!!EXCLUSIVE!! Download Sensex Historical Data
Daryl Kowal
Stocks: Real-time U.S. stock quotes reflect trades reported through Nasdaq only; comprehensive quotes and volume reflect trading in all markets and are delayed at least 15 minutes. International stock quotes are delayed as per exchange requirements. Fundamental company data and analyst estimates provided by FactSet. Copyright FactSet Research Systems Inc. All rights reserved. Source: FactSet
Data are provided 'as is' for informational purposes only and are not intended for trading purposes. FactSet (a) does not make any express or implied warranties of any kind regarding the data, including, without limitation, any warranty of merchantability or fitness for a particular purpose or use; and (b) shall not be liable for any errors, incompleteness, interruption or delay, action taken in reliance on any data, or for any damages resulting therefrom. Data may be intentionally delayed pursuant to supplier requirements.
The data collection effort about investor attitudes that I have been conducting since 1989 has now resulted in a group of Stock Market Confidence Indexes produced by the Yale School of Management. These data are collected in collaboration with Fumiko Kon-Ya and Yoshiro Tsutsui of Japan. Some of our earlier results are also noteworthy: Results of Surveys about Stock Market Speculation 12/99.
Stock market data used in my book, Irrational Exuberance [Princeton University Press 2000, Broadway Books 2001, 2nd ed., 2005] are available for download, U.S. Stock Markets 1871-Present and CAPE Ratio. This data set consists of monthly stock price, dividends, and earnings data and the consumer price index (to allow conversion to real values), all starting January 1871. The price, dividend, and earnings series are from the same sources as described in Chapter 26 of my earlier book (Market Volatility [Cambridge, MA: MIT Press, 1989]), although now I use monthly data, rather than annual data. Monthly dividend and earnings data are computed from the S&P four-quarter totals for the quarter since 1926, with linear interpolation to monthly figures. Dividend and earnings data before 1926 are from Cowles and associates (Common Stock Indexes, 2nd ed. [Bloomington, Ind.: Principia Press, 1939]), interpolated from annual data. Stock price data are monthly averages of daily closing prices through January 2000, the last month available as this book goes to press. The CPI-U (Consumer Price Index-All Urban Consumers) published by the U.S. Bureau of Labor Statistics begins in 1913; for years before 1913 1 spliced to the CPI Warren and Pearson's price index, by multiplying it by the ratio of the indexes in January 1913. December 1999 and January 2000 values for the CPI-Uare extrapolated. See George F. Warren and Frank A. Pearson, Gold and Prices (New York: John Wiley and Sons, 1935). Data are from their Table 1, pp. 1114.
As of September 2018, I now also include an alternative version of CAPE that is somewhat different. As documented in Bunn & Shiller (2014) and Jivraj and Shiller (2017), changes in corporate payout policy (i. e. share repurchases rather than dividends have now become a dominant approach in the United States for cash distribution to shareholders) may affect the level of the CAPE ratio through changing the growth rate of earnings per share. This subsequently may affect the average of the real earnings per share used in the CAPE ratio. A total return CAPE corrects for this bias through reinvesting dividends into the price index and appropriately scaling the earnings per share.
The U.S. Home Price Indices, which Karl Case and I originally developed, which were produced 1991-2002 by our firm Case Shiller Weiss, Inc. under the direction of Allan Weiss, are now produced by CoreLogic under the direction of Linda Ladner and David Stiff. Many of these price indices, including twenty cities, low- medium- and high- tier home price indices, condominium indices, and a U.S. national index, are now published as the S&P/CoreLogic/Case-Shiller Home Price Indices by Standard & Poor's, and are available to the public on Standard & Poor's web site. Eleven of these indices are traded at the Chicago Mercantile Exchange. Information on these futures markets can be found at
Historical housing market data used in my book, Irrational Exuberance [Princeton University Press 2000, Broadway Books 2001, 2nd edition, 2005], showing home prices since 1890 are available for download and updated monthly: US Home Prices 1890-Present.
An annual series is also available here, long term stock, bond, interest rate and consumption data since 1871 that I in collaboration with several colleagues collected to examine long term historical trends in the US market. This is Chapter 26 from my book Market Volatility, 1989, and revised and updated.
Karl Case and I have collected some data sets on prices of houses, which show for a sample of homes that sold twice between 1970 and 1986 in each of four cities Atlanta, Chicago, Dallas, and Oakland, the first sale price, second sale price, first sale date, and second sale date. These data are somewhat outdated, and of interest only to researchers.
CBO regularly publishes data to accompany some of its key reports. These data have been published in the Budget and Economic Outlook and Updates and in their associated supplemental material, except for that from the Long-Term Budget Outlook.
Revenue Projections, by CategoryProjections of revenues by category, estimates of the effects of extending tax provisions scheduled to expire within ten years, and estimates of selected policy options affecting revenues. Starting in April 2018, additional information on revenue projection errors and a listing of legislation with significant impacts on federal revenues have been added to the data.
Historical Data and Economic ProjectionsData on output, prices, labor market measures, interest rates, income, potential GDP, and its underlying inputs from 1949 through the most recent year completed, in comma-separated values (CSV) files. In May 2020, CBO published selected historical economic data.
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FINRA collects the required data via FINRA's Customer Margin Balance Form. The data is compiled in aggregate form, made available below and in Excel format via the download link on this page. See Margin Balance Reporting: Frequently Asked Questions under FINRA Rule 4521(d) (published April 13, 2021) for additional guidance on the calculation of these balances. Monthly variations in the reported balances may be partially due to member firms modifying the methods used in determining the balances reported to FINRA since the publication of the FAQ. Please note, FINRA generally publishes updates to the Margin Statistics on the third week of the month following the reference month. FINRA does not provide the data outside of this webpage and data feeds are not available.
1As of February 2010, data are collected pursuant to FINRA Rule 4521 and are aggregated across all member firms, regardless of whether the firm was designated to NASD or the New York Stock Exchange (NYSE) before the consolidation of NASD and the member firm regulation operations of NYSE Regulation in July 2007 that created FINRA.
Usage restrictions: The data is not for financial industry professional use or use by other professionals at non-financial firms (including government entities). Professional use may be subject to additional licensing fees from a third-party data provider.
Historical data cannot be downloaded or accessed via the Sheets API or Apps Script. If you attempt to do so, you'll see a #N/A error in place of the values in the corresponding cells of your spreadsheet.
The STOCKHISTORY function retrieves historical data about a financial instrument and loads it as an array, which will spill if it's the final result of a formula. This means that Excel will dynamically create the appropriate sized array range when you press ENTER.
Function returns historical price data about the financial instrument corresponding to this value. Enter a ticker symbol in double quotes (e.g., "MSFT") or a reference to a cell containing the Stocks data type. This will pull data from the default exchange for the instrument. You can also refer to a specific exchange by entering a 4-character ISO market identifier code (MIC), followed by a colon, followed by the ticker symbol (e.g., "XNAS:MSFT"). Learn more about our data sources.
The earliest date for which data is retrieved. Note that if interval is not 0 (daily), the first data point may be earlier than the start_date provided - it will be the first date of the period requested.
Please note that while some financial instruments may be available as Stocks data types, the historical information will not be available. For example, this is the case for most popular Index Funds including the S&P 500.
If you want to get the highest high over a 3-month period, it is faster to use a monthly interval than a daily or weekly interval. For example, =MAX(STOCKHISTORY("XNAS:MSFT", "1/1/2022", "3/1/2022", 2, 0, 3)) will calculate the maximum value of 3 datapoints (one for each month), data only with no headers, for the highest trading value for each month. If instead the formula used a weekly or daily interval, you would get the same result but there would be many more datapoints used in the calculation which can lead to reduced performance.
If you want to see a 52-week high or low, it is often faster to use a Stocks data type, which has those properties readily available. For example, convert "xnas:msft" to a stock data type in cell A1, and in cell B1 you can write the formula =A1.[52 week high] to get the value. You can also configure your workbook to automatically refresh that value as described here.
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