Prices for United States Stock Market Index (US30) including live quotes, historical charts and news. United States Stock Market Index (US30) was last updated by Trading Economics this September 1 of 2025.

The main stock market index of United States, the US500, rose to 6464 points on September 1, 2025, gaining 0.06% from the previous session. Over the past month, the index has climbed 2.13% and is up 16.92% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on September of 2025.

Crude Oil rose to 64.68 USD/Bbl on September 2, 2025, up 1.04% from the previous day. Over the past month, Crude Oil's price has fallen 2.44%, and is down 12.67% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Crude Oil - values, historical data, forecasts and news - updated on September of 2025.

Graph and download economic data for 30-Year Expected Inflation (EXPINF30YR) from Jan 1982 to Aug 2025 about 30-year, projection, inflation, and USA.

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.

The 10-year treasury constant maturity rate in the U.S. is forecast to increase by *** percentage points by 2027, while the 30-year fixed mortgage rate is expected to fall by *** percentage points. From *** percent in 2024, the average 30-year mortgage rate is projected to reach *** percent in 2027.

The yield on US 30 Year Bond Yield eased to 4.95% on September 2, 2025, marking a 0.01 percentage point decrease from the previous session. Over the past month, the yield has edged up by 0.16 points and is 0.83 points higher than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. United States 30 Year Bond Yield - values, historical data, forecasts and news - updated on September of 2025.

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 .

Analysis of ‘Time Series Forecasting with Yahoo Stock Price ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/arashnic/time-series-forecasting-with-yahoo-stock-price on 30 September 2021.

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

Context

Stocks and financial instrument trading is a lucrative proposition. Stock markets across the world facilitate such trades and thus wealth exchanges hands. Stock prices move up and down all the time and having ability to predict its movement has immense potential to make one rich. Stock price prediction has kept people interested from a long time. There are hypothesis like the Efficient Market Hypothesis, which says that it is almost impossible to beat the market consistently and there are others which disagree with it.

There are a number of known approaches and new research going on to find the magic formula to make you rich. One of the traditional methods is the time series forecasting. Fundamental analysis is another method where numerous performance ratios are analyzed to assess a given stock. On the emerging front, there are neural networks, genetic algorithms, and ensembling techniques.

Another challenging problem in stock price prediction is Black Swan Event, unpredictable events that cause stock market turbulence. These are events that occur from time to time, are unpredictable and often come with little or no warning.

A black swan event is an event that is completely unexpected and cannot be predicted. Unexpected events are generally referred to as black swans when they have significant consequences, though an event with few consequences might also be a black swan event. It may or may not be possible to provide explanations for the occurrence after the fact – but not before. In complex systems, like economies, markets and weather systems, there are often several causes. After such an event, many of the explanations for its occurrence will be overly simplistic.

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New bleeding age state-of-the-art deep learning models stock predictions is overcoming such obstacles e.g. "Transformer and Time Embeddings". An objectives are to apply these novel models to forecast stock price.

Content

Stock price prediction is the task of forecasting the future value of a given stock. Given the historical daily close price for S&P 500 Index, prepare and compare forecasting solutions. S&P 500 or Standard and Poor's 500 index is an index comprising of 500 stocks from different sectors of US economy and is an indicator of US equities. Other such indices are the Dow 30, NIFTY 50, Nikkei 225, etc. For the purpose of understanding, we are utilizing S&P500 index, concepts, and knowledge can be applied to other stocks as well.

Dataset

The historical stock price information is also publicly available. For our current use case, we will utilize the pandas_datareader library to get the required S&P 500 index history using Yahoo Finance databases. We utilize the closing price information from the dataset available though other information such as opening price, adjusted closing price, etc., are also available. We prepare a utility function get_raw_data() to extract required information in a pandas dataframe. The function takes index ticker name as input. For S&P 500 index, the ticker name is ^GSPC. The following snippet uses the utility function to get the required data.(See Simple LSTM Regression)

Features and Terminology: In stock trading, the high and low refer to the maximum and minimum prices in a given time period. Open and close are the prices at which a stock began and ended trading in the same period. Volume is the total amount of trading activity. Adjusted values factor in corporate actions such as dividends, stock splits, and new share issuance.

Starter Kernel(s)

• Simple LSTM Regression

Acknowledgements

Mining and updating of this dateset will depend upon Yahoo Finance .

Inspiration

Sort of variation of sequence modeling and bleeding age e.g. attention can be applied for research and forecasting

Some Readings

• Applications of deep learning in stock market prediction: recent progress
• Stock predictions with state-of-the-art Transformer and Time Embeddings
• https://arxiv.org/pdf/1712.02136.pdf
• https://catanacapital.com/blog/unpredictable-black-swan-event-stock-market/
• https://par.nsf.gov/servlets/purl/10149715
• https://arxiv.org/pdf/1712.02136.pdf

*If you download and find the data useful your upvote is an explicit feedback for future works*

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

The U.S. Commercial Vehicle Market size was valued at USD 581.31 USD Billion in 2023 and is projected to reach USD 1161.96 USD Billion by 2032, exhibiting a CAGR of 10.4 % during the forecast period. A commercial vehicle is an automobile that is used for business purposes and not for personal uses. Some of the familiar uses of commercial vehicles include transporting cargo, machinery, or people for business reasons. These vehicles include trucks, vans, buses, and trailers for commercial use, all of which are designed uniquely to suit business necessities. Commercial vehicles often have powertrain systems such as powerful engines, structural framework, and body such as extra car capacity for carrying goods and easy loading and offloading. In general, there are several advantages of using commercial vehicles, these are higher efficiency, affordable transport services, as well as the ability to do more business. Current trends in the US market can be attributed to the customer’s inclinations towards green solutions and innovations in technology preference the technological usage of trucks and vans in an environmentally responsible manner due to certain environmental policies that have been passed to curb on emission and fuel consumption. Recent developments include: August 2023 – BYD | RIDE delivered two K7M 30’ battery-electric buses to the City of Burlington in North Carolina to serve the passengers of its Link Transit Fleet. The 30-foot buses can accommodate up to 22 passengers and are equipped with the industry’s safest batteries, providing a smooth, quiet, and sustainable ride throughout the city., June 2023 – General Motors Co. acquired ALGOLiON Ltd., an Israel-based battery software startup, for an undisclosed amount. The software uses data streams from EV battery management systems to identify anomalies in battery performance to ensure proper vehicle health management and provide early detection of battery hazards, including thermal runaway propagation events. , May 2023 – Scania announced to reshape its bus and coach business to provide customers with competitive and sustainable mobility solutions and secure profitable growth in a changing market environment., March 2022 – Volvo Trucks received an order of 50 Volvo VNR Electric Trucks for WattEV's Truck-as-a-Service start-up. The Volvo VNR Electric trucks operate on routes between the Inland Empire, California's San Joaquin Valley, and the Ports of Long Beach and Los Angeles., September 2021 - Ford invested USD 11 billion to set up several plants to produce electric vehicle parts. The company also invested in new assembly plants to build all-electric F-series trucks and three battery plants, including factories in Tennessee & Kentucky.. Key drivers for this market are: Increasing Demand for Forged Products in Power, Agriculture, Aerospace, and Defense to Drive Industry Expansion. Potential restraints include: High Maintenance Cost May Limit the Market Growth. Notable trends are: Rising Adoption of Automation in Manufacturing to Drive Market Growth.

This graph shows a forecast of the gross domestic product of the United States of America for fiscal years 2024 to 2034. GDP refers to the market value of all final goods and services produced within a country in a given period. According to the CBO, the United States GDP will increase steadily over the next decade from 28.18 trillion U.S. dollars in 2023 to 41.65 trillion U.S. dollars in 2034. The annual GDP of the United States for recent years can be found here. Also, view the monthly inflation rate for the country.

The Gross Domestic Product (GDP) in the United States expanded 3.30 percent in the second quarter of 2025 over the previous quarter. This dataset provides the latest reported value for - United States GDP Growth Rate - plus previous releases, historical high and low, short-term forecast and long-term prediction, economic calendar, survey consensus and news.

Forecast: Import of Weighing Machinery Having a Capacity of 30-5000 Kg to the US 2024 - 2028 Discover more data with ReportLinker!

The number of U.S. home sales in the United States declined in 2024, after soaring in 2021. A total of four million transactions of existing homes, including single-family, condo, and co-ops, were completed in 2024, down from 6.12 million in 2021. According to the forecast, the housing market is forecast to head for recovery in 2025, despite transaction volumes expected to remain below the long-term average. Why have home sales declined? The housing boom during the coronavirus pandemic has demonstrated that being a homeowner is still an integral part of the American dream. Nevertheless, sentiment declined in the second half of 2022 and Americans across all generations agreed that the time was not right to buy a home. A combination of factors has led to house prices rocketing and making homeownership unaffordable for the average buyer. A survey among owners and renters found that the high home prices and unfavorable economic conditions were the two main barriers to making a home purchase. People who would like to purchase their own home need to save up a deposit, have a good credit score, and a steady and sufficient income to be approved for a mortgage. In 2022, mortgage rates experienced the most aggressive increase in history, making the total cost of homeownership substantially higher. Are U.S. home prices expected to fall? The median sales price of existing homes stood at 413,000 U.S. dollars in 2024 and was forecast to increase slightly until 2026. The development of the S&P/Case Shiller U.S. National Home Price Index shows that home prices experienced seven consecutive months of decline between June 2022 and January 2023, but this trend reversed in the following months. Despite mild fluctuations throughout the year, home prices in many metros are forecast to continue to grow, albeit at a much slower rate.

The Regional Ocean Forecast System (ROFS) was developed jointly by the Ocean Modeling Branch of the National Weather Service's Environmental Modeling Center, the National Ocean Service's Coast Survey Development Lab, Princeton University, and Naval Oceanographic Office (NAVOCEANO). ROFS is based on a hydrodynamic, three-dimensional ocean circulation model (Princeton Ocean Model) which simulates temperature, salinity, surface elevation, and currents for a region off the U.S. East Coast from ~30 to 47N and out to 50W. The model is driven at the ocean surface boundary by heat, moisture, and momentum fluxes provided by NCEP's Eta mesoscale atmospheric forecast model. The ocean model is driven along its open (that is, southern and eastern) boundaries by climatological estimates of temperature, salinity, and transport. The spatial resolution of the model varies from approximately 20km offshore to about 10km nearshore. The coastal boundary corresponds to the location of the 10m isobath. In the vertical, an 18-layer sigma (terrain-following) coordinate system is used with at least half the layers concentrated in the upper 100m. Tidal forcing is included in the model.

The forecast cycle generates regional ocean forecasts out to 48 hours. Surface forcing is obtained from the 3-hourly surface fields from NCEP's Eta mesoscale atmospheric prediction model. [This abstract was obtained from the ROFS website at http://polar.wwb.noaa.gov/cofs/Description.html#OM on June 23, 2004.]

By 2034, the gross federal debt of the United States is projected to be about 54.39 trillion U.S. dollars. This would be an increase of around 21 trillion U.S. dollars from 2023, when the federal debt was around 33 trillion U.S. dollars.

The federal debt of the U.S.

The federal debt, also called the national debt or public debt, is the amount of debt held by the United States government. This debt may be to other countries, or to different departments within the government itself. The public debt of the United States has increased significantly over the past 30 years, as it was around 3.2 trillion U.S. dollars in 1990 and surpassed 30 trillion dollars for the first time in 2022. When broken down per capita, the national debt amounted to about 80,885 U.S. dollars of debt per person in the United States in 2021.

The problem of the federal debt

Over the past decade, the federal debt limit in the United States has increased significantly. The U.S. debt ceiling can only be changed by an act of Congress which is then signed by the president. The raising of the ceiling has become a recurring political issue in recent years, especially during times when the Presidency and chambers of Congress are controlled by different parties.

The debt ceiling is a tool that allows the Treasury to issue bonds without congressional approval, allowing for efficiency in the way that the government pays for programs and services. It is thought to be further valuable in that it keeps federal finances in check. However, when the two parties are unable to come to an agreement on raising the debt ceiling, the government comes to a shutdown because they can no longer fund themselves. The Republican Party in particular often positions itself against raising the federal debt ceiling, characterizing themselves as the party of fiscal conservativism. However, analyses have shown that both parties have contributed to the country's debt in almost equal measures.

The total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, reaching *** zettabytes in 2024. Over the next five years up to 2028, global data creation is projected to grow to more than *** zettabytes. In 2020, the amount of data created and replicated reached a new high. The growth was higher than previously expected, caused by the increased demand due to the COVID-19 pandemic, as more people worked and learned from home and used home entertainment options more often. Storage capacity also growing Only a small percentage of this newly created data is kept though, as just * percent of the data produced and consumed in 2020 was saved and retained into 2021. In line with the strong growth of the data volume, the installed base of storage capacity is forecast to increase, growing at a compound annual growth rate of **** percent over the forecast period from 2020 to 2025. In 2020, the installed base of storage capacity reached *** zettabytes.

Prices for US 100 Tech Index including live quotes, historical charts and news. US 100 Tech Index was last updated by Trading Economics this September 1 of 2025.

The U.S. Geological Survey has been forecasting sea-level rise impacts on the landscape to evaluate where coastal land will be available for future use. The purpose of this project is to develop a spatially explicit, probabilistic model of coastal response for the Northeastern U.S. to a variety of sea-level scenarios that take into account the variable nature of the coast and provides outputs at spatial and temporal scales suitable for decision support. Model results provide predictions of adjusted land elevation ranges (AE) with respect to forecast sea-levels, a likelihood estimate of this outcome (PAE), and a probability of coastal response (CR) characterized as either static or dynamic. The predictions span the coastal zone vertically from -12 meters (m) to 10 m above mean high water (MHW). Results are produced at a horizontal resolution of 30 meters for four decades (the 2020s, 2030s, 2050s and 2080s). Adjusted elevations and their respective probabilities are generated using regional geospatial datasets of current sea-level forecasts, vertical land movement rates, and current elevation data. Coastal response type predictions incorporate adjusted elevation predictions with land cover data and expert knowledge to determine the likelihood that an area will be able to accommodate or adapt to water level increases and maintain its initial land class state or transition to a new non-submerged state (dynamic) or become submerged (static). Intended users of these data include scientific researchers, coastal planners, and natural resource management communities.

The U.S. Geological Survey has been forecasting sea-level rise impacts on the landscape to evaluate where coastal land will be available for future use. The purpose of this project is to develop a spatially explicit, probabilistic model of coastal response for the Northeastern U.S. to a variety of sea-level scenarios that take into account the variable nature of the coast and provides outputs at spatial and temporal scales suitable for decision support. Model results provide predictions of adjusted land elevation ranges (AE) with respect to forecast sea-levels, a likelihood estimate of this outcome (PAE), and a probability of coastal response (CR) characterized as either static or dynamic. The predictions span the coastal zone vertically from -12 meters (m) to 10 m above mean high water (MHW). Results are produced at a horizontal resolution of 30 meters for four decades (the 2020s, 2030s, 2050s and 2080s). Adjusted elevations and their respective probabilities are generated using regional geospatial datasets of current sea-level forecasts, vertical land movement rates, and current elevation data. Coastal response type predictions incorporate adjusted elevation predictions with land cover data and expert knowledge to determine the likelihood that an area will be able to accommodate or adapt to water level increases and maintain its initial land class state or transition to a new non-submerged state (dynamic) or become submerged (static). Intended users of these data include scientific researchers, coastal planners, and natural resource management communities.