Brain Language Metrics on Earnings Calls - 4500+ US Stocks product image in hero

Brain Language Metrics on Earnings Calls - 4500+ US Stocks

Brain Company
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COMPOSITE_FIGI
DATE
LAST_TRANSCRIPT_DATE
LAST_TRANSCRIPT_QUARTER
LAST_TRANSCRIPT_YEAR
MD_N_CHARACTERS
MD_SENTIMENT
MD_SCORE_UNCERTAINTY
MD_SCORE_LITIGIOUS
MD_SCORE_CONSTRAINING
MD_READABILITY
MD_LEXICAL_RICHNESS
MD_LEXICAL_DENSITY
MD_SPECIFIC_DENSITY
AQ_N_CHARACTERS
AQ_SENTIMENT
AQ_SCORE_UNCERTAINTY
AQ_SCORE_LITIGIOUS
AQ_SCORE_CONSTRAINING
MA_N_CHARACTERS
MA_SENTIMENT
MA_SCORE_UNCERTAINTY
MA_SCORE_LITIGIOUS
MA_SCORE_CONSTRAINING
MA_READABILITY
MA_LEXICAL_RICHNESS
MA_LEXICAL_DENSITY
MA_SPECIFIC_DENSITY
1 xxxxxxxxxx Xxxxxxxxx xxxxxx xxxxxxxxxx Xxxxx Xxxxxx Xxxxxxxxxx Xxxxxx Xxxxxxxxx Xxxxxxxxxx xxxxxxxxx Xxxxxxxxx xxxxxxxxx Xxxxxxx xxxxxx Xxxxx xxxxxxxxxx xxxxxx Xxxxxxxxxx xxxxxx Xxxxx Xxxxxx xxxxx xxxxxxxx xxxxxxx Xxxxx Xxxxxxxx xxxxxxxxxx xxxxxx
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COMPOSITE_FIGI
DATE
LAST_TRANSCRIPT_DATE
LAST_TRANSCRIPT_QUARTER
LAST_TRANSCRIPT_YEAR
PREV_TRANSCRIPT_DATE
PREV_TRANSCRIPT_QUARTER
PREV_TRANSCRIPT_YEAR
MD_DELTA_PERC_N_CHARACTERS
MD_DELTA_SENTIMENT
MD_DELTA_SCORE_UNCERTAINTY
MD_DELTA_SCORE_LITIGIOUS
MD_DELTA_SCORE_CONSTRAINING
MD_DELTA_READABILITY
MD_DELTA_LEXICAL_RICHNESS
MD_DELTA_LEXICAL_DENSITY
MD_DELTA_SPECIFIC_DENSITY
MD_SIMILARITY_ALL
MD_SIMILARITY_POSITIVE
MD_SIMILARITY_NEGATIVE
MD_SIMILARITY_UNCERTAINTY
MD_SIMILARITY_LITIGIOUS
MD_SIMILARITY_CONSTRAINING
AQ_DELTA_PERC_N_CHARACTERS
AQ_DELTA_SENTIMENT
AQ_DELTA_SCORE_UNCERTAINTY
AQ_DELTA_SCORE_LITIGIOUS
AQ_DELTA_SCORE_CONSTRAINING
AQ_SIMILARITY_ALL
AQ_SIMILARITY_POSITIVE
AQ_SIMILARITY_NEGATIVE
MA_DELTA_PERC_N_CHARACTERS
MA_DELTA_SENTIMENT
MA_DELTA_SCORE_UNCERTAINTY
MA_DELTA_SCORE_LITIGIOUS
MA_DELTA_SCORE_CONSTRAINING
MA_DELTA_READABILITY
MA_DELTA_LEXICAL_RICHNESS
MA_DELTA_LEXICAL_DENSITY
MA_DELTA_SPECIFIC_DENSITY
MA_SIMILARITY_ALL
MA_SIMILARITY_POSITIVE
MA_SIMILARITY_NEGATIVE
MA_SIMILARITY_UNCERTAINTY
MA_SIMILARITY_LITIGIOUS
MA_SIMILARITY_CONSTRAINING
1 xxxxxxxxxx Xxxxxxxxx xxxxxx xxxxxxxxxx Xxxxx Xxxxxx Xxxxxxxxxx Xxxxxx Xxxxxxxxx Xxxxxxxxxx xxxxxxxxx Xxxxxxxxx xxxxxxxxx Xxxxxxx xxxxxx Xxxxx xxxxxxxxxx xxxxxx Xxxxxxxxxx xxxxxx Xxxxx Xxxxxx xxxxx xxxxxxxx xxxxxxx Xxxxx Xxxxxxxx xxxxxxxxxx xxxxxx Xxxxxxxxx xxxxxx Xxxxxxxxx Xxxxxxxxx xxxxxxxxxx Xxxxxx Xxxxx xxxxxx xxxxxxx xxxxxxx Xxxxx xxxxxx Xxxxxxxxxx xxxxxxxx xxxxxx Xxxxx Xxxxxxx xxxxxx
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Volume
4.5K
stocks covered
Avail. Format
.csv
File
Coverage
1
Country
History
10
years

Data Dictionary

[Sample] metrics_earnings_call_20210722.csv
Attribute Type Example Mapping
COMPOSITE_FIGI
String BBG000C2V3D6
String A Stock Ticker
DATE
DateTime 2021-07-22T00:00:00+00:00
LAST_TRANSCRIPT_DATE
DateTime 2021-05-26T00:00:00+00:00
LAST_TRANSCRIPT_QUARTER
Integer 2
LAST_TRANSCRIPT_YEAR
Integer 2021
MD_N_CHARACTERS
Float 17327.0
MD_SENTIMENT
Float 0.4907
MD_SCORE_UNCERTAINTY
Float 0.0992
MD_SCORE_LITIGIOUS
Float 0.0229
MD_SCORE_CONSTRAINING
Float 0.0076
MD_READABILITY
Float 10.3541
MD_LEXICAL_RICHNESS
Float 0.3656
MD_LEXICAL_DENSITY
Float 0.5225
MD_SPECIFIC_DENSITY
Float 0.0785
AQ_N_CHARACTERS
Float 10744.0
AQ_SENTIMENT
Float 0.4163
AQ_SCORE_UNCERTAINTY
Float 0.3333
AQ_SCORE_LITIGIOUS
Float 0.0312
AQ_SCORE_CONSTRAINING
Float 0.0104
MA_N_CHARACTERS
Float 24893.0
MA_SENTIMENT
Float 0.506
MA_SCORE_UNCERTAINTY
Float 0.1737
MA_SCORE_LITIGIOUS
Float 0.018
MA_SCORE_CONSTRAINING
Float 0.024
MA_READABILITY
Float 10.2549
MA_LEXICAL_RICHNESS
Float 0.3218
MA_LEXICAL_DENSITY
Float 0.4592
MA_SPECIFIC_DENSITY
Float 0.0763
[Sample] differences_earnings_call_20210722.csv
Attribute Type Example Mapping
COMPOSITE_FIGI
String BBG000C2V3D6
String A Stock Ticker
DATE
DateTime 2021-07-22T00:00:00+00:00
LAST_TRANSCRIPT_DATE
DateTime 2021-05-26T00:00:00+00:00
LAST_TRANSCRIPT_QUARTER
Integer 2
LAST_TRANSCRIPT_YEAR
Integer 2021
PREV_TRANSCRIPT_DATE
DateTime 2021-02-17T00:00:00+00:00
PREV_TRANSCRIPT_QUARTER
Integer 1
PREV_TRANSCRIPT_YEAR
Integer 2021
MD_DELTA_PERC_N_CHARACTERS
Float 0.1015
MD_DELTA_SENTIMENT
Float 0.0336
MD_DELTA_SCORE_UNCERTAINTY
Float -0.0153
MD_DELTA_SCORE_LITIGIOUS
Float -0.0076
MD_DELTA_SCORE_CONSTRAINING
Float -0.0229
MD_DELTA_READABILITY
Float 0.4384
MD_DELTA_LEXICAL_RICHNESS
Float -0.0246
MD_DELTA_LEXICAL_DENSITY
Float -0.0079
MD_DELTA_SPECIFIC_DENSITY
Float -0.007
MD_SIMILARITY_ALL
Float 0.9329
MD_SIMILARITY_POSITIVE
Float 0.9457
MD_SIMILARITY_NEGATIVE
Float 0.3103
MD_SIMILARITY_UNCERTAINTY
Float 0.6267
MD_SIMILARITY_LITIGIOUS
Float 0.9129
MD_SIMILARITY_CONSTRAINING
Float 0.5
AQ_DELTA_PERC_N_CHARACTERS
Float 0.0966
AQ_DELTA_SENTIMENT
Float 0.034
AQ_DELTA_SCORE_UNCERTAINTY
Float -0.1088
AQ_DELTA_SCORE_LITIGIOUS
Float -0.0003
AQ_DELTA_SCORE_CONSTRAINING
Float 0.0104
AQ_SIMILARITY_ALL
Float 0.7433
AQ_SIMILARITY_POSITIVE
Float 0.5107
AQ_SIMILARITY_NEGATIVE
Float 0.9522
MA_DELTA_PERC_N_CHARACTERS
Float -0.1508
MA_DELTA_SENTIMENT
Float 0.0831
MA_DELTA_SCORE_UNCERTAINTY
Float 0.0012
MA_DELTA_SCORE_LITIGIOUS
Float -0.005
MA_DELTA_SCORE_CONSTRAINING
Float 0.0182
MA_DELTA_READABILITY
Float 2.0079
MA_DELTA_LEXICAL_RICHNESS
Float 0.0113
MA_DELTA_LEXICAL_DENSITY
Float 0.0082
MA_DELTA_SPECIFIC_DENSITY
Float 0.0073
MA_SIMILARITY_ALL
Float 0.7444
MA_SIMILARITY_POSITIVE
Float 0.7035
MA_SIMILARITY_NEGATIVE
Float 0.8473
MA_SIMILARITY_UNCERTAINTY
Float 0.5565
MA_SIMILARITY_LITIGIOUS
Float 0.7303
MA_SIMILARITY_CONSTRAINING
Float 0.8165

Description

The exploitation of textual unstructured content (news, company filings, earnings calls etc) in financial analysis is quickly expanding across both quantitative and discretionary strategies as demonstrated by the growing number of academic papers and products in this domain. The Brain Language Metrics on Earnings Calls Transcripts (BLMECT) dataset has the objective of monitoring several language metrics the quarterly earnings call transcripts for 4500+ US stocks. The dataset is made of two parts; one includes the language metrics for the most recent earnings call transcript for each stock, namely: 1) Financial sentiment 2) Percentage of words belonging to financial domain classified by language types: - “Constraining” language - “Litigious” language - “Uncertainty” language 3) Readability score 4) Lexical metrics such as lexical density and richness 5) Text statistics such as the report length and the average sentence length The second part includes the differences between the most recent earnings call transcript and the previous one: 1) Difference of the various language metrics (e.g. delta sentiment, delta readability score delta, delta percentage of a specific language type etc.) 2) Similarity metrics between documents, also with respect to a specific language type (for example similarity with respect to “litigious” language or “uncertainty” language) The metrics calculation is reported separately for the following sections of the transcript: a) Management Discussion b) Analysts Questions c) Management Answers to Analysts Questions The dataset is updated with a daily frequency since new earnings calls transcripts are published every day for some of the universe stocks. Clearly the data for each stock will change on a quarterly basis when new earnings calls are published. The historical dataset is available from year 2012. Factsheet https://braincompany.co/assets/files/BLM_ECT_summary.pdf Data dictionary https://braincompany.co/assets/files/BLM_ECT_data_dictionary.pdf

Country Coverage

North America (1)
United States of America

History

10 years of historical data

Volume

4,500 stocks covered

Pricing

Free sample available
License Starts at
One-off purchase Not available
Monthly License Not available
Yearly License Available
Usage-based Not available

Suitable Company Sizes

Small Business
Medium-sized Business
Enterprise

Delivery

Methods
S3 Bucket
Frequency
daily
Format
.csv

Use Cases

Alpha Generation Systematic Trading
Quantitative Investing
Alternative Investment
Earnings Calls Analysis

Categories

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Frequently asked questions

What is Brain Language Metrics on Earnings Calls - 4500+ US Stocks?

The Brain Language Metrics on Earnings Calls Transcripts (BLMECT) dataset has the objective of monitoring several language metrics the quarterly earnings call transcripts for 4500+ US stocks.

What is Brain Language Metrics on Earnings Calls - 4500+ US Stocks used for?

This product has 5 key use cases. Brain Company recommends using the data for Alpha Generation, Systematic Trading, Quantitative Investing, Alternative Investment, and Earnings Calls Analysis. Global businesses and organizations buy Stock Market Data from Brain Company to fuel their analytics and enrichment.

Who can use Brain Language Metrics on Earnings Calls - 4500+ US Stocks?

This product is best suited if you’re a Medium-sized Business, Enterprise, or Small Business looking for Stock Market Data. Get in touch with Brain Company to see what their data can do for your business and find out which integrations they provide.

How far back does the data in Brain Language Metrics on Earnings Calls - 4500+ US Stocks go?

This product has 10 years of historical coverage. It can be delivered on a daily basis.

Which countries does Brain Language Metrics on Earnings Calls - 4500+ US Stocks cover?

This product includes data covering 1 country like USA. Brain Company is headquartered in Italy.

How much does Brain Language Metrics on Earnings Calls - 4500+ US Stocks cost?

Pricing information for Brain Language Metrics on Earnings Calls - 4500+ US Stocks is available by getting in contact with Brain Company. Connect with Brain Company to get a quote and arrange custom pricing models based on your data requirements.

How can I get Brain Language Metrics on Earnings Calls - 4500+ US Stocks?

Businesses can buy Stock Market Data from Brain Company and get the data via S3 Bucket. Depending on your data requirements and subscription budget, Brain Company can deliver this product in .csv format.

What is the data quality of Brain Language Metrics on Earnings Calls - 4500+ US Stocks?

You can compare and assess the data quality of Brain Company using Datarade’s data marketplace.

What are similar products to Brain Language Metrics on Earnings Calls - 4500+ US Stocks?

This product has 3 related products. These alternatives include Brain Language Metrics on Company Filings for 6000+ US Stocks, The Data Appeal Point of Interest (POI) Data API, Dataset 200 Million+ POI Data Mapped Measure Sentiment and Customer Experience, and Dappier Financial & Real-Time Stock Market Data RAG API, LLM Compatible Market & Exchange Search. You can compare the best Stock Market Data providers and products via Datarade’s data marketplace and get the right data for your use case.

Pricing available upon request
License Starts at
One-off purchase Not available
Monthly License Not available
Yearly License Available
Usage-based Not available