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Four Seasons Education (Cayman) Inc.: current assets

Current assets for Four Seasons Education (Cayman) Inc. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All Four Seasons Education (Cayman) Inc. financial histories

What this measure means

Assets classified as current under the normal operating cycle or one-year boundary. Not all current assets can be converted immediately into cash.

Exact concept: us-gaap:AssetsCurrent. 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 2017-02-28 to 2026-02-28. 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

Current assets in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
At date2026-02-28252,342,000CNY2026-06-1720-F · 0001193125-26-273350
At date2025-02-28296,978,000CNY2026-06-1720-F · 0001193125-26-273350
At date2024-02-29322,579,000CNY2025-06-2620-F · 0000950170-25-090163
At date2023-02-28511,188,000CNY2024-06-2720-F · 0000950170-24-078480
At date2022-02-28525,982,000CNY2023-06-2820-F · 0000950170-23-030412
At date2021-02-28516,842,000CNY2023-03-1020-F/A · 0000950170-23-007130
At date2020-02-29616,218,000CNY2021-07-0220-F · 0001564590-21-035731
At date2019-02-28495,742,000CNY2020-06-2420-F · 0001564590-20-030428
At date2018-02-28595,025,000CNY2019-06-2520-F · 0001564590-19-023444
At date2017-02-28282,618,000CNY2018-06-2720-F · 0001564590-18-016280
At date2026-02-2836,796,000USD2026-06-1720-F · 0001193125-26-273350
At date2025-02-2840,777,000USD2025-06-2620-F · 0000950170-25-090163
At date2024-02-2944,816,000USD2024-06-2720-F · 0000950170-24-078480
At date2023-02-2873,739,000USD2023-06-2820-F · 0000950170-23-030412
At date2022-02-2883,378,000USD2023-03-1020-F/A · 0000950170-23-007130
At date2021-02-2879,846,000USD2021-07-0220-F · 0001564590-21-035731
At date2020-02-2988,148,000USD2020-06-2420-F · 0001564590-20-030428
At date2019-02-2874,088,000USD2019-06-2520-F · 0001564590-19-023444
At date2018-02-2894,031,000USD2018-06-2720-F · 0001564590-18-016280

Related financial histories

Inspect the source

Entity
Four Seasons Education (Cayman) Inc. / CIK 0001709819
Captured
2026-09-21T17:24:21.722Z
SEC response SHA-256
c3c771f97de3de73ea7691ba40bef5ba970a0a574226bb86215825130ec66ada

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/0001709819.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"])))