View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

Jordan Amman Stock Exchange: Index: Free Float Weighted Index: Tobacco data was reported at 1,830.600 NA in Oct 2024. This records an increase from the previous number of 1,627.200 NA for Sep 2024. Jordan Amman Stock Exchange: Index: Free Float Weighted Index: Tobacco data is updated monthly, averaging 14,934.513 NA from Jul 2013 (Median) to Oct 2024, with 135 observations. The data reached an all-time high of 29,546.557 NA in Jan 2021 and a record low of 1,627.200 NA in Sep 2024. Jordan Amman Stock Exchange: Index: Free Float Weighted Index: Tobacco data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s Jordan – Table JO.EDI.SE: Amman Stock Exchange: Monthly.

Our Financial API provides access to a vast collection of historical financial statements for over 50,000+ companies listed on major exchanges. With this powerful tool, you can easily retrieve balance sheets, income statements, and cash flow statements for any company in our extensive database. Stay informed about the financial health of various organizations and make data-driven decisions with confidence. Our API is designed to deliver accurate and up-to-date financial information, enabling you to gain valuable insights and streamline your analysis process. Experience the convenience and reliability of our company financial API today.

Free Float Weighted Index: ASE: Services: Health Care data was reported at 936.261 Dec1999=1000 in Jun 2018. This records an increase from the previous number of 899.613 Dec1999=1000 for May 2018. Free Float Weighted Index: ASE: Services: Health Care data is updated monthly, averaging 881.461 Dec1999=1000 from Dec 1999 (Median) to Jun 2018, with 223 observations. The data reached an all-time high of 2,593.788 Dec1999=1000 in Apr 2005 and a record low of 537.356 Dec1999=1000 in May 2003. Free Float Weighted Index: ASE: Services: Health Care data remains active status in CEIC and is reported by Amman Stock Exchange. The data is categorized under Global Database’s Jordan – Table JO.Z001: Amman Stock Exchange: Free Float Weighted Index.

Jordan Free Float Weighted Index: ASE: General data was reported at 2,126.785 Dec1999=1000 in 2017. This records a decrease from the previous number of 2,170.291 Dec1999=1000 for 2016. Jordan Free Float Weighted Index: ASE: General data is updated yearly, averaging 2,150.890 Dec1999=1000 from Dec 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 4,259.706 Dec1999=1000 in 2005 and a record low of 813.343 Dec1999=1000 in 2000. Jordan Free Float Weighted Index: ASE: General data remains active status in CEIC and is reported by Amman Stock Exchange. The data is categorized under Global Database’s Jordan – Table JO.Z002: Amman Stock Exchange: Free Float Weighted Index: Annual.

Custommade Historical Financial Data For 230M Companies Worldwide: - Data from 2017, 2018, 2019, 2020 & 2021 - Includes turnover, employee size. - Custommade based on geographical location, turnover range, employee range and industry type - Standardized database for all countries

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We compile raw data from the Datastream database for all stocks traded on the Tokyo Stock Exchance, Osaka Exchange, Fukuoka Stock Exchange, Nagoya Stock Exchange and Sapporo Securities Exchange. Particularly, we collect the following data series, on a monthly basis: (i) total return index (RI series), (ii) market value (MV series), (iii) market-to-book equity (PTBV series), and (iv) primary SIC codes. Following Griffing et al. (2010), we exclude non-common equity securities from Datastream data. Additionally, we remove all companies with less than 12 observations in RI series for the period under analysis. Hence, our sample comprises 5,627 stocks, considering all companies that started trading or were delisted in the period under analysis. We use the three-month Treasury Bill rate for Japan, as provided by the OECD database, as a proxy for the risk-free rate. Accordingly, the dataset comprises the following series:

1. Japan_25_Portfolios_MV_PTBV_M: Monthly returns for 25 size-book-to-market equity portfolios, following the Fama and French (1993) methodology. (Raw data source: Datastream database)
2. Japan_20_Portfolios_MOM_M: Monthly returns for 20 momentum portfolios rebalanced in June of each year. (Raw data source: Datastream database)
3. Japan_61_Portfolios_SECTOR_M: Monthly returns for 61 industry portfolios. (Raw data source: Datastream database)
4. Japan_RF_M: Three-month Treasury Bill rate for Japan. (Raw data source: OECD)
5. Japan_C_Q: Private final consumption expenditure, in national currency and constant prices, non-seasonally adjusted, for Japan. (Raw data source: OECD)
6. Japan_Trade_Y: Trade openness for Japan, as measured by the variation rate of exports plus imports. (Raw data source: OECD)
7. Japan_RD_Y: Variation rate of R&D investment for Japan. (Raw data source: OECD)
8. Japan_IK_Y: Investment-capital ratio for Japan., determined using the methodology suggested by Cochrane (1991) (Raw data source: OECD)
9. Japan_CCI_M: Consumer confidence index for Japan. (Raw data source: OECD)

REFERENCES:

Cochrane, J.H. (1991), Production-based asset pricing and the link between stock returns and economic fluctuations. The Journal of Finance, 46, 209-237. Fama, E. F. and French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33, 3–56. Griffin, J. M., Kelly, P., and Nardari, F. (2010). Do market efficiency measures yield correct inferences? A comparison of developed and emerging markets. Review of Financial Studies, 23, 3225–3277.

National Stock Number extract includes the current listing of National Stock Numbers (NSNs) , NSN item name and descriptions, and current selling price of each product listed in GSA Advantage and managed by GSA. Each NSN is listed with the vendors description of the item. Some descriptions exceed the standard length and are truncated.

Jordan Free Float Weighted Index: ASE: Financial data was reported at 2,655.005 Dec1999=1000 in Oct 2018. This records a decrease from the previous number of 2,707.905 Dec1999=1000 for Sep 2018. Jordan Free Float Weighted Index: ASE: Financial data is updated monthly, averaging 2,853.262 Dec1999=1000 from Dec 1999 (Median) to Oct 2018, with 227 observations. The data reached an all-time high of 7,665.119 Dec1999=1000 in Nov 2005 and a record low of 782.209 Dec1999=1000 in Aug 2000. Jordan Free Float Weighted Index: ASE: Financial data remains active status in CEIC and is reported by Amman Stock Exchange. The data is categorized under Global Database’s Jordan – Table JO.Z001: Amman Stock Exchange: Free Float Weighted Index.

An excel template with data elements and conventions corresponding to the openLCA unit process data model. Includes LCA Commons data and metadata guidelines and definitions Resources in this dataset:Resource Title: READ ME - data dictionary. File Name: lcaCommonsSubmissionGuidelines_FINAL_2014-09-22.pdfResource Title: US Federal LCA Commons Life Cycle Inventory Unit Process Template. File Name: FedLCA_LCI_template_blank EK 7-30-2015.xlsxResource Description: Instructions: This template should be used for life cycle inventory (LCI) unit process development and is associated with an openLCA plugin to import these data into an openLCA database. See www.openLCA.org to download the latest release of openLCA for free, and to access available plugins.

Graph and download economic data for CBOE Volatility Index: VIX (VIXCLS) from 1990-01-02 to 2025-07-02 about VIX, volatility, stock market, and USA.

S&P 500 index data including level, dividend, earnings and P/E ratio on a monthly basis since 1870. The S&P 500 (Standard and Poor's 500) is a free-float, capitalization-weighted index of the top ...

The RAM Legacy Stock Assessment Database is a compilation of stock assessment results for commercially exploited marine populations from around the world. The RAM Legacy Stock Assessment Database is grateful to the many stock assessment scientists whose work this database is based upon and the many collaborators who recorded the assessment model results for inclusion in the RAM Legacy Stock Assessment Database. Since 2011 the RAM Legacy Data base has been hosted and managed at the University of Washington with financial assistance from a consortium of Seattle-based seafood companies and organizations, and from the Walton Family Foundation. Initial development of the database from 2006-2010 was supported by the Census of Marine Life, Canadian Foundation for Innovation, NCEAS, NSERC, the Smith Conservation Research Fellowship, New Jersey Sea Grant, and the National Science Foundation.

Jordan Free Float Weighted Index: ASE: Services: Media data was reported at 82.856 Dec1999=1000 in Jun 2018. This stayed constant from the previous number of 82.856 Dec1999=1000 for May 2018. Jordan Free Float Weighted Index: ASE: Services: Media data is updated monthly, averaging 1,268.095 Dec1999=1000 from Dec 1999 (Median) to Jun 2018, with 223 observations. The data reached an all-time high of 4,148.347 Dec1999=1000 in Feb 2008 and a record low of 82.856 Dec1999=1000 in Jun 2018. Jordan Free Float Weighted Index: ASE: Services: Media data remains active status in CEIC and is reported by Amman Stock Exchange. The data is categorized under Global Database’s Jordan – Table JO.Z001: Amman Stock Exchange: Free Float Weighted Index.

List of companies in the S&P 500 (Standard and Poor's 500). The S&P 500 is a free-float, capitalization-weighted index of the top 500 publicly listed stocks in the US (top 500 by market cap). The ...

NASCArrays is the Nottingham Arabidopsis Stock Centre''s microarray database. Currently most of the data is for Arabidopsis thaliana experiments run by the NASC Affymetrix Facility. There are also experiments from other species, and experiments run by other centres too. NASCArrays is an Affymetrix microarray database. It contains free Affymetrix microarray data, and also features a series of tools allowing you to query that data in powerful ways. Most of the data currently comes from NASC''s Affymetrix Service. It also includes data from other sources, notably the AtGenExpress project. They currently distribute over 30,000 tubes of seed a year. There are currently the following data mining tools available. All of these tools allow you to type in a gene(s) of interest, and identify experiments or slides that you might be interested in: -Spot History: This tool allows you to see the pattern of gene expression over all slides in the database. Easily identify slides (and therefore experimental treatments) where genes are highly, lowly, or unusually expressed -Two gene scatter plot: This tool allows you to see the pattern of gene expression over all slides for two genes as a scatter plot. If you are interested in two genes, you can find out if they act in tandem, and highlight slides (and therefore experimental conditions) where these two genes behave in an unusual manner. -Gene Swinger: If you have a gene of interest, this tool will show you which experiment the gene expression varied most -Bulk Gene Download: This tool allows you to download the expression of a list of genes over all experiments. You can get all genes over all experiments (the entire database!) from the Super Bulk Gene Download Sponsors: This is a BBSRC funded consortium to provide services to the Arabidopsis community.

The replication data contain MATLAB and GAUSS codes as well as the data required for replication of the results from the paper

1. Monte Carlo Simulation:

Contains codes and data for simulation study from Section 3.

Data:

• MV.mat, MV.txt- monthly data on market capitalization of the 205 stocks of the S&P500 index obtained from DataStream for the period 01.01.1974-01.05.2015

• sp500_edata.mat - monthly data on close prices of components of S&P500 index for the period 01.01.1974-01.05.2015 processed to obtain excess returns using as a risk free return data on the risk free return from French & Fama database. Description of the price data from DataStream: "The ‘current’ prices taken at the close of market are stored each day. These stored prices are adjusted for subsequent capital actions, and this adjusted figure then becomes the default price offered on all Research programs. " Description of the excess return of the market from French & Fama database : "the excess return on the market, value-weight return of all CRSP firms incorporated in the US and listed on the NYSE, AMEX, or NASDAQ that have a CRSP share code of 10 or 11 at the beginning of month t, good shares and price data at the beginning of t, and good return data for t minus theone-month Treasury bill rate (from Ibbotson Associates)." From the latest file two separate data files were created (see CAPMsim.m):

• sp500_stocks.txt, sp500_stocks.mat - monthly data on close prices of 205 components of S&P500 index for the period 01.01.1974-01.05.2015

• FactorData.txt, FactorData.txt - The Fama & French factors from French & Fama database for a period July 1926 - May 2015.

Codes:

• CAPMsim.m - the main code that replicates the Monte Carlo simulation of the artificial market and proxy indexes subject to different types of the measurement error.

• sure.m- obtains the estimated parameters for the SUR system and performs hypothesis testing of the significance of the coefficients.

2. Empirical Application

Contains codes and data for empirical application from Section 4.

Data:

• data1203.txt - 120 monthly observations on the excess returns on 20 random stocks from S&P500, S&P500 index return, DJIA return from DataStream and excess return of the CRSP index from French & Fama database for a period 01/06/2005-01/05/2015.

• data1204.txt - 120 monthly observations on the excess returns on 30 stocks from DJIA, S&P500 index return, DJIA return from DataStream and excess return of the CRSP index from French & Fama database for a period 01/06/2005-01/05/2015.

• DJSTOCKS_60_FF_Z.dat - 60 monthly observations on the excess returns on 30 stocks from DJIA from DataStream and excess return of the CRSP index from French & Fama database for a period 01/06/2010-01/05/2015.

• DJSTOCKS_60_SP_Z.dat - 60 monthly observations on the excess returns on 30 stocks from DJIA and S&P500 index return from DataStream for a period 01/06/2010-01/05/2015.

  • DJSTOCKS_60_DJ_Z.dat - 60 monthly observations on the excess returns on 30 stocks from DJIA and DJIA return from DataStream for a period 01/06/2010-01/05/2015.
  • STOCKS_60_FF_Z.dat - 60 monthly observations on the excess returns on 20 random stocks from S&P500 from DataStream and excess return of the CRSP index from French & Fama database for a period 01/06/2010-01/05/2015.
  • STOCKS_60_SP_Z.dat - 60 monthly observations on the excess returns on 20 random stocks from S&P500 and S&P500 index return from DataStream for a period 01/06/2010-01/05/2015.

• STOCKS_60_DJ_Z.dat - 60 monthly observations on the excess returns on 20 random stocks from S&P500 and DJIA return from DataStream for a period 01/06/2010-01/05/2015.

  Description of the variables in the data sets:

• Z_1, Z_2,...,Z_20,..., Z_30 - returns of individual stocks depending on the data set.

• For calculation of the returns adjusted prices from DataStream were used (see data from Monte Carlo simulation part). Risk free return is taken from French & Fama database.

• Time period was shortened from 120 to 60 observations: 01/06/2010-01/05/2015

• Excess returns from the market and indeces:

  • Z_SP - 60 observations on excess return of the S&P500 from DataStream
  • Z_DJ - 60 observations on excess return of the DJIA from DataStream
  • Z_FF - 60 observations on excess return of the market from French & Fama database

Codes:

• load_stocks120.gss - loads the data on the returns of the randomly selected 20 socks of S&P500 and selects last 60 observations
  • load_djstocks120.gss - loads the data on the returns of the 30 socks of the Dow-Jones Industrial Average Index and selects last 60 observations
  • CAPM.prc- contains functions to estimate CAPM model by SUR and Minimum Distance methods
• CAPM.inc- sets the format for the output files from the GAUSS procedures
• CAPM_STOCKS20_FF.gss, CAPM_STOCKS20_DJ.gss, CAPM_STOCKS20_SP.gss, CAPM_DJSTOCKS30_FF.gss,CAPM_DJSTOCKS30_DJ.gss,CAPM_DJSTOCKS30_SP.gss - GAUSS procedures to estimate the CAPM models based on particular data set (20 random stocks or 30 stocks from DJIA as well as different market indexes: S&P500, DJIA, CRSP) and generate separate output files. 2019-03-05 11:51:42.893129 The replication data contain MATLAB and GAUSS codes as well as the data required for replication of the results from the paper

It is not so often that one can find fundamental data of companies on which it would be possible to accurately assess the value of a company.

So I decided to use yahoo_fin api to collect some fundamentals of 48 companies from the S&P 500 index.

The content of indicators in each table: - total assets. - cash. - stockholder equity. - profit. - revenue. - return on equity, return on assets, profit margin. - trailing P/E, P/S, P/B, PEG, forward P/E.

In addition, the dataset has prices for all stocks for four years.

This workflow aims to streamline the integration of phytosociological inventory data stored in Excel format into a MongoDB database. This process is essential for the project's Virtual Research Environment (VRE), facilitating comprehensive data analysis. Key components include converting Excel files to JSON format, checking for duplicate inventories to ensure data integrity, and uploading the JSON files to the database. This workflow promotes a reliable, robust dataset for further exploration and utilization within the VRE, enhancing the project's inventory database. Background Efficient data management in phytosociological inventories requires seamless integration of inventory data. This workflow facilitates the importation of phytosociological inventories in Excel format into the MongoDB database, connected to the project's Virtual Research Environment (VRE). The workflow comprises two components: converting Excel to JSON and checking for inventory duplicates, ultimately enhancing the inventory database. Introduction Phytosociological inventories demand efficient data handling, especially concerning the integration of inventory data. This workflow focuses on the pivotal task of importing phytosociological inventories, stored in Excel format, into the MongoDB database. This process is integral to the VRE of the project, laying the groundwork for comprehensive data analysis. The workflow's primary goal is to ensure a smooth and duplicate-free integration, promoting a reliable dataset for further exploration and utilization within the project's VRE. Aims The primary aim of this workflow is to streamline the integration of phytosociological inventory data into the MongoDB database, ensuring a robust and duplicate-free dataset for further analysis within the project's VRE. To achieve this, the workflow includes the following key components: 1. Excel to JSON Conversion: Converts phytosociological inventories stored in Excel format to JSON, preparing the data for MongoDB compatibility. 2. Duplicate Check and Database Upload: Checks for duplicate inventories in the MongoDB database and uploads the JSON file, incrementing the inventory count in the database. Scientific Questions - Data Format Compatibility: How effectively does the workflow convert Excel-based phytosociological inventories to the JSON format for MongoDB integration? - Database Integrity Check: How successful is the duplicate check component in ensuring data integrity by identifying and handling duplicate inventories? - Inventory Count Increment: How does the workflow contribute to the increment of the inventory count in the MongoDB database, and how is this reflected in the overall project dataset?

The IvyDB Signed Volume dataset, available as an add-on product for IvyDB US, contains daily data on detailed option trading volume. Trades in the IvyDB US dataset are assigned as either buyer-initiated or seller-initiated based on the trade price and the bid-ask quote at the time of the trade. The total assigned daily volume is aggregated and updated nightly.