Middle East & Africa and Latin America are emerging as important markets, buoyed by rising wealth levels, favorable regulatory environments, and increasing financial inclusion. The regional diversity in demand drivers underscores the global appeal and resilience of the gold bullion market.

Product Type Analysis

The gold bullion market is segmented by product type into bars, coins, rounds, and others, each catering to distinct investor preferences and use cases. Gold bars, often regarded as the standard investment vehicle for institutional buyers and high-net-worth individuals, account for the largest share of the market. Their appeal lies in their high purity, lower premiums over spot prices, and ease of storage and transport, making them the preferred choice for those seeking to make substantial investments in physical

The dataset shows average price in domestic and foreign markets of gold and silver

Note: The data sources are: 1. Gold and Silver Prices in Mumbai: Business Standard, Business Line, or The Economic Times (Mumbai) , IBJA Website. 2. Gold Price in London: LBMA. 3. Silver Price in New York:Thomson Reuters.

Gold Fields stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

This dataset is about news. It has 224 rows and is filtered where the keywords includes A model of short-run gold price behaviour?. It features 2 columns including news link.

The dataset shows average price in domestic and foreign markets of gold and silver

Note: 1. The data source for this Table for the period till 1999-2000 are Bombay Bullion Association and Press Trust of India. For the period 2000-01 onwards, the data sources are (i) Business Standard/ Business Line and Economic Times, Mumbai/IBJA Website for gold and silver price in Mumbai and LBMA for gold price in London and (ii) Thomson Reuters for silver price in New York. 2. Data provided in this Table for the period 1979-80 to 1999-2000 and 2000-01 to 2020-21 may not be strictly comparable due to different sources of information.

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: A Brighter Future Ahead?

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

The global market for gold should reach $189.6 billion by 2022 from $163.9 billion in 2017 at a compound annual growth rate of 3.0% from 2017 to 2022..

Analysis of ‘Sentiment Analysis of Commodity News (Gold)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/ankurzing/sentiment-analysis-in-commodity-market-gold on 14 February 2022.

--- Dataset description provided by original source is as follows ---

Context

This is a news dataset for the commodity market where we have manually annotated 11,412 news headlines across multiple dimensions into various classes. The dataset has been sampled from a period of 20+ years (2000-2021).

Content

The dataset has been collected from various news sources and annotated by three human annotators who were subject experts. Each news headline was evaluated on various dimensions, for instance - if a headline is a price related news then what is the direction of price movements it is talking about; whether the news headline is talking about the past or future; whether the news item is talking about asset comparison; etc.

Acknowledgements

Sinha, Ankur, and Tanmay Khandait. "Impact of News on the Commodity Market: Dataset and Results." In Future of Information and Communication Conference, pp. 589-601. Springer, Cham, 2021.

https://arxiv.org/abs/2009.04202 Sinha, Ankur, and Tanmay Khandait. "Impact of News on the Commodity Market: Dataset and Results." arXiv preprint arXiv:2009.04202 (2020)

We would like to acknowledge the financial support provided by the India Gold Policy Centre (IGPC).

Inspiration

Commodity prices are known to be quite volatile. Machine learning models that understand the commodity news well, will be able to provide an additional input to the short-term and long-term price forecasting models. The dataset will also be useful in creating news-based indicators for commodities.

Apart from researchers and practitioners working in the area of news analytics for commodities, the dataset will also be useful for researchers looking to evaluate their models on classification problems in the context of text-analytics. Some of the classes in the dataset are highly imbalanced and may pose challenges to the machine learning algorithms.

--- Original source retains full ownership of the source dataset ---

Get the latest insights on price movement and trend analysis of Gold in different regions across the world (Asia, Europe, North America, Latin America, and the Middle East Africa).

This document contains statistical data and analysis of global gold demand and prices from 2010 to 2024, presented by Dojipedia, a website focused on Forex investment information. The data is organized quarterly and includes various categories of gold demand such as jewelry fabrication, technology use, investment, and central bank purchases. It also provides the LBMA gold price in US dollars per ounce for each quarter.The document highlights significant events that influenced gold prices and demand during this period. These events include major economic crises, geopolitical tensions, and market shifts. For instance, it mentions the European debt crisis in 2010, the U.S. credit rating downgrade in 2011, the Federal Reserve's quantitative easing tapering signals in 2013, and the COVID-19 pandemic's impact starting in 2020.The data shows how gold demand and prices often increase during times of economic uncertainty or political instability, as investors view gold as a safe-haven asset. For example, gold prices reached record highs in 2024 amid global economic and geopolitical uncertainties.Dojipedia presents itself as a platform with five years of Forex market investment experience. The site offers free educational content on technical analysis methods such as Elliott Wave, ICT Trading, and Smart Money Concept. It also mentions plans to publish free books on technical analysis.The document includes a disclaimer stating that the information provided is for general purposes only and not financial advice. It warns about the high risks associated with investing in financial markets like CFDs, Forex, cryptocurrencies, and gold. The disclaimer emphasizes that leveraged products may not be suitable for all investors due to the high risk to capital.Overall, this document serves as a comprehensive resource for those interested in gold market trends and their relationship to global economic events over the past decade and a half.

Amid growing geopolitical tensions and strategic central bank moves, gold prices have surged to new highs. Experts from Macquarie Group and other financial institutions project prices reaching up to $3,500 this year.