DOLLAR GENERAL CORP: cash and cash equivalents
Cash and cash equivalents for DOLLAR GENERAL CORP. Inspect selected reporting periods, original units and SEC filing links; download the financial history.
All DOLLAR GENERAL CORP financial histories
What this measure means
Cash and qualifying short-term liquid investments under the filer’s accounting policy. Restricted cash and longer-term investments may be reported separately.
Exact concept: us-gaap:CashAndCashEquivalentsAtCarryingValue. Each value is a balance at the reporting date, not a flow earned over a year. Different units remain separate; no currency conversion or interpolation is applied.
Coverage of this history
Selected reporting periods run from 2009-01-30 to 2026-01-30. The SEC response was captured on 2026-09-19.
Selected filing history
| Period start | Period end | Value | Unit | Filed | Source filing |
|---|---|---|---|---|---|
| At date | 2026-01-30 | 1,138,501,000 | USD | 2026-03-20 | 10-K · 0001104659-26-032325 |
| At date | 2025-01-31 | 932,576,000 | USD | 2026-03-20 | 10-K · 0001104659-26-032325 |
| At date | 2024-02-02 | 537,283,000 | USD | 2025-03-21 | 10-K · 0001558370-25-003413 |
| At date | 2023-02-03 | 381,576,000 | USD | 2024-03-25 | 10-K · 0001558370-24-003813 |
| At date | 2022-01-28 | 344,829,000 | USD | 2023-03-24 | 10-K · 0001558370-23-004574 |
| At date | 2021-01-29 | 1,376,577,000 | USD | 2022-03-18 | 10-K · 0001558370-22-003921 |
| At date | 2020-01-31 | 240,320,000 | USD | 2021-03-19 | 10-K · 0001558370-21-003245 |
| At date | 2019-02-01 | 235,487,000 | USD | 2020-03-19 | 10-K · 0001558370-20-002915 |
| At date | 2018-02-02 | 267,441,000 | USD | 2019-03-22 | 10-K · 0001558370-19-002383 |
| At date | 2017-02-03 | 187,915,000 | USD | 2018-03-23 | 10-K · 0001558370-18-002366 |
| At date | 2016-01-29 | 157,947,000 | USD | 2018-03-23 | 10-K · 0001558370-18-002366 |
| At date | 2015-01-30 | 579,823,000 | USD | 2018-03-23 | 10-K · 0001558370-18-002366 |
| At date | 2014-01-31 | 505,566,000 | USD | 2017-03-24 | 10-K · 0001558370-17-002116 |
| At date | 2013-02-01 | 140,809,000 | USD | 2016-03-22 | 10-K · 0001047469-16-011420 |
| At date | 2012-02-03 | 126,126,000 | USD | 2015-03-20 | 10-K · 0001047469-15-002540 |
| At date | 2011-01-28 | 497,446,000 | USD | 2014-03-20 | 10-K · 0001047469-14-002721 |
| At date | 2010-01-29 | 222,076,000 | USD | 2013-03-25 | 10-K · 0001047469-13-003283 |
| At date | 2009-01-30 | 377,995,000 | USD | 2012-03-22 | 10-K · 0001047469-12-003084 |
Related financial histories
Inspect the source
- Entity
- DOLLAR GENERAL CORP / CIK 0000029534
- Captured
- 2026-09-19T10:53:41.999Z
- SEC response SHA-256
16157a14c6c91f04a8b3e89ccedfc91ee0d5ea6978f8c6ed1d25d8cfe73541cf
Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON
Latest-filed annual-report facts per unit and reporting period at capture time. Duration facts cover 300 to 400 days. This selection can include restatements and is not a point-in-time backtest dataset. Missing concepts are omitted, never zero-filled. Values retain original units and are not currency converted.
Public company accounting reference, not market prices, returns, an investment recommendation, or ALPHAC performance. Validate a separately constructed return series with the validation API; accounting values are not returns.
Use this in research
A financial period ends before its results become public. Use the filing date as a minimum availability boundary, inspect amendments, and retain the original filing vintage when testing historical signals. This latest-filed selection can contain information unavailable at the time.
These pages do not supply prices, total-return histories, corporate-action adjustments or a tradable universe. Build those inputs separately before evaluating a strategy. A profitable backtest can still reflect selection bias or costs that were left out.
Research methodology · Execution and cost assumptions · Check backtest overfitting
Build with the open-source tools
Use these accounting records as inspectable inputs. When you have constructed a return series, the validation tools can help test its statistical evidence and preserve the result with its limitations.
- Get an API key and run your first validation
- Connect the MCP server to your coding assistant
- Inspect the ALPHAC engine on GitHub
- Read the MCP server source and integration examples
Read the published dataset with Python
import json
from urllib.request import urlopen
with urlopen("https://canlicapital.com/company-data/0000029534.json") as response:
record = json.load(response)
print(record["fetched_at"])
print(record["policy"])
for concept in record["concepts"]:
print(concept["tag"], next(iter(concept["observations"])))