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NEW JERSEY RESOURCES CORPORATION: investing cash flow

Investing cash flow for NEW JERSEY RESOURCES CORPORATION. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All NEW JERSEY RESOURCES CORPORATION financial histories

What this measure means

Net cash from investing activities, including asset purchases, disposals and investment transactions. This differs from capital expenditure payments alone.

Exact concept: us-gaap:NetCashProvidedByUsedInInvestingActivities. 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 2007-10-01 to 2025-09-30. The SEC response was captured on 2026-09-19.

Selected filing history

Investing cash flow in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2024-10-012025-09-30-568,271,000USD2025-11-2010-K · 0000356309-25-000093
2023-10-012024-09-30-569,073,000USD2025-11-2010-K · 0000356309-25-000093
2022-10-012023-09-30-538,625,000USD2025-11-2010-K · 0000356309-25-000093
2021-10-012022-09-30-590,613,000USD2024-11-2610-K · 0000356309-24-000083
2020-10-012021-09-30-622,117,000USD2023-11-2110-K · 0000356309-23-000083
2019-10-012020-09-30-994,025,000USD2022-11-1710-K · 0000356309-22-000098
2018-10-012019-09-30-287,377,000USD2021-11-1810-K · 0000356309-21-000095
2017-10-012018-09-30-373,090,000USD2020-11-3010-K · 0000356309-20-000098
2016-10-012017-09-30-391,983,000USD2019-11-2210-K · 0000356309-19-000133
2015-10-012016-09-30-363,190,000USD2018-11-2010-K · 0000356309-18-000139
2014-10-012015-09-30-321,729,000USD2017-11-2110-K · 0000356309-17-000185
2013-10-012014-09-30-282,595,000USD2016-11-2210-K · 0000356309-16-000283
2012-10-012013-09-30-193,633,000USD2015-11-2410-K · 0000356309-15-000097
2011-10-012012-09-30-217,117,000USD2014-11-2510-K · 0000356309-14-000113
2010-10-012011-09-30-175,077,000USD2013-11-2610-K · 0000356309-13-000103
2009-10-012010-09-30-101,403,000USD2012-11-2910-K · 0000356309-12-000060
2008-10-012009-09-30-121,277,000USD2011-11-2310-K · 0000356309-11-000033
2007-10-012008-09-30-103,941,000USD2010-11-2410-K · 0000356309-10-000025

Related financial histories

Inspect the source

Entity
NEW JERSEY RESOURCES CORPORATION / CIK 0000356309
Captured
2026-09-19T14:57:37.923Z
SEC response SHA-256
2d510c5c9123def0b987a7d84b3e93924bc9b721b59f0eedc79aebaed265d5fb

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/0000356309.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"])))