Big Sky Industrial Inc.: capital expenditure payments
Big Sky Industrial capital expenditure payments: $435.0 thousand for the year ending 2022-12-31, up 121.9% on the year. 8 values since 2013 from SEC filings.
All Big Sky Industrial Inc. financial histories
At a glance
Big Sky Industrial reported capital expenditure payments of $435.0 thousand for the year ending 2022-12-31, up 121.9% from $196.0 thousand a year earlier. From 2013 to 2022 it fell at a compound 34.9% a year, from $20.8 million to $435.0 thousand. Across the last five reported years it ranged from $11.0 thousand (2018-12-31) to $435.0 thousand (2022-12-31). That was 1.0% of revenue ($44.6 million) for the same year.
Computed from the values in the table below, in USD; each links to the filing it came from.
What this measure means
Cash payments to acquire property, plant and equipment. This taxonomy concept does not capture every form of investment or acquisition.
Exact concept: us-gaap:PaymentsToAcquirePropertyPlantAndEquipment. 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 2013-01-01 to 2022-12-31. The SEC response was captured on 2026-09-19.
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 |
|---|---|---|---|---|---|
| 2022-01-01 | 2022-12-31 | 435,000 | USD | 2023-04-13 | 10-K · 0001493152-23-012144 SEC |
| 2021-01-01 | 2021-12-31 | 196,000 | USD | 2023-04-13 | 10-K · 0001493152-23-012144 SEC |
| 2018-01-01 | 2018-12-31 | 11,000 | USD | 2020-03-30 | 10-K · 0001493152-20-005194 SEC |
| 2017-01-01 | 2017-12-31 | 299,000 | USD | 2018-03-28 | 10-K · 0001493152-18-004053 SEC |
| 2016-01-01 | 2016-12-31 | 194,000 | USD | 2018-03-28 | 10-K · 0001493152-18-004053 SEC |
| 2015-01-01 | 2015-12-31 | 3,620,000 | USD | 2018-03-28 | 10-K · 0001493152-18-004053 SEC |
| 2014-01-01 | 2014-12-31 | 31,044,000 | USD | 2017-04-17 | 10-K · 0001615774-17-001735 SEC |
| 2013-01-01 | 2013-12-31 | 20,799,000 | USD | 2016-04-14 | 10-K · 0001615774-16-004967 SEC |
Related BIG SKY INDUSTRIAL INC. histories
Inspect the source
- Entity
- BIG SKY INDUSTRIAL INC. / CIK 0000101594
- Captured
- SEC response SHA-256
c9351c839b50c94e16e84c8dd6f25ce736d0e444a33f174b719e0eb7dc0b0bf7
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.
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Read the published dataset with Python
import json
from urllib.request import urlopen
with urlopen("https://canlicapital.com/company-data/0000101594.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"])))