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20230930-DK-BUTTERFLY-1, INC.: capital expenditure payments

Capital expenditure payments for 20230930-DK-BUTTERFLY-1, INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All 20230930-DK-BUTTERFLY-1, INC. financial histories

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 2007-03-04 to 2023-02-25. 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

Capital expenditure payments in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2022-02-272023-02-25332,886,000USD2023-06-1410-K · 0000886158-23-000059
2021-02-282022-02-26354,185,000USD2023-06-1410-K · 0000886158-23-000059
2020-03-012021-02-27183,077,000USD2023-06-1410-K · 0000886158-23-000059
2019-03-032020-02-29277,401,000USD2022-04-2110-K · 0000886158-22-000047
2018-03-042019-03-02325,366,000USD2021-04-2210-K · 0000886158-21-000015
2017-02-262018-03-03375,793,000USD2020-04-2910-K · 0000886158-20-000008
2016-02-282017-02-25373,574,000USD2019-04-3010-K · 0000886158-19-000012
2015-03-012016-02-27328,395,000USD2018-05-0210-K · 0001171843-18-003340
2014-03-022015-02-28330,637,000USD2017-04-2510-K · 0001171843-17-002300
2013-03-032014-03-01320,812,000USD2016-04-2610-K · 0001171843-16-009400
2012-02-262013-03-02315,937,000USD2015-04-2810-K · 0001171843-15-002257
2011-02-272012-02-25243,374,000USD2014-04-2910-K · 0001171843-14-001962
2010-02-282011-02-26183,474,000USD2013-04-3010-K · 0001104659-13-035115
2009-03-012010-02-27153,680,000USD2012-04-2410-K · 0001104659-12-027814
2008-03-022009-02-28215,859,000USD2011-04-2610-K · 0001104659-11-022393
2007-03-042008-03-01358,210,000USD2010-04-2710-K · 0001104659-10-022152

Related 20230930-DK-BUTTERFLY-1, INC. histories

Inspect the source

Entity
20230930-DK-BUTTERFLY-1, INC. / CIK 0000886158
Captured
SEC response SHA-256
77bd7030131d1c121298dcee740194ef516c98f2415daca32b383513101da669

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.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0000886158.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"])))