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Eagle Financial Services, Inc.: contract revenue excluding tax

Eagle Financial Services contract revenue excluding tax: $0 for the year ending 2023-12-31, down 100.0% on the year. 3 values since 2021 from SEC filings.

All Eagle Financial Services, Inc. financial histories

At a glance

Eagle Financial Services reported contract revenue excluding tax of $0 for the year ending 2023-12-31, down 100.0% from $3000 a year earlier. Across the last three reported years it ranged from $0 (2023-12-31) to $236.0 thousand (2021-12-31).

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

What this measure means

Revenue from customer contracts excluding assessed taxes under this specific taxonomy concept. It is not automatically comparable to older revenue tags.

Exact concept: us-gaap:RevenueFromContractWithCustomerExcludingAssessedTax. 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 2021-01-01 to 2023-12-31. The SEC response was captured on 2026-09-20.

This selected history ends more than two years before capture. Do not treat its final value as a current balance or current annual result. More recent filings may use another accounting tag; inspect the filings before drawing conclusions about the company.

Selected filing history

Contract revenue excluding tax in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2023-01-012023-12-310USD2024-03-2910-K · 0000950170-24-038718 SEC
2022-01-012022-12-313,000USD2024-03-2910-K · 0000950170-24-038718 SEC
2021-01-012021-12-31236,000USD2023-03-2910-K · 0000950170-23-010622 SEC

Related EAGLE FINANCIAL SERVICES, INC. histories

All 35 Eagle Financial Services histories

Inspect the source

Entity
EAGLE FINANCIAL SERVICES, INC. / CIK 0000880641
Captured
SEC response SHA-256
bcb089b91984c196ee76414e025b0e7f05f92e54d6aded7fa8624048359b1c1c

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/0000880641.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"])))