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Futu Holdings Ltd: operating expenses

Operating expenses for Futu Holdings Ltd. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All Futu Holdings Ltd financial histories

What this measure means

Recurring operating costs under this accounting concept, generally excluding production costs included in cost of sales. Check filing presentation before combining expense subtotals.

Exact concept: us-gaap:OperatingExpenses. 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 expenses in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-315,823,936,000HKD2026-04-1520-F · 0001104659-26-043451
2024-01-012024-12-314,522,950,000HKD2026-04-1520-F · 0001104659-26-043451
2023-01-012023-12-313,464,705,000HKD2026-04-1520-F · 0001104659-26-043451
2022-01-012022-12-313,048,993,000HKD2025-04-1420-F · 0001410578-25-000706
2021-01-012021-12-312,726,443,000HKD2024-04-2420-F · 0001104659-24-051213
2020-01-012020-12-311,147,007,000HKD2023-04-2420-F · 0001104659-23-048600
2019-01-012019-12-31591,896,000HKD2022-03-1820-F · 0001104659-22-035332
2018-01-012018-12-31352,990,000HKD2021-03-2620-F · 0001104659-21-041771
2017-01-012017-12-31194,265,000HKD2020-04-2720-F · 0001104659-20-051297
2025-01-012025-12-31748,261,000USD2026-04-1520-F · 0001104659-26-043451
2024-01-012024-12-31582,276,000USD2025-04-1420-F · 0001410578-25-000706
2023-01-012023-12-31443,573,000USD2024-04-2420-F · 0001104659-24-051213
2022-01-012022-12-31390,820,000USD2023-04-2420-F · 0001104659-23-048600
2021-01-012021-12-31349,562,000USD2022-03-1820-F · 0001104659-22-035332
2020-01-012020-12-31147,936,000USD2021-03-2620-F · 0001104659-21-041771
2019-01-012019-12-3175,988,000USD2020-04-2720-F · 0001104659-20-051297

Related financial histories

Inspect the source

Entity
Futu Holdings Ltd / CIK 0001754581
Captured
2026-09-21T17:26:08.385Z
SEC response SHA-256
ba4ca731fde76735a3fbfb9b5cf92fc1f38273c54e414f55ae1ad4334c4ce108

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/0001754581.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"])))