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AMAZON COM INC: net income or loss

Net income or loss for AMAZON COM INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All AMAZON COM INC financial histories

What this measure means

Reported profit or loss for the period. Check the filing for attribution, exceptional items and discontinued operations before comparing companies.

Exact concept: us-gaap:NetIncomeLoss. 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

Net income or loss in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-3177,670,000,000USD2026-02-0610-K · 0001018724-26-000004
2024-01-012024-12-3159,248,000,000USD2026-02-0610-K · 0001018724-26-000004
2023-01-012023-12-3130,425,000,000USD2026-02-0610-K · 0001018724-26-000004
2022-01-012022-12-31-2,722,000,000USD2025-02-0710-K · 0001018724-25-000004
2021-01-012021-12-3133,364,000,000USD2024-02-0210-K · 0001018724-24-000008
2020-01-012020-12-3121,331,000,000USD2023-02-0310-K · 0001018724-23-000004
2019-01-012019-12-3111,588,000,000USD2022-02-0410-K · 0001018724-22-000005
2018-01-012018-12-3110,073,000,000USD2021-02-0310-K · 0001018724-21-000004
2017-01-012017-12-313,033,000,000USD2020-01-3110-K · 0001018724-20-000004
2016-01-012016-12-312,371,000,000USD2019-02-0110-K · 0001018724-19-000004
2015-01-012015-12-31596,000,000USD2018-02-0210-K · 0001018724-18-000005
2014-01-012014-12-31-241,000,000USD2017-02-1010-K · 0001018724-17-000011
2013-01-012013-12-31274,000,000USD2016-01-2910-K · 0001018724-16-000172
2012-01-012012-12-31-39,000,000USD2015-01-3010-K · 0001018724-15-000006
2011-01-012011-12-31631,000,000USD2014-01-3110-K · 0001018724-14-000006
2010-01-012010-12-311,152,000,000USD2013-01-3010-K · 0001193125-13-028520
2009-01-012009-12-31902,000,000USD2012-02-0110-K · 0001193125-12-032846
2008-01-012008-12-31645,000,000USD2011-01-2810-K · 0001193125-11-016253
2007-01-012007-12-31476,000,000USD2010-01-2910-K · 0001193125-10-016098

Related financial histories

Inspect the source

Entity
AMAZON COM INC / CIK 0001018724
Captured
2026-09-20T05:13:11.592Z
SEC response SHA-256
7549fb68446eee40e1f50a166fa06b2d2ee6349e07c8553a4828757e032d3cd4

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/0001018724.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"])))