Dataset
earnings_call
Earnings-call transcripts from an IBM research project, tens of thousands of records with finance tags, in CC0. A filings-adjacent corpus for call-tone and question-and-answer analysis.
Data preview
Dataset card
The Earnings Calls dataset pairs NASDAQ earnings call transcripts with daily stock prices and sector index values for the 2016–2020 period. It is distributed by jlh-ibm under a CC0-1.0 license and totals 21,887 rows in its training split.
What this dataset contains
The dataset combines 188 earnings call transcripts with 11,970 stock price observations and 1,196 sector index values, all drawn from companies listed on NASDAQ between 2016 and 2020. Transcripts were sourced from Thomson Reuters Eikon, while price data was retrieved from Yahoo Finance. Together these records support text classification and sentiment analysis research in finance.
Structure and fields
The tabular portion is keyed by a date field and identifies the issuing company via a string company column. Trading activity is captured with OHLC fields (open, high, low, close), an adjusted close (adj_close), and an int64 volume field. Earnings call transcripts and sector index values are distributed alongside these structured columns for joint modeling.
How analysts use it
Researchers use the dataset as a benchmark for evaluating NLP techniques on financial text, linking transcript-derived signals to subsequent open, close, and adj_close movements. The volume column enables liquidity-aware studies, while the company field supports cross-sectional comparisons across NASDAQ issuers. Quants can prototype event-driven or sentiment-augmented strategies, though the 2016–2020 window and 188-transcript corpus limit statistical depth.
Documentation & references 1
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SEC EDGAR 10-K & 10-Q financial statements for 2,600+ NASDAQ companies.
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