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Golden Minerals Company: financial reference

Explore Golden Minerals Company financial histories from SEC filings, with original units, reporting periods, filing dates and downloadable source data.

Reported financial histories

Choose a measure to inspect its definition, complete selected history and filing provenance. Each row shows the latest period available for that selected concept and original unit. Separate currencies and reporting intervals remain separate rows. Coverage dates can differ between concepts. A recent capture does not imply recent accounting coverage; these amounts are not prices.

Latest periods by selected concept and original unit
MeasurePeriod startPeriod endValueUnitFiled
Total assetsAt date2024-12-314,816,000USD2025-04-15
Total liabilitiesAt date2024-12-316,918,000USD2025-04-15
Stockholders equityAt date2024-12-31-2,102,000USD2025-04-15
Cash and cash equivalentsAt date2024-12-313,175,000USD2025-04-15
Net income or loss2024-01-012024-12-31-7,600,000USD2025-04-15
Operating cash flow2024-01-012024-12-31-7,737,000USD2025-04-15
Revenue2023-01-012023-12-3112,002,000USD2024-03-19
Contract revenue excluding tax2023-01-012023-12-3112,002,000USD2024-03-19
Financing cash flow2024-01-012024-12-31-19,000USD2025-04-15
Investing cash flow2024-01-012024-12-317,165,000USD2025-04-15
Retained earnings or deficitAt date2024-12-31-554,788,000USD2025-04-15
Basic weighted-average shares2024-01-012024-12-3114,721,036shares2025-04-15
Diluted weighted-average shares2021-01-012021-12-31161,942,970shares2022-03-23
Basic earnings per share2024-01-012024-12-31-0.52USD/shares2025-04-15
Diluted earnings per share2021-01-012021-12-31-0.01USD/shares2022-03-23
Income tax expense or benefit2023-01-012023-12-3111,000USD2024-03-19
Net property, plant and equipmentAt date2024-12-3122,000USD2025-04-15
Share-based compensation expense2024-01-012024-12-31404,000USD2025-04-15
Operating income or loss2024-01-012024-12-31-4,553,000USD2025-04-15
Current assetsAt date2024-12-313,853,000USD2025-04-15
Current liabilitiesAt date2024-12-313,637,000USD2025-04-15
Net current accounts receivableAt date2020-12-3172,000USD2022-03-23
Net inventoryAt date2023-12-31830,000USD2024-03-19
Cost of revenue2023-01-012023-12-3112,358,000USD2024-03-19

Inspect the source

Entity
Golden Minerals Company / CIK 0001011509
Captured
2026-09-20T05:12:23.237Z
SEC response SHA-256
68be643b3bced93dbb4f74460e56e9a417e2c5f0b134b74fdb507fa2e87b6d75

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/0001011509.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"])))