Prices for US Bank Index including live quotes, historical charts and news. US Bank Index was last updated by Trading Economics this September 14 of 2025.

Stock prices of selected regional banks in the United States plummeted in March 2023, as investor confidence dropped due to economic uncertainties. Silicon Valley Bank failed on 10th of March 2023. The stock prices of the displayed banks fell particularly sharply on and after that day, which was the second largest bank failure since 2001. The observed period was particularly devastating for First Republic, whose stock price was more than ** percent lower on the 20th of March than on the first day of the month.

Graph and download economic data for Monetary Authority; Federal Reserve Bank Stock; Liability, Level (MAFRBIA027N) from 1945 to 2024 about monetary authorities, stocks, IMA, liabilities, banks, depository institutions, and USA.

As of January 14, 2025, the market capitalization of ************** amounted to ****** billion U.S. dollars, making it the largest bank in the United States. By this measure, the second-largest bank was ***************, followed by ***********. ************** and *************** are also the two largest banks in the world by market capitalization. What is market capitalization? Market capitalization, or stock market value, is the total value of shares issued by a publicly traded company. It reflects the equity value of a company. Market cap is calculated by multiplying the market price of one share by the number of shares outstanding. For example, the market cap of Bank of America can be calculated by multiplying its share price by the number of shares it has issued. Other measures of company size Total assets also allow to determine the size of a bank. Instead of focusing on the stock price, this metric measures the size of the bank’s operations by counting the size of its balance sheet. Bank revenue and income are also common indicators used to compare banks and their performance.

United States US: Stocks Traded: Total Value data was reported at 39,785.881 USD bn in 2017. This records a decrease from the previous number of 42,071.330 USD bn for 2016. United States US: Stocks Traded: Total Value data is updated yearly, averaging 17,934.293 USD bn from Dec 1984 (Median) to 2017, with 34 observations. The data reached an all-time high of 47,245.496 USD bn in 2008 and a record low of 1,108.421 USD bn in 1984. United States US: Stocks Traded: Total Value data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Financial Sector. The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

Graph and download economic data for Monetary Authority; Federal Reserve Bank Stock; Liability, Transactions (BOGZ1FU713164003A) from 1946 to 2024 about monetary authorities, stocks, transactions, liabilities, banks, depository institutions, and USA.

Bank Of America stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

Stock prices of the largest European banks fell sharply in March 2023, as the collapse of Silicon Valley Bank and First Republic in the U.S. crumbled confidence in the sector. Shortly after the second and third largest U.S. bank failures, Credit Suisse went under, which pushed the stock prices of leading European banks down further. Towards the end of the month, stock prices increased notably, but remained well below prices at the start of March.

Dataset

This dataset was created by Ranjit Mishra

Released under CC0: Public Domain

Contents

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.

Dow Jones U.S. Banks: Banking on a Brighter Future?

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 price of Bank of America shares traded on the New York Stock Exchange fluctuated significantly during the period from 1990 to 2023, as of year-end. The price of one Bank of America share amounted to ***** U.S. dollars in 2021, which was the highest price since 2006. At the end of 2022, however, the share price dropped to ***** U.S. dollars, a significant decrease compared to a year earlier. At the end of 2023, the share price of the bank was ***** U.S. dollars.

Graph and download economic data for Monetary Authority; Federal Reserve Bank Stock; Liability, Transactions (BOGZ1FU713164003Q) from Q4 1946 to Q2 2025 about monetary authorities, stocks, transactions, liabilities, banks, depository institutions, and USA.

United States US: Stocks Traded: Total Value: % of GDP data was reported at 205.181 % in 2017. This records a decrease from the previous number of 225.893 % for 2016. United States US: Stocks Traded: Total Value: % of GDP data is updated yearly, averaging 155.485 % from Dec 1984 (Median) to 2017, with 34 observations. The data reached an all-time high of 320.992 % in 2008 and a record low of 27.431 % in 1984. United States US: Stocks Traded: Total Value: % of GDP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Financial Sector. The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values.; ; World Federation of Exchanges database.; Weighted average; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

Common-Stock-Shares-Outstanding Time Series for U.S. Bancorp. U.S. Bancorp, a financial services holding company, provides various financial services to individuals, businesses, institutional organizations, governmental entities, and other financial institutions in the United States. The company operates through Wealth, Corporate, Commercial and Institutional Banking; Consumer and Business Banking; Payment Services; and Treasury and Corporate Support segments. It offers depository services, including checking accounts, savings accounts, and time certificate contracts; and lending services, such as traditional credit products and credit card services, lease financing and import/export trade, asset-backed lending, agricultural finance, and other products. The company also provides cash management, capital markets, and trust and investment management services; and ancillary services comprising capital markets, treasury management, and receivable lock-box collection services to corporate and governmental entity customers. In addition, it offers asset management and fiduciary services for individuals, estates, foundations, business corporations, and charitable organizations; and investment and insurance products to its customers principally within its domestic markets, as well as fund administration services to mutual and other funds. Further, the company provides corporate and purchasing card, and corporate trust services; and credit card services, merchant and ATM processing, mortgage banking, insurance, brokerage and leasing services. U.S. Bancorp was founded in 1863 and is headquartered in Minneapolis, Minnesota.

The Dow Jones U.S. Banks index is expected to continue its upward trend in the short term, with a moderate level of risk. Positive economic fundamentals and strong bank earnings are expected to drive the index higher. However, rising interest rates and geopolitical uncertainty could pose potential headwinds, leading to volatility and potential downside risks.

In 2024, ** percent of adults in the United States invested in the stock market. This figure has remained steady over the last few years, and is still below the levels before the Great Recession, when it peaked in 2007 at ** percent. What is the stock market? The stock market can be defined as a group of stock exchanges, where investors can buy shares in a publicly traded company. In more recent years, it is estimated an increasing number of Americans are using neobrokers, making stock trading more accessible to investors. Other investments A significant number of people think stocks and bonds are the safest investments, while others point to real estate, gold, bonds, or a savings account. Since witnessing the significant one-day losses in the stock market during the Financial Crisis, many investors were turning towards these alternatives in hopes for more stability, particularly for investments with longer maturities. This could explain the decrease in this statistic since 2007. Nevertheless, some speculators enjoy chasing the short-run fluctuations, and others see value in choosing particular stocks.

Stock Price Time Series for The Bank of New York Mellon Corporation. The Bank of New York Mellon Corporation provides a range of financial products and services in the United States and internationally. It operates through Securities Services, Market and Wealth Services, Investment and Wealth Management, and Other segments. The Securities Services segment offers custody, trust and depositary, accounting, exchange-traded funds, middle-office solutions, transfer agency, services for private equity and real estate funds, foreign exchange, securities lending, liquidity/lending services, and data analytics. This segment also provides trustee, paying agency, fiduciary, escrow and other financial, issuer, and support services for brokers and investors. The Market and Wealth Services segment offers clearing and custody, investment, wealth and retirement solutions, technology and enterprise data management, trading, and prime brokerage services. This segment also provides integrated cash management solutions, including payments, foreign exchange, liquidity management, receivables processing, payables management, and trade finance, as well as U.S. government and global clearing, and tri-party services. The Investment and Wealth Management segment offers investment management strategies, investment products distribution, investment management, custody, wealth and estate planning, private banking, investment, and information management services. The Other segment provides leasing, corporate treasury, derivative and other trading, corporate and bank-owned life insurance, tax credit investment, other corporate investment, and business exit services. The company serves central banks and sovereigns, financial institutions, asset managers, insurance companies, corporations, local authorities and high net-worth individuals, and family offices. The Bank of New York Mellon Corporation was founded in 1784 and is headquartered in New York, New York.

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.

U.S. Bank's (USB) Banking on Growth: Worth the Investment?

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

United States US: Stocks Traded: Turnover Ratio of Domestic Shares data was reported at 116.078 % in 2017. This records an increase from the previous number of 94.719 % for 2016. United States US: Stocks Traded: Turnover Ratio of Domestic Shares data is updated yearly, averaging 114.857 % from Dec 1984 (Median) to 2017, with 34 observations. The data reached an all-time high of 407.630 % in 2008 and a record low of 51.444 % in 1991. United States US: Stocks Traded: Turnover Ratio of Domestic Shares data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Financial Sector. Turnover ratio is the value of domestic shares traded divided by their market capitalization. The value is annualized by multiplying the monthly average by 12.; ; World Federation of Exchanges database.; Weighted average; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

Dataset Description: 34-year Daily Stock Data (1990-2024)

Context and Inspiration

This dataset captures historical financial market data and macroeconomic indicators spanning over three decades, from 1990 onwards. It is designed for financial analysis, time series forecasting, and exploring relationships between market volatility, stock indices, and macroeconomic factors. This dataset is particularly relevant for researchers, data scientists, and enthusiasts interested in studying: - Volatility forecasting (VIX) - Stock market trends (S&P 500, DJIA, HSI) - Macroeconomic influences on markets (joblessness, interest rates, etc.) - The effect of geopolitical and economic uncertainty (EPU, GPRD)

Sources

The data has been aggregated from a mix of historical financial records and publicly available macroeconomic datasets: - VIX (Volatility Index): Chicago Board Options Exchange (CBOE). - Stock Indices (S&P 500, DJIA, HSI): Yahoo Finance and historical financial databases. - Volume Data: Extracted from official exchange reports. - Macroeconomic Indicators: Bureau of Economic Analysis (BEA), Federal Reserve, and other public records. - Uncertainty Metrics (EPU, GPRD): Economic Policy Uncertainty Index and Global Policy Uncertainty Database.

Columns

1. dt: Date of observation in YYYY-MM-DD format.
2. vix: VIX (Volatility Index), a measure of expected market volatility.
3. sp500: S&P 500 index value, a benchmark of the U.S. stock market.
4. sp500_volume: Daily trading volume for the S&P 500.
5. djia: Dow Jones Industrial Average (DJIA), another key U.S. market index.
6. djia_volume: Daily trading volume for the DJIA.
7. hsi: Hang Seng Index, representing the Hong Kong stock market.
8. ads: Aruoba-Diebold-Scotti (ADS) Business Conditions Index, reflecting U.S. economic activity.
9. us3m: U.S. Treasury 3-month bond yield, a short-term interest rate proxy.
10. joblessness: U.S. unemployment rate, reported as quartiles (1 represents lowest quartile and so on).
11. epu: Economic Policy Uncertainty Index, quantifying policy-related economic uncertainty.
12. GPRD: Geopolitical Risk Index (Daily), measuring geopolitical risk levels.
13. prev_day: Previous day’s S&P 500 closing value, added for lag-based time series analysis.

Key Features

• Cross-Market Analysis: Compare U.S. markets (S&P 500, DJIA) with international benchmarks like HSI.
• Macroeconomic Insights: Assess how external factors like joblessness, interest rates, and economic uncertainty affect markets.
• Temporal Scope: Longitudinal data facilitates trend analysis and machine learning model training.

Potential Use Cases

• Forecasting market indices using machine learning or statistical models.
• Building volatility trading strategies with VIX Futures.
• Economic research on relationships between policy uncertainty and market behavior.
• Educational material for financial data visualization and analysis tutorials.

Feel free to use this dataset for academic, research, or personal projects.