Consumer Price Index CPI in the United States increased to 322.56 points in June from 321.46 points in May of 2025. This dataset provides the latest reported value for - United States Consumer Price Index (CPI) - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

In 2023, the U.S. Consumer Price Index was 309.42, and is projected to increase to 352.27 by 2029. The base period was 1982-84. The monthly CPI for all urban consumers in the U.S. can be accessed here. After a time of high inflation, the U.S. inflation rateis projected fall to two percent by 2027. United States Consumer Price Index ForecastIt is projected that the CPI will continue to rise year over year, reaching 325.6 in 2027. The Consumer Price Index of all urban consumers in previous years was lower, and has risen every year since 1992, except in 2009, when the CPI went from 215.30 in 2008 to 214.54 in 2009. The monthly unadjusted Consumer Price Index was 296.17 for the month of August in 2022. The U.S. CPI measures changes in the price of consumer goods and services purchased by households and is thought to reflect inflation in the U.S. as well as the health of the economy. The U.S. Bureau of Labor Statistics calculates the CPI and defines it as, "a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services." The BLS records the price of thousands of goods and services month by month. They consider goods and services within eight main categories: food and beverage, housing, apparel, transportation, medical care, recreation, education, and other goods and services. They aggregate the data collected in order to compare how much it would cost a consumer to buy the same market basket of goods and services within one month or one year compared with the previous month or year. Given that the CPI is used to calculate U.S. inflation, the CPI influences the annual adjustments of many financial institutions in the United States, both private and public. Wages, social security payments, and pensions are all affected by the CPI.

Core consumer prices in the United States increased 2.90 percent in June of 2025 over the same month in the previous year. This dataset provides - United States Core Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

We report average expected inflation rates over the next one through 30 years. Our estimates of expected inflation rates are calculated using a Federal Reserve Bank of Cleveland model that combines financial data and survey-based measures. Released monthly.

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.

Surging Services: Will Dow Jones CPI Signal Continued Consumer Strength?

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

In January 2025, the unadjusted consumer price index (CPI) of all items for urban consumers in the United States amounted to about 317.67. The data represents U.S. city averages. The base period was 1982-84=100. The CPI is defined by the United States Bureau of Labor Statistics as “a measure of the average change over time in the prices paid by urban consumers for a market basket of consumer goods and services”. The annual consumer price index for urban consumers in the U.S. can be accessed here. Consumer Price Index The Consumer Price Index (CPI) began in 1919 under the Bureau of Labor Statistics and is published every month. The CPI for all urban consumers includes urban households in Metropolitan Statistical Areas and regions with over 2,500 inhabitants, as well as non-farm consumers living in rural regions. This index was established in 1978 and includes about 80 percent of the U.S. population. The monthly CPI of urban consumers in the United States increased from 292.3 in May 2022 to 304.13 in 2023. Inflation tends not to impact everyone equally for a variety of reasons, including geography - CPI often differs between regions, with a high of 287.49 in the Western region as of 2021. There are also disparities in inflation between income quartiles, in which inflation is generally felt more heavily by lower income households. The annual CPI in the United States has increased steadily over the past two decades, from 140.3 in 1992 to 292.56 in 2022. A forecast of the CPI expects this positive trend to continue, reaching 325.6 by 2027. As of March 2023, the CPI of the nation’s education had increased by 3.5 percent. Further, in the same month costs of recreation, rent, housing, medical care, and food and beverages, gasoline, and transportation increased. Comparatively, the CPI in Hong Kong reached 103.3 in 2022.

Brazil Market Expectation: Inflation: Accumulated Over Next 12 Months: Extended National Consumer Price Index (IPCA): Smoothed: Median data was reported at 3.680 % in 28 Jun 2019. This records an increase from the previous number of 3.670 % for 27 Jun 2019. Brazil Market Expectation: Inflation: Accumulated Over Next 12 Months: Extended National Consumer Price Index (IPCA): Smoothed: Median data is updated daily, averaging 5.240 % from Dec 2001 (Median) to 28 Jun 2019, with 4401 observations. The data reached an all-time high of 12.350 % in 19 Dec 2002 and a record low of 3.380 % in 23 May 2007. Brazil Market Expectation: Inflation: Accumulated Over Next 12 Months: Extended National Consumer Price Index (IPCA): Smoothed: Median data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Business and Economic Survey – Table BR.SA032: Market Expectation: Inflation: Accumulated Over Next 12 Months: Extended National Consumer Price Index (IPCA): Smoothed. Market Expectations System was implemented in November 2001, previous projections were collected from incipient through telephone contacts, transcribed into spreadsheets and consolidated manually. Some empty time points occurred because the Market didn´t have the expectation for those days. Monitors the variations in costs of people earning from one to forty minimum wages in the metropolitan areas of Belém, Belo Horizonte, Curitiba, Fortaleza, Porto Alegre, Recife, Rio de Janeiro, Salvador, São Paulo, municipality of Goiânia and Federal District. The IPCA measures the change in cost of expenses as described above in the period from the first to the last day of each reference month. In the period from the eleventh day to the twenty day of the following month the IBGE announces the variations.

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

In 2020 the Consumer Price Index (CPI) rate of the United Kingdom is expected to be between *** percent and *** percent, according to forecasts from three different institutions, the Office for Budget Responsibility, the International Monetary Fund, and the The National Institute of Economic and Social Research. CPI measures the rate of change to market basket price levels of consumer goods and services purchased by households.

Expected Inflation Term Structure is a part of the Inflation Expectations indicator of the Federal Reserve Bank of Cleveland.

Inflation Expectations in the United States increased to 3.10 percent in July from 3 percent in June of 2025. This dataset provides - United States Consumer Inflation Expectations- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Ten-Year TIPS Yields versus Real Yields is a part of the Inflation Expectations indicator of the Federal Reserve Bank of Cleveland.

Brazil Market Expectation: Price Indices: Extended National Consumer Price Index 15 (IPCA-15): 2 Years Ahead: Median data was reported at 3.750 % in 28 Jun 2019. This stayed constant from the previous number of 3.750 % for 27 Jun 2019. Brazil Market Expectation: Price Indices: Extended National Consumer Price Index 15 (IPCA-15): 2 Years Ahead: Median data is updated daily, averaging 4.500 % from Nov 2001 (Median) to 28 Jun 2019, with 4425 observations. The data reached an all-time high of 6.500 % in 24 Mar 2003 and a record low of 3.500 % in 28 Jun 2002. Brazil Market Expectation: Price Indices: Extended National Consumer Price Index 15 (IPCA-15): 2 Years Ahead: Median data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Business and Economic Survey – Table BR.SA017: Market Expectation: Price Indices: Extended National Consumer Price Index 15 (IPCA-15). Market Expectations System was implemented in November 2001, previous projections were collected from incipient through telephone contacts, transcribed into spreadsheets and consolidated manually. Some empty time points occurred because the Market didn´t have the expectation for those days. Measures the variation of the costs of the expenses, as described in the IPCA, in the approximate period from the 15th of a month to the 15th of the subsequent month.

Brazil Market Expectation: Price Indices: Extended National Consumer Price Index 15 (IPCA-15): 1 Year Ahead: Average data was reported at 3.810 % in 28 Jun 2019. This stayed constant from the previous number of 3.810 % for 27 Jun 2019. Brazil Market Expectation: Price Indices: Extended National Consumer Price Index 15 (IPCA-15): 1 Year Ahead: Average data is updated daily, averaging 4.520 % from May 2001 (Median) to 28 Jun 2019, with 4543 observations. The data reached an all-time high of 8.480 % in 18 Dec 2002 and a record low of 2.960 % in 16 Jul 2001. Brazil Market Expectation: Price Indices: Extended National Consumer Price Index 15 (IPCA-15): 1 Year Ahead: Average data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Business and Economic Survey – Table BR.SA017: Market Expectation: Price Indices: Extended National Consumer Price Index 15 (IPCA-15). Market Expectations System was implemented in November 2001, previous projections were collected from incipient through telephone contacts, transcribed into spreadsheets and consolidated manually. Some empty time points occurred because the Market didn´t have the expectation for those days. Measures the variation of the costs of the expenses, as described in the IPCA, in the approximate period from the 15th of a month to the 15th of the subsequent month.

Inflation Rate in the United States increased to 2.70 percent in June from 2.40 percent in May of 2025. This dataset provides - United States Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

The inflation rate in the United States is expected to decrease to 2.1 percent by 2029. 2022 saw a year of exceptionally high inflation, reaching eight percent for the year. The data represents U.S. city averages. The base period was 1982-84. In economics, the inflation rate is a measurement of inflation, the rate of increase of a price index (in this case: consumer price index). It is the percentage rate of change in prices level over time. The rate of decrease in the purchasing power of money is approximately equal. According to the forecast, prices will increase by 2.9 percent in 2024. The annual inflation rate for previous years can be found here and the consumer price index for all urban consumers here. The monthly inflation rate for the United States can also be accessed here. Inflation in the U.S.Inflation is a term used to describe a general rise in the price of goods and services in an economy over a given period of time. Inflation in the United States is calculated using the consumer price index (CPI). The consumer price index is a measure of change in the price level of a preselected market basket of consumer goods and services purchased by households. This forecast of U.S. inflation was prepared by the International Monetary Fund. They project that inflation will stay higher than average throughout 2023, followed by a decrease to around roughly two percent annual rise in the general level of prices until 2028. Considering the annual inflation rate in the United States in 2021, a two percent inflation rate is a very moderate projection. The 2022 spike in inflation in the United States and worldwide is due to a variety of factors that have put constraints on various aspects of the economy. These factors include COVID-19 pandemic spending and supply-chain constraints, disruptions due to the war in Ukraine, and pandemic related changes in the labor force. Although the moderate inflation of prices between two and three percent is considered normal in a modern economy, countries’ central banks try to prevent severe inflation and deflation to keep the growth of prices to a minimum. Severe inflation is considered dangerous to a country’s economy because it can rapidly diminish the population’s purchasing power and thus damage the GDP .

Ten-Year Expected Inflation and Real and Inflation Risk Premia is a part of the Inflation Expectations indicator of the Federal Reserve Bank of Cleveland.

Inflation Rate in India decreased to 1.55 percent in July from 2.10 percent in June of 2025. This dataset provides - India Inflation Rate - actual values, historical data, forecast, chart, statistics, economic calendar and news.

Brazil Market Expectation: Price Indices: Extended National Consumer Price Index 15 (IPCA-15): Current Calendar Year: Standard Deviation data was reported at 0.240 % in 28 Jun 2019. This stayed constant from the previous number of 0.240 % for 27 Jun 2019. Brazil Market Expectation: Price Indices: Extended National Consumer Price Index 15 (IPCA-15): Current Calendar Year: Standard Deviation data is updated daily, averaging 0.300 % from May 2001 (Median) to 28 Jun 2019, with 4537 observations. The data reached an all-time high of 3.140 % in 30 Dec 2002 and a record low of 0.050 % in 05 Dec 2012. Brazil Market Expectation: Price Indices: Extended National Consumer Price Index 15 (IPCA-15): Current Calendar Year: Standard Deviation data remains active status in CEIC and is reported by Central Bank of Brazil. The data is categorized under Brazil Premium Database’s Business and Economic Survey – Table BR.SA017: Market Expectation: Price Indices: Extended National Consumer Price Index 15 (IPCA-15). Market Expectations System was implemented in November 2001, previous projections were collected from incipient through telephone contacts, transcribed into spreadsheets and consolidated manually. Some empty time points occurred because the Market didn´t have the expectation for those days. Measures the variation of the costs of the expenses, as described in the IPCA, in the approximate period from the 15th of a month to the 15th of the subsequent month.

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 is cpi?

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