US Earnings Call Transcripts (Top 1,000 Companies, 2021–2025)
Five years of full-text earnings call transcripts from the top ~1,000 US public companies by reporting frequency (plus Tesla and Meta, which IPO'd more recently), covering Q1 2021 through Q4 2025. 19,677 transcripts across 1002 symbols, packaged as 10 gzipped JSONL files — one file per half-year (H1 = Q1+Q2, H2 = Q3+Q4) to stay under platform per-file size limits. Each line is one transcript with fields: symbol, fiscal_year, fiscal_quarter, date, content (full prepared remarks + Q&A, speaker labels preserved). Sourced from Financial Modeling Prep. Read natively with pandas.read_json(path, lines=True, compression='gzip') or duckdb.read_json('file.jsonl.gz', lines=true) — concatenate all files for the full 5-year corpus. Industry-grade NLP corpus: ~25 KB per transcript average. Ideal for sentiment models, topic modeling, executive language change-detection, earnings-drift research keyed off transcript embedding similarity, and LLM fine-tuning on real corporate disclosure language.
Use Cases
- NLP sentiment / tone analysis at scale (CFO confidence, hedging language, forward guidance shifts)
- Earnings-drift research using transcript embedding similarity vs realized return
- Topic modeling and executive-language change detection across cycles
- Fine-tuning LLMs on corporate disclosure register
- Quote-mining for thematic equity research (AI mentions, tariff exposure, supply-chain commentary)
Methodology
Top 1,000 US-listed companies selected by noOfTranscripts from FMP's earnings-transcript-list (proxy for longest reporting history). For each, fetched Q1–Q4 of 2021–2025 via earning-call-transcript. Empty quarters skipped. Output is sorted by symbol then date ascending; one normalized JSON object per line.
Update Schedule
Static snapshot. Reflects what was reported as of the build date.
Attribution
Data: Financial Modeling Prep. Top-1000 selection: FMP earnings-transcript-list (sorted by transcript count).
Schema
| name | type |
|---|---|
| symbol | string |
| fiscal_year | number |
| fiscal_quarter | string |
| date | date |
| content | string |
Sample Data
| date | symbol | content | fiscal_year | fiscal_quarter |
|---|---|---|---|---|
| 2021-04-28 | 034220.KS | Daniel Lee: Good afternoon. This is Daniel Lee, in charge of LG Display's IR. On behalf of the company, let me thank all the participants at this conference call. Today, I'm joined by the CFO, DH Suh; Heeyeon Kim, Senior Vice President of Corporate Strategy Group; Seung Min Lim, Vice President of Corporate Planning; Stephen Ko, Vice President of TV Marketing; Jae Yong Kwon, Vice President of IT, Strategy and Marketing; and Ki-Joon Jin, in charge of auto marketing. The conference call today will … | 2021 | Q1 |
| 2021-07-28 | 034220.KS | Daniel Lee: [Foreign Language] [Interpreted] Good morning. This is Daniel Lee, in charge of LG Display's IR. On behalf of the company, let me thank all the participants at this conference call. Today, I'm joined by the CFO, DH Suh; Heeyeon Kim, Senior Vice President of Corporate Strategy Group; Seung Min Lim, Vice President of Corporate Planning; Stephen Ko, Vice President of TV Marketing; Jae Yong Kwon, Vice President of IT, Strategy and Marketing; and Ki-Joon Jin, in charge of Auto Marketing. … | 2021 | Q2 |
| 2021-10-27 | 034220.KS | Operator: Good morning and good evening. First of all, thank you all for joining this Conference Call. And now we will begin the conference of the Fiscal Year 2021 Third Quarter Earnings Results by LG Display. This conference will start with a presentation followed by a divisional Q&A session. [Operator Instructions] Now we shall commence the presentation on the fiscal year 2021 third quarter earnings results by LG Display. Unidentified Company Representative: [Foreign Language] Good morning. Th… | 2021 | Q3 |
Get this via API
# 1. Add dAgentBase once, in any MCP client. No install, no vendor keys.
# Claude.ai / Claude Desktop: Settings -> Connectors -> Add custom connector
# Cursor / Claude Code / others: mcp.json
{
"mcpServers": {
"dagentbase": {
"url": "https://dagentbase.com/api/mcp",
"headers": { "Authorization": "Bearer dm_live_YOUR_KEY" }
}
}
}
# 2. Then ask your agent, in plain language:
# "Preview 'US Earnings Call Transcripts (Top 1,000 Companies, 2021–2025)' and, if it fits, claim it and download the files."
# Tools it will use: search_listings -> preview_listing -> purchase_listing -> get_download_urls
# 1. Add dAgentBase once, in any MCP client. No install, no vendor keys.
# Claude.ai / Claude Desktop: Settings -> Connectors -> Add custom connector
# Cursor / Claude Code / others: mcp.json
{
"mcpServers": {
"dagentbase": {
"url": "https://dagentbase.com/api/mcp",
"headers": { "Authorization": "Bearer dm_live_YOUR_KEY" }
}
}
}
# 2. Then ask your agent, in plain language:
# "Preview 'US Earnings Call Transcripts (Top 1,000 Companies, 2021–2025)' and, if it fits, claim it and download the files."
# Tools it will use: search_listings -> preview_listing -> purchase_listing -> get_download_urlsone time · open license
Details
Available formats