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Sound Group Inc.: operating income or loss

Operating income or loss for Sound Group Inc. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All Sound Group Inc. financial histories

What this measure means

Operating revenue less operating expenses for the reporting period. It excludes items outside the reported operating result and is not free cash flow.

Exact concept: us-gaap:OperatingIncomeLoss. 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 2017-01-01 to 2025-12-31. The SEC response was captured on 2026-09-21.

Coverage by original unit

These are separate reported series. A newer period in one unit does not update another unit’s history or establish a currency conversion.

Selected filing history

Operating income or loss in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-31217,002,000CNY2026-04-3020-F · 0001493152-26-019716
2024-01-012024-12-31-89,703,000CNY2026-04-3020-F · 0001493152-26-019716
2023-01-012023-12-31-147,668,000CNY2026-04-3020-F · 0001493152-26-019716
2022-01-012022-12-3166,651,000CNY2025-04-2920-F · 0001410578-25-000976
2021-01-012021-12-31-138,518,000CNY2024-10-3120-F · 0001410578-24-001728
2020-01-012020-12-31-88,689,000CNY2023-04-2820-F · 0001104659-23-051892
2019-01-012019-12-31-141,837,000CNY2022-04-2720-F · 0001193125-22-123622
2018-01-012018-12-31-11,998,000CNY2021-03-2620-F · 0001193125-21-096539
2017-01-012017-12-31-149,922,000CNY2020-04-2020-F · 0001193125-20-112157
2025-01-012025-12-3131,031,000USD2026-04-3020-F · 0001493152-26-019716
2024-01-012024-12-31-12,289,000USD2025-04-2920-F · 0001410578-25-000976
2023-01-012023-12-31-20,799,000USD2024-10-3120-F · 0001410578-24-001728
2022-01-012022-12-319,663,000USD2023-04-2820-F · 0001104659-23-051892
2021-01-012021-12-31-21,737,000USD2022-04-2720-F · 0001193125-22-123622
2020-01-012020-12-31-13,592,000USD2021-03-2620-F · 0001193125-21-096539
2019-01-012019-12-31-20,373,000USD2020-04-2020-F · 0001193125-20-112157

Related financial histories

Inspect the source

Entity
Sound Group Inc. / CIK 0001783407
Captured
2026-09-21T17:31:17.645Z
SEC response SHA-256
94f4356682dcd1cc869a97245336122c8cc678c52f8c0f7d4b55cddc93394866

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/0001783407.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"])))