DIGITAL LOCATIONS, INC.: interest expense
Interest expense for DIGITAL LOCATIONS, INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.
All DIGITAL LOCATIONS, INC. financial histories
What this measure means
Borrowing costs recognized as interest expense. This is distinct from cash interest paid and may not include every capitalized borrowing cost.
Exact concept: us-gaap:InterestExpense. Each value covers an annual-duration reporting interval, shown with both start and end dates. Different units remain separate; no currency conversion or interpolation is applied.
Coverage of this history
Selected reporting periods run from 2010-01-01 to 2023-12-31. The SEC response was captured on 2026-09-22.
This selected history ends more than two years before capture. Do not treat its final value as a current balance or current annual result. More recent filings may use another accounting tag; inspect the filings before drawing conclusions about the company.
Selected filing history
| Period start | Period end | Value | Unit | Filed | Source filing |
|---|---|---|---|---|---|
| 2023-01-01 | 2023-12-31 | 985,562 | USD | 2024-03-29 | 10-K · 0001493152-24-011984 SEC |
| 2022-01-01 | 2022-12-31 | 509,633 | USD | 2024-03-29 | 10-K · 0001493152-24-011984 SEC |
| 2021-01-01 | 2021-12-31 | 919,095 | USD | 2023-03-20 | 10-K · 0001477932-23-001568 SEC |
| 2020-01-01 | 2020-12-31 | 626,685 | USD | 2022-03-28 | 10-K · 0001477932-22-001669 SEC |
| 2019-01-01 | 2019-12-31 | 974,713 | USD | 2021-03-29 | 10-K · 0001477932-21-001746 SEC |
| 2018-01-01 | 2018-12-31 | -968,826 | USD | 2020-04-14 | 10-K · 0001477932-20-001921 SEC |
| 2017-01-01 | 2017-12-31 | -902,748 | USD | 2019-04-01 | 10-K · 0001477932-19-001311 SEC |
| 2016-01-01 | 2016-12-31 | 798,650 | USD | 2018-03-30 | 10-K · 0001477932-18-001540 SEC |
| 2015-01-01 | 2015-12-31 | 770,752 | USD | 2017-03-21 | 10-K · 0001445866-17-000250 SEC |
| 2014-01-01 | 2014-12-31 | 600,083 | USD | 2016-03-24 | 10-K · 0001445866-16-001750 SEC |
| 2013-01-01 | 2013-12-31 | 765,708 | USD | 2015-03-30 | 10-K · 0001445866-15-000296 SEC |
| 2012-01-01 | 2012-12-31 | 66,083 | USD | 2014-03-31 | 10-K · 0001445866-14-000198 SEC |
| 2011-01-01 | 2011-12-31 | 803 | USD | 2013-04-02 | 10-K · 0001445866-13-000328 SEC |
| 2010-01-01 | 2010-12-31 | 1,089 | USD | 2012-03-30 | 10-K · 0001013762-12-000649 SEC |
Related DIGITAL LOCATIONS, INC. histories
Inspect the source
- Entity
- DIGITAL LOCATIONS, INC. / CIK 0001407878
- Captured
- SEC response SHA-256
57260d3ba2ce92652bbd10fc30813d682d7d5645d78581c86a36573188cbd7b0
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. Extended concepts require compatible unit shapes and at least three reporting ends with changing values within one unit. Constant or incompatible added histories are omitted.
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/0001407878.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"])))