Updated weekly, this database provides aggregate fundamental indicators for market sectors/industries of publicly traded U.S. stocks. 18 aggregate indicators are provided per industry with history extending back to 2005. Each indicator consists of an aggregate value (average / median) determined from the underlying stocks’ fundamental indicators.
- Instant determination of industry health simply by viewing the aggregate indicators
- Aggregate indicators are provided for standard sectors and major industries
- Cross-reference to the popular Global Industry Classification Standard (GICS) structure Sector / Group Industry / Industry / Subindustry is provided
- Subscriber requests for new stock groups will be implemented where practical
- Free preview access; use this data right now
- Works with Quandl API and libraries
- Email support, usually within 1 business day
- License for individual (personal) use: $65 per month
- License for Small business and start-ups: $150 per month
- LIcense for established businesses: $1,000 per month
Annual discounts are 25% for all subscription types.
Equity Analytx specializes in the generation of unique financial data sets for use by investment professionals and analysts. The company prides itself on its ability to produce high quality data, deliver the data in a timely fashion, and responsiveness to customer needs. Equity Analytx was founded in 2015.
This database provides fundamental indicators for a wide selection of industy groups of publicly traded U.S. stocks in a weekly time series format.
The industry fundamental indicators consist of an aggregate value of all the stocks within the group. The aggregate value is a market cap weighted average of the individual stock fundamentals. In addition to the aggregate value, the median value along with the 80th and 20th percentile are also provided.
Note: The documentation from here on refers to sectors, subsectors, subindustires, and other types of stock groups as “industries”.
A dataset consists of a group of logically related time-series data. In the case of the Industry Aggregate database, each dataset corresponds to one fundamental and one aggregate indicator. There are 225 industries and 18 fundamental indicators per industry. This means that there are thousands of datasets. But regardless of numbers, each dataset still has the same fields (columns). The five columns are described in the table below.
|| Market Capitalization Weighted Average of all stocks within the industry
|| 80th percentile value for the stock industry
|| 50th percentile (median) value for the stock industry
|| 20th percentile value for the stock industry
|| Number of stocks used to calculate the aggregate value for the specific time period, industry and indicator
Note 1: 80PCTL/20PCTL values are set equal to 50PCTL when STOCKS is less than 10
Note 2: 50PCTL is set to zero (0) when STOCKS is less than 5
18 fundamental indicators have been carefully chosen to represent the state (or health) of each industry. The indicators are summarized in the table below.
|| Aggregate Gross Margin (%)
|| Aggregate Operating Margin (%)
|| Aggregate Asset Turnover (%)
|| Aggregate Current Ratio
|| Aggregate Debt / Equity Ratio (%)
|| Aggregate CAPEX / Sales Ratio (%)
|| Aggregate Free Cash FLow / Sales Ratio (%)
|| Aggregate Sales / Enterprise Value (%)
|| Aggregate EBITDA / Enterprise Value (%)
|| Aggregate Book / Market Value (%)
|| Aggregate Earnings Yield (%)
|| Aggregate Tax Rate (%)
|| Aggregate Return on Equity (%)
|| Aggregate Return on Capital (%)
|| Aggregate Dividend Yield (%)
|| Aggregate Dividend Yield excl Nonpayers (%)
|| Aggregate Dividend Coverage (%)
|| Aggregate Dividend Coverage excl Nonpayers (%)
Refer to the Methodology section for more information on the fundamental indicators.
A list of currently supported industries can be found here: CSV, Excel.
A cross-reference from the GICS structure to Equity Analytx database can be found here: CSV, Excel
The Quandl Code is in the following format:
For example, if the industry code is MATERIALS and the indicator is AGM, then the Quandl code is
Industry Aggregate Calculation
The aggregate is based on fundamental factors that have been extracted from individual stocks that form the industry. The rules for gathering the data and stock participation are listed below:
- Fundamental data are "As Reported" (AR) only; "Most Recent" (MR) are not used
- Cash flow and income-related fundamentals are based on Trailing Twelve Months (TTM), calculated from the last 4 quarterly reports and most recent annual report
- Balance sheet fundamentals utilize data from the most recent report, either quarterly report or annual report
- Market Cap/Price-related indicators vary between quarterly reports. For this reason, the indicators are calculated on a daily basis prior to being included in the aggregate
- Stock symbols that have been listed for less than one year are not included in the aggregate due to insufficient financial information
- American Depositary Receipts (ADRs) and Canadian stocks are not included in the calculations due to inconsistent reporting and currency issues
- Graveyard stocks are not included in the aggregate prior to launch of this database
Occasionally, companies make errors in their SEC filing. In most cases, such errors are insignificant for the calculation of the industry aggregate. But in rare instances the fundamental value is so far off nominal that it can significantly skew the aggregate calculation. For this reason, limits are imposed on individual stock fundamentals to prevent this from occurring.
In addition, companies occasionally omit line items from their filing. In these cases, indicators that are based on the omitted line item are thrown out (for that stock only). STOCKS (column 5 from the dataset) is reduced accordingly for that particular time period.
MCWA (Column 1)
Most equity indices (such as Dow Jones) and passive equity ETFs are based on some form of stock market capitalization weighting. For this reason, the primary indicator is the MktCap Weighted Average (MCWA) of the stocks. This means that each individual stock’s fundamental indicator is weighted by its stock market capitalization in the aggregate.
Note: the MCWA is rebalanced weekly
50PCTL (Column 3)
Over the last decade, passive ETFs and index products have started using an equal weight average of stock holdings. In order to mimic such ETFs, the mean (equal weight) indicator value should ideally be provided in the dataset. However, outliers (typically microcaps) tend to adversely affect the resulting aggregate making the mean value undesirable. For this reason, the median value, or 50th percentile value is used instead, as outliers do not impact the result.
Note: 50PCTL is set to zero (0) when STOCKS is less than 5.
80PCTL (Column 2), 20PCTL (Column 4)
The 80th percentile and 20th percentiles represent the approximate upper and lower boundaries for individual stock values for the given period. This is a convenient method of discarding outliers and providing an approximate range of values. The range is provided for quantitative analysts and market timers that want to know whether the indicator range is expanding or contracting.
Note: 80PCTL and 20PCTL are set equal to 50PCTL when STOCKS is less than 10.
STOCKS (Column 5)
The number of stocks used in the aggregate calculation can vary from one indicator to another and also between time periods. The variations are a result of omitted line items as described above, and also due to specific accounting methods (Banking industry for example). Also, the number of stocks can vary dramatically from one industry to another. In some cases, industries are so narrowly defined, that the aggregate could potentially degrade if the number of stock constituents is too low. For these reasons, the STOCKS field is included to assist the user evaluate the quality of the time series.
Indicators need to be specified properly in order to produce accurate results. As an example, market analysts often quote Price/Earnings Ratio as an aggregate. But the aggregate indicator is inaccurate due to some companies have negative earnings. The negative earnings result in a negative P/E Ratio which brings the aggregate average down, the opposite of what should really happen. For this reason, the financial ratios need to be specified so that potentially negative values reside in the numerator, not the denominator.
Price / Earnings Ratio is flipped upside down and becomes Earnings Yield
Price / Book Value Per Share is flipped upside down to become Book / Market
EV / EBITDA is flipped upside down and becomes EBITDA / EV
It should be noted that in some rare cases the Enterprise Value (EV) can be negative. For this reason, stocks with negative or zero EV are not included in the calculation. This affects EBITDA2EV and SALES2EV. The same logic holds for the rare instance when sales (revenues) are negative and sales is in the denominator. This applies to CPX2SALES and FCF2SALES.
Dividend Coverage (DIVCOV) is a non-standard financial ratio: Net Income Available to Common / Dividends Paid. The ratio provides an indication of how many times the common shareholder dividend could be paid using income available to common.
Dividend Coverage and Dividend Yield (DIVYLD) are provided in two versions of indicator: all stocks; and dividend payers only. The latter version is marked with an 'X' at the end of the industry code. Thus the Dividend Yield excluding Nonpayers (%) is DIVYLDX. Dividend Coverage excluding Nonpayers (%) is DIVCOVX.
Subscribers can download the entire database at anytime:
In addition subscribers can download the most recent observation for each dataset:
A zipped csv file is returned for each of the above.
The data in these batch downloads is updated weekly on Sundays at approximately 08h00 Eastern Standard Time (EST).
The full database is accessible via the Quandl API. The database is also available via Quandl's free libraries for R, Python, Matlab, Excel and other tools.
For complete API documentation, see quandl.com/docs/api
To get the Energy sector Gross Margin MktCap Weighted Average for the last 3 months in JSON:
The Quandl code for this dataset is
|This truncates the result to include only the first 13 rows (13 weeks) of data|
|This ensures the result includes the most recent day first|
|This tells the server to send only column 2 (MktCap Weighted Average)|
With all columns:
API and Library Helpers
To quickly generate API calls or library calls, you can visit any data page (EA1/ENERGY_AGM for example). On the right side of the screen are buttons that help you build API calls based on what you are looking at on the screen.
For more information:
- General Quandl API Documentation
- Quandl Libraries
Premium support is available for this database: firstname.lastname@example.org