API: Core Earnings and Earnings Distortion Metrics

This dataset provides the Core Earnings and Earnings Distortion data featured in the paper "Core Earnings: New Data and Evidence" published in The Journal of Financial Economics. A summary of the paper is available here. Specific trading strategies for monetizing the novel alpha in Core Earnings and Earnings Distortion are here.

API: Core Earnings and Earnings Distortion Metrics: Single Datapoint

Endpoint
URL
Method
/reconciliation/core-earnings-and-earnings-distortion/:ticker
GET
URL Parameters
Name
Description
Example
:ticker
Ticker of the stock. You can use the coverage endpoint to get full lists of options.
A
Query Parameters
Name
Required
Description
Example
:datapoint
Required
Name of data point. Click here for a full list of available data points
CORE_EARNINGS_AFTER_TAX
:year
Required
Fiscal year of the data point. We generally cover companies back to the first digital document filed with the SEC.
2017
:quarter
Optional
Fiscal quarter Options:
Omit for annual data
1 = Q1 quarterly data
2 = Q2 quarterly data
3 = Q3 quarterly data
4 = Q4 quarterly data
1
:ttm
Optional
Trailing twelve months (TTM) data Options:
Omit for annual data
1 = TTM data ending with Q1 (indicated fiscal year Q1 + prior fiscal year Q4, Q3, & Q2)
2 = TTM data ending with Q2 (indicated fiscal year Q2 & Q1 + prior fiscal year Q4 & Q3)
3 = TTM data ending with Q3 (indicated fiscal year Q3, Q2, & Q1 + prior fiscal year Q4)
4 = TTM data ending with Q4 (indicated fiscal year Q4, Q3, Q2, & Q1).
1
Header Parameters
Name
Value
x-api-key
[New Constructs-provided API key]
Content-Type
application/json
Return Values
Name
Description
Example
ticker
Ticker of the listed security.
AAPL
year
Fiscal year of the data value.
2017
period
Period of the requested data; 1-4 indicate quarterly or TTM periods and 5 indicates an annual period.
5
periodtype
Period type of the requested data (ANNUAL, QUARTERLY, or TTM)
ANNUAL
periodstring
Period string of the requested data (ANNUAL, QUARTERLY, or TTM)
ANNUAL
datapoint
Name of data point.
CORE_EARNINGS_AFTER_TAX
datavalue
Value of the requested datapoint in ones.
53394000000.00000000000000000
filingtype
Type of filing the datapoint is from.
10-K
Sample Call:
Check out Python examples and more in our GitHub repo.
curl -i -H 'x-api-key: [New Constructs-provided API key]' -H "Content-Type: application/json" 'https://api.newconstructs.com/v1/reconciliation/core-earnings-and-earnings-distortion/AAPL?datapoint=CORE_EARNINGS_AFTER_TAX&year=2015'
Success Response: 

{
  "statusCode": 200,
  "headers": {"Content-Type": "application/json"},
  "body": {
    "results": [
      {
        "ticker": "AAPL",
        "year": 2015,
        "period": 5,
        "periodtype": "ANNUAL",
        "periodstring": "ANNUAL",
        "datapoint": "CORE_EARNINGS_AFTER_TAX",
        "datavalue": "51990121685.24540000000000000",
      "filingtype": "10-K"
      }
    ]
  }
}

API: Core Earnings and Earnings Distortion: All Datapoints

Endpoint
URL
Method
/reconciliation/core-earnings-and-earnings-distortion/:ticker
GET
URL Parameters
Name
Description
Example
:ticker
Ticker of the stock. You can use the coverage endpoint to get full lists of options.
A
Query Parameters
Name
Required
Description
Example
:year
Required
Fiscal year of the data point. We generally cover companies back to the first digital document filed with the SEC.
2017
:quarter
Optional
Fiscal quarter Options:
Omit for annual data
1 = Q1 quarterly data
2 = Q2 quarterly data
3 = Q3 quarterly data
4 = Q4 quarterly data
1
:ttm
Optional
Trailing twelve months (TTM) data Options:
Omit for annual data
1 = TTM data ending with Q1 (indicated fiscal year Q1 + prior fiscal year Q4, Q3, & Q2)
2 = TTM data ending with Q2 (indicated fiscal year Q2 & Q1 + prior fiscal year Q4 & Q3)
3 = TTM data ending with Q3 (indicated fiscal year Q3, Q2, & Q1 + prior fiscal year Q4)
4 = TTM data ending with Q4 (indicated fiscal year Q4, Q3, Q2, & Q1).
1
Header Parameters
Name
Value
x-api-key
[New Constructs-provided API key]
Content-Type
application/json
Return Values
Name
Description
Example
ticker
Ticker of the listed security.
AAPL
year
Fiscal year of the data value.
2017
period
Period of the requested data; 1-4 indicate quarterly or TTM periods and 5 indicates an annual period.
5
periodtype
Period type of the requested data (ANNUAL, QUARTERLY, or TTM)
ANNUAL
periodstring
Period string of the requested data (ANNUAL, QUARTERLY, or TTM)
ANNUAL
datapoint
Name of data point.
CORE_EARNINGS_AFTER_TAX
datavalue
Value of the datapoint in ones.
51990121685.24540000000000000
filingtype
Type of filing the datapoint is from.
10-K
Sample Call:
Check out Python examples and more in our GitHub repo.
curl -i -H 'x-api-key: [New Constructs-provided API key]' -H "Content-Type: application/json" 'https://api.newconstructs.com/v1/reconciliation/core-earnings-and-earnings-distortion/AAPL?year=2015'
Success Response: 

{
  "statusCode": 200,
  "headers": {"Content-Type": "application/json"},
  "body": {
    "results": [
      {
        "ticker": "AAPL",
        "year": 2015,
        "period": 5,
        "periodtype": "ANNUAL",
        "periodstring": "ANNUAL",
        "datapoint": "CORE_EARNINGS_AFTER_TAX",
        "datavalue": "51990121685.24540000000000000",
      "filingtype": "10-K"
      },
      {
        "ticker": "AAPL",
        "year": 2015,
        "period": 5,
        "periodtype": "ANNUAL",
        "periodstring": "ANNUAL",
        "datapoint": "TAX_DISTORTION",
        "datavalue": "-614121685.24539600000000000",
      "filingtype": "10-K"
      },
      ...
    ]
  }
}

Datapoints

Name
Description
Datapoint
Core Earnings
Core Earnings, After-Tax measures the sustainable, recurring portion of firms' profits.
CORE_EARNINGS_AFTER_TAX
Total Core Earnings Distortion, Net
Total Earnings Distortion, Net is the total of all (hidden & reported) unusual or less persistent non-operating losses and gains and the income tax distortion associated with these items. It measures the difference of reported GAAP Net Income from Core Earnings
EARNINGS_DISTORTION_TOTAL
Core Earnings Distortion from Hidden Items, Net
Earnings distortion from unusual or less persistent non-operating losses and gains that do not appear directly on the income statement. These items are bundled inside other line items that appear on the income statement. Hidden items are found only in the Management Discussion & Analysis (MD&A) or in the footnotes to the financial statements.
EARNINGS_DISTORTION_HIDDEN
Core Earnings Distortion from Reported Items Pre-Tax, Net
Earnings distortion from unusual or less persistent non-operating losses and gains that are reported pre-tax directly on the income statement.
EARNINGS_DISTORTION_REPORTED_PRE_TAX
Income Tax Distortion
Income tax distortion. Income Tax Distortion is calculated for each company individually based on our calculation of Cash Operating Taxes.
TAX_DISTORTION
Core Earnings Distortion from Reported Items After-Tax, Net
Earnings distortion from unusual or less persistent non-operating losses and gains that are reported after-tax directly on the income statement.
EARNINGS_DISTORTION_REPORTED_AFTER_TAX
GAAP Net Income
GAAP net income.
INCOME_NET
Basic Weighted Avg. Shares
Weighted average basic shares oustanding as reported on the income statment, adjusted for stock splits.
WABSO_SPLIT_ADJUSTED
Total Core Earnings Distortion Net Per Weighted Average Basic Shares Outstanding (Split Adjusted)
Total Core Earnings Distortion divided by weighted average basic shares outstanding (split adjusted).
EARNINGS_DISTORTION_TOTAL_PER_WABSO_SPLIT_ADJUSTED
Weighted Average Diluted Shares Outstanding (Split Adjusted)
Weighted average diluted shares oustanding as reported on the income statment, adjusted for stock splits.
WADSO_SPLIT_ADJUSTED
Total Core Earnings Distortion, Net Weighted Average Diluted Shares Outstanding (Split Adjusted)
Total Core Earnings Distortion divided by weighted average diluted shares outstanding (split adjusted).
EARNINGS_DISTORTION_TOTAL_PER_WADSO_SPLIT_ADJUSTED

*Indicates the datapoint is affected by stock price.

API: Fundamental Data Errors

Error
Message
Error Code
DataPointNotFound
The requested datapoint was not found.
404