Gold rose to 3,362.51 USD/t.oz on August 1, 2025, up 2.25% from the previous day. Over the past month, Gold's price has risen 0.15%, and is up 37.65% 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 August of 2025.

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 prices in , June, 2025 For that commodity indicator, we provide data from January 1960 to June 2025. The average value during that period was 600.07 USD per troy ounce with a minimum of 34.94 USD per troy ounce in January 1970 and a maximum of 3352.66 USD per troy ounce in June 2025. | TheGlobalEconomy.com

Silver rose to 37.02 USD/t.oz on August 1, 2025, up 0.93% from the previous day. Over the past month, Silver's price has risen 1.25%, and is up 29.60% 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 August of 2025.

As of the end of April 2024, boerse.de Gold was the best-performing gold exchange-traded commodity (ETC) worldwide. EUWAX Gold followed closely behind in second place, providing an annual return of ***** percent by the month of April.

China Commodity Trading Market over 100 M Yuan: Turnover: Retail: Gold, Jeweller, Jade Market data was reported at 2.965 RMB bn in 2023. This records a decrease from the previous number of 3.631 RMB bn for 2022. China Commodity Trading Market over 100 M Yuan: Turnover: Retail: Gold, Jeweller, Jade Market data is updated yearly, averaging 4.601 RMB bn from Dec 2008 (Median) to 2023, with 16 observations. The data reached an all-time high of 7.689 RMB bn in 2019 and a record low of 1.717 RMB bn in 2009. China Commodity Trading Market over 100 M Yuan: Turnover: Retail: 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: Retail.

CRB Index fell to 369.61 Index Points on July 31, 2025, down 1.78% from the previous day. Over the past month, CRB Index's price has risen 1.62%, and is up 12.72% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. CRB Commodity Index - values, historical data, forecasts and news - updated on August of 2025.

China 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. China 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. China 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.

The price of gold per troy ounce increased considerably between 1990 and 2025, despite some fluctuations. A troy ounce is the international common unit of weight used for precious metals and is approximately **** grams. At the end of 2024, a troy ounce of gold cost ******* U.S. dollars. As of * June 2025, it increased considerably to ******** U.S. dollars. Price of – additional information In 2000, the price of gold was at its lowest since 1990, with a troy ounce of gold costing ***** U.S. dollars in that year. Since then, gold prices have been rising and after the economic crisis of 2008, the price of gold rose at higher rates than ever before as the market began to see gold as an increasingly good investment. History has shown, gold is seen as a good investment in times of uncertainty because it can or is thought to function as a good store of value against a declining currency as well as providing protection against inflation. However, unlike other commodities, once gold is mined it does not get used up like other commodities (for example, such as gasoline). So while gold may be a good investment at times, the supply demand argument does not apply to gold. Nonetheless, the demand for gold has been mostly consistent.

Context

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.

Content

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.

Data

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

Starter Kernel(s)

-Start with Fundamentals: TSA & Box-Jenkins Methods

This notebook is an overview of TSA and traditional methods

Acknowledgements

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.

Inspiration

• Forecast gold price

*If you find the data useful your upvote is an explicit feedback for future works, Have fun exploring data!*

#

MORE DATASETs ...

China Commodity Trading Market over 100 M Yuan: Turnover By Category: Retail: Gold, Silver and Jewellery data was reported at 5.606 RMB bn in 2023. This records a decrease from the previous number of 6.759 RMB bn for 2022. China Commodity Trading Market over 100 M Yuan: Turnover By Category: Retail: Gold, Silver and Jewellery data is updated yearly, averaging 7.862 RMB bn from Dec 2008 (Median) to 2023, with 16 observations. The data reached an all-time high of 11.325 RMB bn in 2019 and a record low of 3.556 RMB bn in 2008. China Commodity Trading Market over 100 M Yuan: Turnover By Category: Retail: 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: Turnover By Category: Retail.

Commodity Index Funds Market Outlook

The global commodity index funds market size was valued at approximately $200 billion in 2023 and is projected to reach nearly $400 billion by 2032, growing at a robust CAGR of 7.5% during the forecast period. The significant growth in this market can be attributed to the increasing demand for diversification in investment portfolios and the inherent benefits of hedging against inflation that commodity investments provide. Furthermore, the volatility in global stock markets and geopolitical uncertainties have led investors to seek safer, more stable investment avenues, thus driving the growth of commodity index funds.

One of the primary growth factors propelling the commodity index funds market is the rising awareness among investors about the advantages of commodity investments as a hedge against inflation. Commodities, unlike stocks and bonds, often move inversely to the stock market, providing a cushion during market downturns. This characteristic makes commodity index funds an attractive option for risk-averse investors and those looking to balance their portfolios. Additionally, the globalization of trade and the increasing demand for raw materials in emerging markets have further spurred the demand for commodity investments.

Technological advancements in trading platforms have also significantly contributed to the growth of this market. The advent of sophisticated online platforms has made it easier for retail investors to access and invest in commodity index funds. These platforms offer a range of tools and resources that help investors make informed decisions, thereby democratizing access to commodity investments. Moreover, the rise of robo-advisors and algorithm-based trading strategies has further simplified the investment process, attracting a new generation of tech-savvy investors.

The regulatory landscape has also played a crucial role in shaping the commodity index funds market. Governments and financial regulatory bodies across the globe have been working to create a transparent and secure trading environment. Regulatory reforms aimed at reducing market manipulation and increasing transparency have instilled confidence among investors, thereby boosting the market. Additionally, tax incentives and favorable policies for commodity investments in various countries have also contributed to market growth.

In terms of regional outlook, North America holds a significant share of the global commodity index funds market, followed by Europe and Asia Pacific. The presence of well-established financial markets and a high level of investor awareness in North America are key factors driving the market in this region. Europe, with its strong regulatory framework and increasing adoption of alternative investment strategies, is also witnessing substantial growth. Meanwhile, the Asia Pacific region is emerging as a lucrative market, driven by the rapid economic growth in countries like China and India, and the increasing interest in commodity investments among institutional and retail investors.

Fund Type Analysis

When analyzing the market by fund type, Broad Commodity Index Funds dominate the landscape. These funds invest in a diversified portfolio of commodities, making them a popular choice for investors seeking broad exposure to the commodity markets. The broad commodity index funds are designed to track the performance of a basket of commodities, ranging from energy products to metals and agricultural goods. This diversification helps mitigate risks associated with the volatility of individual commodities, thereby providing a more stable investment option for risk-averse investors.

Single Commodity Index Funds, on the other hand, focus on specific commodities such as gold, oil, or agricultural products. These funds appeal to investors who have a strong conviction about the performance of a particular commodity. For instance, during periods of economic uncertainty, gold-focused funds often see a surge in demand as investors flock to the safe-haven asset. Similarly, energy-focused funds attract investors when there are disruptions in oil supply or significant geopolitical events affecting oil prices. While these funds offer the potential for high returns, they also come with higher risks due to their lack of diversification.

Sector Commodity Index Funds are another important segment within the commodity index funds market. These funds concentrate on commodities within a specific sector, such as energy, agriculture, or metals, allowing investors to target particular segments of the commo

China 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. China 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. China 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.

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 precious metal trading platform market, valued at $3.863 billion in 2025, is projected to experience robust growth, driven by increasing investor interest in gold, silver, platinum, and palladium as safe haven assets and inflation hedges. The market's Compound Annual Growth Rate (CAGR) of 5.6% from 2019 to 2033 indicates a steady expansion, fueled by technological advancements such as improved online trading platforms, mobile accessibility, and the integration of AI-driven analytical tools. The rise of retail investors and the growing adoption of sophisticated trading strategies further contribute to market expansion. Increased regulatory scrutiny and cybersecurity concerns, however, pose potential restraints to growth. Market segmentation is likely dominated by platform types (e.g., web-based, mobile, desktop), trading styles (e.g., spot, futures), and investor demographics (e.g., retail, institutional). Key players like GAIN Global Markets, AxiTrader, LMAX Global, IG Group, and CMC Markets are vying for market share through competitive pricing, advanced features, and strong customer support. Geographic distribution is expected to be influenced by economic conditions and investor sentiment in major regions like North America, Europe, and Asia-Pacific. The forecast period (2025-2033) will likely see increased competition and consolidation as companies strive to enhance their offerings and cater to the evolving needs of traders. The market's sustained growth relies on several factors. The volatility of traditional financial markets consistently pushes investors toward precious metals. The ongoing development of user-friendly platforms with advanced charting, analytics, and educational resources further broadens the appeal to both experienced and novice traders. Moreover, the expansion of the market into emerging economies presents significant opportunities for growth. However, maintaining trust through robust security measures and complying with evolving regulatory frameworks are critical for long-term success. The presence of established players along with a growing number of smaller, niche platforms suggests a dynamic competitive landscape with continued innovation in technology and service offerings driving market expansion.

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.

Copper rose to 4.42 USD/Lbs on August 1, 2025, up 0.29% from the previous day. Over the past month, Copper's price has fallen 14.18%, but it is still 7.63% higher than a year ago, 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 August of 2025.

In 2024, the rate of return on gold was 26.62 percent, making gold the leading commodity based on return rate in that year. Natural resources, like any other investment, exhibit a wide range of fluctuations over time.

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 August 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