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American Railcar Industries, Inc.: filings

Every American Railcar Industries, Inc. annual and quarterly report in the SEC record with the published financial measures it tagged, 30 filings, each linked to its SEC index.

Filing record ends 2018-10-30

The latest filing in this captured record is a 10-Q filed 2018-10-30. No later filing is in the SEC companyfacts record captured on 2026-09-22. American Railcar Industries, Inc. may have stopped filing, merged, or changed its reporting entity; nothing on this page describes its current status. Values are as reported at the time.

Filings with published measures

Each page shows what one filing reported, as tagged in that filing, with the periods it covered. Later filings can restate a value; the company overview shows the latest-filed value per period.

FormFiledFiscal periodMeasuresFactsSEC accession
10-Q2018-10-30fiscal Q3 201836980001344596-18-000055
10-Q2018-08-01fiscal Q2 201836980001344596-18-000047
10-Q2018-05-01fiscal Q1 201835740001344596-18-000032
10-K2018-02-23fiscal FY 2017431340001344596-18-000016
10-Q2017-10-31fiscal Q3 201736930001344596-17-000056
10-Q2017-08-02fiscal Q2 201736930001344596-17-000046
10-Q2017-05-02fiscal Q1 201736730001344596-17-000029
10-K2017-02-24fiscal FY 2016421270001344596-17-000009
10-Q2016-10-28fiscal Q3 201636930001344596-16-000124
10-Q2016-07-29fiscal Q2 201636930001344596-16-000115
10-Q2016-04-29fiscal Q1 201636730001344596-16-000098
10-K2016-02-23fiscal FY 2015421270001344596-16-000077
10-Q2015-11-03fiscal Q3 201536930001344596-15-000058
10-Q2015-07-30fiscal Q2 201535930001344596-15-000050
10-Q2015-05-06fiscal Q1 201535730001344596-15-000032
10-K2015-02-20fiscal FY 2014401210001344596-15-000006
10-Q2014-10-31fiscal Q3 201435930001344596-14-000082
10-Q2014-07-31fiscal Q2 201435930001344596-14-000068
10-Q2014-05-05fiscal Q1 201435730001344596-14-000042
10-K2014-02-25fiscal FY 2013421260001344596-14-000021
10-Q2013-11-05fiscal Q3 2013391030001344596-13-000017
10-Q2013-08-05fiscal Q2 2013391030001344596-13-000008
10-Q2013-04-30fiscal Q1 201339770001193125-13-187449
10-K2013-03-12fiscal FY 2012421280001193125-13-103407
10-Q2012-11-02fiscal Q3 2012401080001193125-12-449201
10-Q2012-08-03fiscal Q2 2012401080001193125-12-332343
10-Q2012-05-01fiscal Q1 201236730001193125-12-196840
10-K2012-03-02fiscal FY 201136940001193125-12-094764
10-Q2011-11-02fiscal Q3 201134850000950123-11-094102
10-Q2011-08-02fiscal Q2 201134850000950123-11-071631

Inspect the source

Entity
American Railcar Industries, Inc. / CIK 0001344596
Captured
SEC response SHA-256
ac3d834d2f650358857407c7ad688c04a0287bb712e30d59cc8df88cfd8a27a7

Current SEC company facts · Download the original response snapshot (gzip) · Download the selected JSON

Every published concept a filing tagged, with the periods it covered, as reported in that filing at capture time. Forms 10-K, 10-K/A, 10-Q, 10-Q/A, 20-F, 20-F/A, 40-F, 40-F/A. A filing page needs at least 8 published concepts. Later filings can restate these values; the company history pages show the latest-filed value per period.

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/0001344596.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"])))