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LABCORP HOLDINGS INC.: financing cash flow

Financing cash flow for LABCORP HOLDINGS INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All LABCORP HOLDINGS INC. financial histories

What this measure means

Net cash from financing activities, including borrowing, repayments and transactions with owners. A positive amount does not establish operating profitability.

Exact concept: us-gaap:NetCashProvidedByUsedInFinancingActivities. 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 2007-01-01 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Financing cash flow in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-31-1,457,000,000USD2026-02-2410-K · 0000920148-26-000111
2024-01-012024-12-31779,900,000USD2026-02-2410-K · 0000920148-26-000111
2023-01-012023-12-31-59,300,000USD2026-02-2410-K · 0000920148-26-000111
2022-01-012022-12-31-1,322,200,000USD2025-02-2510-K · 0000920148-25-000032
2021-01-012021-12-31-2,065,800,000USD2024-02-2610-K · 0000920148-24-000014
2020-01-012020-12-31-517,400,000USD2023-02-2810-K · 0000920148-23-000017
2019-01-012019-12-31-252,700,000USD2022-02-2510-K · 0000920148-22-000015
2018-01-012018-12-31-1,389,900,000USD2021-02-2510-K · 0000920148-21-000018
2017-01-012017-12-31593,200,000USD2020-02-2810-K · 0000920148-20-000011
2016-01-012016-12-31-671,000,000USD2019-02-2810-K · 0000920148-19-000033
2015-01-012015-12-313,184,600,000USD2018-02-2710-K · 0000920148-18-000024
2014-01-012014-12-31-200,600,000USD2016-03-0110-K · 0000920148-16-000165
2013-01-012013-12-31-518,300,000USD2016-03-0110-K · 0000920148-16-000165
2012-01-012012-12-31-800,000USD2015-02-2610-K · 0000920148-15-000020
2011-01-012011-12-31-645,000,000USD2014-02-2510-K · 0000920148-14-000021
2010-01-012010-12-31515,300,000USD2013-02-2610-K · 0000920148-13-000022
2009-01-012009-12-31-600,900,000USD2012-02-2410-K · 0000920148-12-000039
2008-01-012008-12-31-218,500,000USD2011-03-0710-K/A · 0000920148-11-000024
2007-01-012007-12-31-363,700,000USD2010-02-2410-K · 0000920148-10-000021

Related financial histories

Inspect the source

Entity
LABCORP HOLDINGS INC. / CIK 0000920148
Captured
2026-09-20T05:07:51.083Z
SEC response SHA-256
870099f23ed7598e05f405c7b5db78de7f4e413de290bf898fe02180fd87bdd8

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/0000920148.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"])))