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MARINE PRODUCTS CORPORATION: accumulated other comprehensive income or loss

Accumulated other comprehensive income or loss for MARINE PRODUCTS CORPORATION. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All MARINE PRODUCTS CORPORATION financial histories

What this measure means

Cumulative other comprehensive items after tax, such as translation and unrealized hedging or securities effects. These amounts have not passed through net income.

Exact concept: us-gaap:AccumulatedOtherComprehensiveIncomeLossNetOfTax. Each value is a balance at the reporting date, not a flow earned over a year. Different units remain separate; no currency conversion or interpolation is applied.

Coverage of this history

Selected reporting periods run from 2010-12-31 to 2023-12-31. The SEC response was captured on 2026-09-21.

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

Accumulated other comprehensive income or loss in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
At date2023-12-310USD2024-02-2810-K · 0001558370-24-001992
At date2022-12-31-1,995,000USD2024-02-2810-K · 0001558370-24-001992
At date2021-12-31-2,576,000USD2023-02-2710-K · 0001558370-23-002169
At date2020-12-31-1,947,000USD2022-02-2810-K · 0001558370-22-002350
At date2019-12-31-2,748,000USD2021-02-2610-K · 0001104659-21-029338
At date2018-12-31-2,175,000USD2021-02-2610-K · 0001104659-21-029338
At date2017-12-31-1,980,000USD2020-02-2810-K · 0001104659-20-027034
At date2016-12-31-2,182,000USD2019-02-2810-K · 0001144204-19-011172
At date2015-12-31-1,901,000USD2018-02-2810-K · 0001144204-18-011707
At date2014-12-31-1,969,000USD2017-02-2810-K · 0001571049-17-001712
At date2013-12-31-853,000USD2016-02-2910-K · 0001571049-16-012369
At date2012-12-31-1,572,000USD2015-02-2710-K · 0001571049-15-001481
At date2011-12-31-1,458,000USD2014-03-0610-K · 0001188112-14-000618
At date2010-12-31-996,000USD2013-03-0110-K · 0001188112-13-000534

Related financial histories

Inspect the source

Entity
MARINE PRODUCTS CORPORATION / CIK 0001129155
Captured
2026-09-21T17:18:01.935Z
SEC response SHA-256
381c37a5b9a25d0f964d189358e523a58f7bf6517d93c0c27d4202f69a5bb907

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/0001129155.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"])))