United States - Import Price Index (End Use): Gem Diamonds was 100.40000 Index Dec 2007=100 in May of 2025, according to the United States Federal Reserve. Historically, United States - Import Price Index (End Use): Gem Diamonds reached a record high of 118.80000 in March of 2022 and a record low of 97.20000 in March of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Import Price Index (End Use): Gem Diamonds - last updated from the United States Federal Reserve on July of 2025.

In 1960, the average price for such a diamond stood at some ***** U.S. dollars. Since then, the diamond price has increased more than tenfold, to ****** U.S. dollars in 2015. Diamond prices: carats to dollars Diamonds are a carbon-based gemstone coveted by innumerable people worldwide. They are among the hardest materials on Earth (if not the hardest), which makes them very valuable for industrial uses in addition to their wide use in luxury jewelry. Diamonds are also expensive. The cut, clarity, color, and carat (weight and size) are the so-called four 'Cs' that dictate a diamond's price. One carat is equal to a weight of approximately *** milligrams, and cost approximately ****** U.S. dollars in 2015. Diamond prices per carat show a consistent increasing trend, while the annual rough diamond production worldwide has sat between *** million carats and *** million carats between 2009 and 2019. Impact of the diamond demand-supply gap on prices As the known global diamond reserves continue to be mined and depleted while the global demand for diamonds increases, a diamond demand-supply gap is expected to develop in the coming years. By 2050, there is a forecasted supply shortfall of some *** million carats of diamonds worldwide. This will likely cause the price per carat to continue increasing for natural diamonds. The production of synthetic diamonds, also referred to as lab grown diamonds, is a potential solution to the projected diamond shortfall. There was a steady production of between **** and **** billion carats of synthetic diamonds worldwide between 2007 and 2016. Synthetic diamonds also cost between ** and ** percent less than a natural diamond does, but not every consumer is willing to forgo natural diamonds in favor of a diamond that has been created in a lab.

Graph and download economic data for Import Price Index (Harmonized System): Diamonds, Whether or Not Worked, but Not Mounted or Set (IP7102) from Dec 1992 to May 2025 about harmonized, imports, price index, indexes, price, and USA.

In 2023, the price of a one carat diamond from De Beers was approximately ** U.S. dollars. De Beers is one of the leading diamond companies in the world. It is headquartered in London, United Kingdom.

Graph and download economic data for Import Price Index (End Use): Gem Diamonds (IR42100) from Dec 2007 to May 2025 about end use, imports, price index, indexes, price, and USA.

Snapshot img

Diamond Market Size 2024-2028

The diamond market size is forecast to increase by USD 42.72 billion, at a CAGR of 8.09% between 2023 and 2028.

The market is experiencing significant growth, driven primarily by the increasing demand for diamond jewelry, particularly for engagement and wedding rings. This trend is fueled by cultural traditions, societal norms, and the desire for luxury and self-expression. Additionally, the emergence of synthetic diamonds in various applications, such as industrial and consumer electronics, is expanding the market's scope and potential. However, the market faces challenges, including the presence of counterfeit products in the e-retailing space. This issue undermines consumer trust and poses a threat to market integrity.
Companies must prioritize authenticity and transparency to mitigate the risks and maintain a strong market position. To capitalize on opportunities and navigate challenges effectively, market participants should focus on innovation, quality, and ethical sourcing. By addressing these factors, they can differentiate themselves and build lasting customer relationships.

What will be the Size of the Diamond Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2018-2022 and forecasts 2024-2028 - in the full report.
Request Free Sample

The market continues to evolve, with dynamic interplays between various sectors shaping its landscape. Diamond engagement rings remain a significant application, with GIA certification playing a crucial role in ensuring transparency and trust. Simultaneously, diamond auctions provide a platform for buying and selling polished and rough diamonds, influencing market prices. The 4Cs of diamonds - carat weight, color, clarity, and cut - remain the benchmark for evaluating diamond quality. However, the advent of technology has led to advancements such as irradiation treatment, polishing wheels, and blockchain technology, enhancing diamond certification and traceability. Irradiation treatment alters the diamond's color, while polishing wheels refine its shape.

Blockchain technology offers enhanced transparency and security, ensuring ethical sourcing and traceability. Retail markups vary, with luxury goods commanding premium prices. Meanwhile, the rough diamond sector undergoes continuous transformation, with mining, processing, and value assessment shaping its market dynamics. Rough diamonds are cut and polished to create stunning jewelry pieces, such as earrings, pendants, and bracelets. Investment-grade diamonds attract investors, with conflict-free diamonds gaining popularity due to ethical considerations. Synthetic diamonds, including lab-grown and cultured diamonds, challenge the traditional market, offering cost-effective alternatives. Diamond Mining equipment and processing technologies continue to advance, enabling efficient extraction and refinement. The market's continuous evolution reflects the interplay between technology, consumer preferences, and industry trends.

How is this Diamond Industry segmented?

The diamond industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Application

  Jewelry making
  Industrial applications


Type

  Natural
  Synthetic


Mining Method

  Open Pit
  Underground
  Alluvial
  Marine


Cut/Shape

  Round Brilliant
  Princess
  Cushion
  Emerald
  Oval
  Pear
  Marquise
  Asscher
  Radiant
  Heart


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  Middle East and Africa

    Egypt
    KSA
    Oman
    UAE


  APAC

    China
    India
    Japan


  South America

    Argentina
    Brazil


  Rest of World (ROW)

By Application Insights

The jewelry making segment is estimated to witness significant growth during the forecast period.

The market experiences significant growth due to the expanding middle class and their increasing disposable income. This economic shift enables consumers to invest in luxury goods, particularly diamond jewelry. The desire for personal accessories, coupled with evolving lifestyles and urbanization, fuels innovation among manufacturers, resulting in unique designs to attract customers. Key entities shaping this market include diamond mining equipment for extracting rough diamonds, cultured diamonds for ethical sourcing, and diamond certification bodies like GIA and IGI ensuring authenticity and quality. Polished diamonds are then cut and graded based on the 4Cs – carat weight, color, clarity, and cut – before being transformed into various jewelry pieces such as engagement rings, earrings, pendants, and bracelets.

Diamond auctions and wholesale platforms facilitate t

In 2022, lab-created diamonds that weighed 1.5 carats cost less at over ****, U.S. dollars when compared with natural diamonds at a cost of more than ****, U.S. dollars. Since 2016, the prices of laboratory diamonds have increased whereas the prices of natural diamonds have decreased each year.

South Africa: Diamond production, USD per carat: The latest value from 2024 is 124.03 USD per carat, a decline from 134.75 USD per carat in 2023. In comparison, the world average is 43.67 USD per carat, based on data from 59 countries. Historically, the average for South Africa from 2004 to 2024 is 140.54 USD per carat. The minimum value, 76.34 USD per carat, was reached in 2004 while the maximum of 319.04 USD per carat was recorded in 2017.

Import Price Index - Diamonds: 33 years of historical data from 1992 to 2025.

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

United States - Import Price Index (Harmonized System): Diamonds, Whether or Not Worked, but Not Mounted or Set was 102.40000 Index 2000=100 in May of 2025, according to the United States Federal Reserve. Historically, United States - Import Price Index (Harmonized System): Diamonds, Whether or Not Worked, but Not Mounted or Set reached a record high of 121.10000 in March of 2022 and a record low of 95.00000 in October of 2001. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Import Price Index (Harmonized System): Diamonds, Whether or Not Worked, but Not Mounted or Set - last updated from the United States Federal Reserve on July of 2025.

As of October 2019, Clean Origin lab-grown diamonds were the most affordable diamonds in a comparison of eight different lab-grown and mined diamond brands. A 1.5 carat round lab-grown diamond from Clean Origin cost approximately 4,425 U.S. dollars retail as of that time. At the other end of this comparison, a mined 1.5 carat diamond of the same quality specifications from the Brilliant Earth brand cost 13,100 U.S. dollars as of October 2019.

Israel Export Price Index: 2000=100: Rough Diamonds data was reported at 109.700 2000=100 in Mar 2009. This records a decrease from the previous number of 134.800 2000=100 for Dec 2008. Israel Export Price Index: 2000=100: Rough Diamonds data is updated quarterly, averaging 118.250 2000=100 from Jun 2001 (Median) to Mar 2009, with 32 observations. The data reached an all-time high of 165.000 2000=100 in Jun 2008 and a record low of 101.500 2000=100 in Dec 2002. Israel Export Price Index: 2000=100: Rough Diamonds data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Israel – Table IL.I027: Export Price Index: 2000=100. Diamonds show Gross Diamonds.

United States - Export Price Index (Harmonized System): Diamonds, Whether or Not Worked, but Not Mounted or Set was 99.20000 Index Dec 2013=100 in May of 2025, according to the United States Federal Reserve. Historically, United States - Export Price Index (Harmonized System): Diamonds, Whether or Not Worked, but Not Mounted or Set reached a record high of 118.20000 in March of 2022 and a record low of 94.60000 in March of 2020. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Export Price Index (Harmonized System): Diamonds, Whether or Not Worked, but Not Mounted or Set - last updated from the United States Federal Reserve on July of 2025.

Israel Import Price Index: Commodities: Diamonds data was reported at 109.600 2010=100 in Jun 2018. This records a decrease from the previous number of 118.700 2010=100 for May 2018. Israel Import Price Index: Commodities: Diamonds data is updated monthly, averaging 117.900 2010=100 from Jan 2011 (Median) to Jun 2018, with 90 observations. The data reached an all-time high of 176.600 2010=100 in Nov 2011 and a record low of 93.400 2010=100 in Aug 2013. Israel Import Price Index: Commodities: Diamonds data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Israel – Table IL.I032: Import Price Index: 2010=100.

Israel Import Price Index: 2000=100: Raw Materials: Diamonds data was reported at 131.400 2000=100 in Mar 2009. This records a decrease from the previous number of 147.500 2000=100 for Dec 2008. Israel Import Price Index: 2000=100: Raw Materials: Diamonds data is updated quarterly, averaging 117.150 2000=100 from Jun 2001 (Median) to Mar 2009, with 32 observations. The data reached an all-time high of 170.900 2000=100 in Jun 2008 and a record low of 101.400 2000=100 in Dec 2002. Israel Import Price Index: 2000=100: Raw Materials: Diamonds data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Global Database’s Israel – Table IL.I035: Import Price Index: 2000=100.

United States Export Price Index: CG: NM: Durables: Gem Diamonds data was reported at 93.700 Dec2023=100 in Mar 2025. This stayed constant from the previous number of 93.700 Dec2023=100 for Feb 2025. United States Export Price Index: CG: NM: Durables: Gem Diamonds data is updated monthly, averaging 96.100 Dec2023=100 from Dec 2023 (Median) to Mar 2025, with 16 observations. The data reached an all-time high of 100.000 Dec2023=100 in Feb 2024 and a record low of 91.800 Dec2023=100 in Jan 2025. United States Export Price Index: CG: NM: Durables: Gem Diamonds data remains active status in CEIC and is reported by U.S. Bureau of Labor Statistics. The data is categorized under Global Database’s United States – Table US.JA113: Export Price Index: by End Use: 2000=100.

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.

MPVD:TSX Mountain Province Diamonds Inc.

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

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.

Mountain Province Diamonds Inc. is assigned short-term Ba1 & long-term Ba1 estimated rating.

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

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.

Petra Diamonds: A Rough Ride Ahead? (PDL)

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