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Horizon Kinetics Holding Corporation: selling, general and administrative expense

Horizon Kinetics Holding selling, general and administrative expense: $2.74 million for the year ending 2025-12-31, up 18.2% on the year. 3 values since 2023.

All Horizon Kinetics Holding Corporation financial histories

At a glance

Horizon Kinetics Holding reported selling, general and administrative expense of $2.74 million for the year ending 2025-12-31, up 18.2% from $2.32 million a year earlier. Across the last three reported years it ranged from $1.66 million (2023-12-31) to $2.74 million (2025-12-31). That was 3.8% of revenue ($72.8 million) for the same year.

Computed from the values in the table below, in USD; each links to the filing it came from.

What this measure means

Selling and general administrative costs reported under this concept. It is an expense category, not a substitute for total operating expenses.

Exact concept: us-gaap:SellingGeneralAndAdministrativeExpense. 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 2023-01-01 to 2025-12-31. The SEC response was captured on 2026-09-19.

Selected filing history

Selling, general and administrative expense in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-312,742,000USD2026-03-1210-K · 0001193125-26-104113 SEC
2024-01-012024-12-312,319,000USD2026-03-1210-K · 0001193125-26-104113 SEC
2023-01-012023-12-311,664,000USD2025-03-3110-K · 0000950170-25-047560 SEC

Related HORIZON KINETICS HOLDING CORPORATION histories

All 55 Horizon Kinetics Holding histories

Inspect the source

Entity
HORIZON KINETICS HOLDING CORPORATION / CIK 0000088000
Captured
SEC response SHA-256
dacd72f126ca0eea55bc505a359fab8b09cb2640b3c74cfb605b83923e0c81f5

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.

The MCP server is free and MIT-licensed: npx -y canli-mcp. If these records help your research, a star on GitHub helps other researchers find them.

Read the published dataset with Python
import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0000088000.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"])))