Copper rose to 4.50 USD/Lbs on September 8, 2025, up 0.76% from the previous day. Over the past month, Copper's price has risen 1.49%, and is up 10.49% 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 September of 2025.

About This Dataset: Copper Prices and Market Trends

    This dataset provides **insights into copper prices**, including current rates, historical trends, and key factors affecting price fluctuations. Copper is essential in **construction**, **electronics**, and **transportation** industries. Investors, traders, and analysts use accurate copper price data to guide decisions related to **trading**, **futures**, and **commodity investments**.

    ### **Key Features of the Dataset**

    #### **Live Market Data and Updates**
    Stay updated with the latest **copper price per pound** in USD. This data is sourced from exchanges like the **London Metal Exchange (LME)** and **COMEX**. Price fluctuations result from **global supply-demand shifts**, currency changes, and geopolitical factors.

    #### **Interactive Copper Price Charts**
    Explore **dynamic charts** showcasing real-time and historical price movements. These compare copper with **gold**, **silver**, and **aluminium**, offering insights into **market trends** and inter-metal correlations.

    ### **Factors Driving Copper Prices**

    #### **1. Supply and Demand Dynamics**
    Global copper supply is driven by mining activities in regions like **Peru**, **China**, and the **United States**. Disruptions in production or policy changes can cause **supply shocks**. On the demand side, **industrial growth** in countries like **India** and **China** sustains demand for copper.

    #### **2. Economic and Industry Trends**
    Copper prices often reflect **economic trends**. The push for **renewable energy** and **electric vehicles** has boosted long-term demand. Conversely, economic downturns and **inflation** can reduce demand, lowering prices.

    #### **3. Impact of Currency and Trade Policies**
    As a globally traded commodity, copper prices are influenced by **currency fluctuations** and **tariff policies**. A strong **US dollar** typically suppresses copper prices by increasing costs for international buyers. Trade tensions can also disrupt **commodity markets**.

    ### **Applications and Benefits**

    This dataset supports **commodity investors**, **traders**, and **industry professionals**:

    - **Investors** forecast price trends and manage **investment risks**. 
    - **Analysts** perform **market research** using price data to assess **copper futures**. 
    - **Manufacturers** optimize supply chains and **cost forecasts**.

    Explore more about copper investments on **Money Metals**:

    - [**Buy Copper Products**](https://www.moneymetals.com/buy/copper) 
    - [**95% Copper Pennies (Pre-1983)**](https://www.moneymetals.com/pre-1983-95-percent-copper-pennies/4) 
    - [**Copper Buffalo Rounds**](https://www.moneymetals.com/copper-buffalo-round-1-avdp-oz-999-pure-copper/297)

    ### **Copper Price Comparisons with Other Metals**

    Copper prices often correlate with those of **industrial** and **precious metals**:

    - **Gold** and **silver** are sensitive to **inflation** and currency shifts. 
    - **Iron ore** and **aluminium** reflect changes in **global demand** within construction and manufacturing sectors.

    These correlations help traders develop **hedging strategies** and **investment models**.

    ### **Data Variables and Availability**

    Key metrics include:

    - **Copper Price Per Pound:** The current market price in USD. 
    - **Copper Futures Price:** Data from **COMEX** futures contracts. 
    - **Historical Price Trends:** Long-term movements, updated regularly. 

    Data is available in **CSV** and **JSON** formats, enabling integration with analytical tools and platforms.

    ### **Conclusion**

    Copper price data is crucial for **monitoring global commodity markets**. From **mining** to **investment strategies**, copper impacts industries worldwide. Reliable data supports **risk management**, **planning**, and **economic forecasting**.

    For more tools and data, visit the **Money Metals** [Copper Prices Page](https://www.moneymetals.com/copper-prices).

Aluminum rose to 2,614.40 USD/T on September 8, 2025, up 0.32% from the previous day. Over the past month, Aluminum's price has risen 1.16%, and is up 11.23% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Aluminum - values, historical data, forecasts and news - updated on September of 2025.

LME Index rose to 4,233.30 Index Points on September 5, 2025, up 0.05% from the previous day. Over the past month, LME Index's price has risen 1.61%, and is up 9.11% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. LME Index - values, historical data, forecasts and news - updated on September of 2025.

Nickel fell to 15,180 USD/T on September 8, 2025, down 0.65% from the previous day. Over the past month, Nickel's price has fallen 0.95%, and is down 4.55% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Nickel - values, historical data, forecasts and news - updated on September of 2025.

Lead fell to 1,981.28 USD/T on September 9, 2025, down 0.46% from the previous day. Over the past month, Lead's price has fallen 0.98%, but it is still 1.34% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Lead - values, historical data, forecasts and news - updated on September of 2025.

This data collection consists of survey data collected from mine workers in Tanzania. Artisanal and small-scale mining (ASM) has long been a mainstay of Tanzania’s rural economy, contributing to the livelihoods of more than three million Tanzanians. ASM is nonetheless yet to realise its full development potential, with the sub-sector continuing to be beset by social, environmental and economic under-performance issues as a result of structural resource and capacity constraints. Like countries such as Ghana, Cameroon and Zimbabwe, foreign investors, often of Chinese origin, are increasingly participating in Tanzania’s ASM chains, which bring in much-needed capital, technologies and know-how. Therefore, such investments have the potential to contribute to resolving ASM barriers to upgrading, but could also pose a threat if not properly regulated. These investments however have by and large failed to fulfil their transformative potential by forging limited productive linkages with ASM miners. We also observed limited differences between Chinese and other investors in business models and associated impacts, attesting to the sector- wide – rather than investor-specific – nature of these challenges. In light of the ongoing sector reform, this paper highlights a host of critical institutional issues that deserve greater attention if the Tanzanian government is to improve the performance of ASM and leverage the potential of foreign investment in the sub-sector.This project addresses two key development challenges and opportunities concerning Africa's natural resource governance today: the growing informal commodity trade and engagement with China. It focuses on the impacts of Chinese actors in informal agriculture, mining and timber trade along two fast-developing trade corridors connected to the Indian Ocean. The first corridor is a transit route for commodities such as timber and minerals from the Democratic Republic of Congo (DRC) through East Africa for export from Kenya. The second corridor links central southern Africa (Zambia and DRC's Katanga province to Beira port in Mozambique, from where agricultural products, timber and, increasingly minerals are exported). Examining the two trade routes that link Africa's informal natural resource sectors to the ever-growing Chinese market, this work will provide urgently needed insights on natural resource governance, global trade patterns, and the positive and deleterious effects of informal resource exploitation on local poverty and the natural environment. It builds on ongoing efforts by IIED and CIFOR in relation to these topics, expanding and deepening research in the area and using a well-connected policy network to achieve impact. Specifically, the research involves four work streams over the course of 36 months: i) value chain analysis of selected commodity chains with a particular focus on power dynamics and benefit distribution among actors, ii) political-economic analysis of regulatory and customary regimes governing the selected commodity trade, iii) environmental impacts analysis through land-use/land cover change and iv) cross-sector synthesis of the three sectors' findings and key policy lessons. The proposed research addresses all the objectives of the DFID-ESRC China and Africa Research Programme Call. First, it takes Africa's development challenges (the growing informal economy and depleting natural resource base) as starting points to examine Chinese engagement in the context of informal commodity trade. Envisioned as one of the first systematic examinations of micro-level Chinese activities in Africa's natural resource governance, this research will provide rigorous evidence and dispel misconceptions about Chinese trade and investment in Africa's informal economy. Second, it benefits economically-marginalized actors (such as rural resource users, women and youth not integrated in the formal economy) in the selected African countries by identifying opportunities and challenges for poverty alleviation and sustainable resource use associated with Africa's growing informal economy and China-Africa commodity trade Third, it confronts two cross-cutting themes: gender and fragile states through gender-disaggregated value chain and livelihoods analysis and inclusion of the DRC as a research site. Fourth, it supports national and international policymaking by generating an evidence-based body of knowledge strongly demanded by Chinese, African and international policymakers, businesses as well as rural African resource users - their requests for accurate information have been highlighted through the previous research, personal communications and policy engagement work by IIED, CIFOR, GEI and the African institutions (see Pathways to Impact). Finally, it adds to the development literature by extending and adopting existing methodologies to informal economy research - a field that is rapidly growing in importance for studying economic development in the global South. It also takes a multidisciplinary approach through environmental impact assessment using GIS remote sensing, which is critical to obtaining a comprehensive understanding of the challenges and opportunities associated with sustainable development. Within Tanzania, four areas popular for gold and copper were selected using key informant interviews: Chunya and Geita for gold, Mpwapwa and Mwanga for copper. For each location, a key case study mining business was identified. For each case, between 30 to 40 employees of the mine were surveyed.

Introduction

The famous Sherlock Holmes quote, “Data! data! data!” from The Copper Beeches perfectly encapsulates the essence of both detective work and data analysis. Holmes’ relentless pursuit of every detail closely mirrors the approach of modern data analysts, who understand that conclusions drawn without solid data are mere conjecture. Just as Holmes systematically gathered clues, analysed them from different perspectives, and tested hypotheses to arrive at the truth, today’s analysts follow similar processes when investigating complex data-driven problems. This project draws a parallel between Holmes’ detective methods and modern data analysis techniques by visualising and interpreting data from The Adventures of Sherlock Holmes.

“**Data! data! data!**” he cried, impatiently. “I can’t make bricks without clay.”

The above quote comes from one of my favourite Sherlock Holmes stories, The Copper Beeches. In this single outburst, Holmes captures a principle that resonates deeply with today’s data analysts: without data, conclusions are mere speculation. Data is the bedrock of any investigation. Without sufficient data, the route to solving a problem or answering a question is clouded with uncertainty.

Sherlock Holmes, the iconic fictional detective, thrived on difficult cases, relishing the challenge of pitting his wits against the criminal mind.

His methods of detection: - Examining crime scenes. - Interrogating witnesses. - Evaluating motives.

Closely parallel how a data analyst approaches a complex problem today. By carefully collecting and interpreting data, Holmes was able to unravel mysteries that seemed impenetrable at first glance.

1. Data Collection: Gathering Evidence
Holmes’s meticulous approach to data collection mirrors the first stage of data analysis. Just as Holmes would scrutinise a crime scene for every detail; whether it be a footprint, a discarded note, or a peculiar smell. Data analysts seek to gather as much relevant data as possible. Just as incomplete or biased data can skew results in modern analysis, Holmes understood that every clue mattered. Overlooking a small piece of information could compromise the entire investigation.

2. Data Quality: “I can’t make bricks without clay.”
This quote is more than just a witty remark, it highlights the importance of having the right data. In the same way that substandard materials result in poor construction, incomplete or inaccurate data leads to unreliable analysis. Today’s analysts face similar issues: they must assess data integrity, clean noisy datasets, and ensure they’re working with accurate information before drawing conclusions. Holmes, in his time, would painstakingly verify each clue, ensuring that he was not misled by false leads.

3. Data Analysis: Considering Multiple Perspectives
Holmes’s genius lay not just in gathering data, but in the way he analysed it. He would often examine a problem from multiple angles, revisiting clues with fresh perspectives to see what others might have missed. In modern data analysis, this approach is akin to using different models, visualisations, and analytical methods to interpret the same dataset. Analysts explore data from multiple viewpoints, testing different hypotheses, and applying various algorithms to see which provides the most plausible insight.

4. Hypothesis Testing: Eliminate the Improbable
One of Holmes’s guiding principles was: “When you have eliminated the impossible, whatever remains, however improbable, must be the truth.” This mirrors the process of hypothesis testing in data analysis. Analysts might begin with several competing theories about what the data suggests. By testing these hypotheses, ruling out those that are contradicted by the data, they zero in on the most likely explanation. For both Holmes and today’s data analysts, the process of elimination is crucial to arriving at the correct answer.

5. Insight and Conclusion: The Final Deduction
After piecing together all the clues, Holmes would reveal his conclusion, often leaving his audience in awe at how the seemingly unrelated pieces of data fit together. Similarly, data analysts must present their findings clearly and compellingly, translating raw data into actionable insights. The ability to connect the dots and tell a coherent story from the data is what transforms analysis into impactful decision-making.

In summary, the methods Sherlock Holmes employed were gathering data meticulously, testing multiple angles, and drawing conclusions through careful analysis. Are strikingly similar to the techniques used by modern data analysts. Just as Holmes required high-quality data and a structured approach to solve crimes, today’s data analysts rely on well-prepared data and methodical analysis to provide insights. Whether you’re cracking a case or uncovering business...

Cobalt traded flat at 33,335 USD/T on September 4, 2025. Over the past month, Cobalt's price has remained flat, but it is still 37.18% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Cobalt - values, historical data, forecasts and news - updated on September of 2025.

Zinc rose to 2,875.95 USD/T on September 8, 2025, up 0.43% from the previous day. Over the past month, Zinc's price has risen 2.22%, and is up 5.31% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Zinc - values, historical data, forecasts and news - updated on September of 2025.

Titanium fell to 49 CNY/KG on September 8, 2025, down 0.02% from the previous day. Over the past month, Titanium's price has remained flat, but it is still 11.36% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. This dataset includes a chart with historical data for Titanium.