Skip to content

EnerSys: interest expense

Interest expense for EnerSys. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All EnerSys financial histories

What this measure means

Borrowing costs recognized as interest expense. This is distinct from cash interest paid and may not include every capitalized borrowing cost.

Exact concept: us-gaap:InterestExpense. 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 2008-04-01 to 2024-03-31. 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

Interest expense in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2023-04-012024-03-3149,954,000USD2024-05-2210-K · 0001289308-24-000018
2022-04-012023-03-3159,529,000USD2024-05-2210-K · 0001289308-24-000018
2021-04-012022-03-3137,777,000USD2024-05-2210-K · 0001289308-24-000018
2020-04-012021-03-3138,436,000USD2023-05-2410-K · 0001289308-23-000023
2019-04-012020-03-3143,673,000USD2022-05-2510-K · 0001289308-22-000036
2018-04-012019-03-3130,868,000USD2021-05-2610-K · 0001289308-21-000027
2017-04-012018-03-3125,001,000USD2020-06-0110-K · 0001289308-20-000029
2016-04-012017-03-3122,197,000USD2019-05-2910-K · 0001289308-19-000028
2015-04-012016-03-3122,343,000USD2018-05-3010-K · 0001289308-18-000017
2014-04-012015-03-3119,644,000USD2017-05-3010-K · 0001289308-17-000019
2013-04-012014-03-3117,105,000USD2016-05-3110-K · 0001289308-16-000060
2012-04-012013-03-3118,719,000USD2015-05-2710-K · 0001289308-15-000029
2011-04-012012-03-3116,484,000USD2014-05-2810-K · 0001289308-14-000019
2010-04-012011-03-3122,038,000USD2013-05-2810-K · 0001193125-13-237411
2009-04-012010-03-3122,658,000USD2012-05-2510-K · 0001193125-12-249202
2008-04-012009-03-3126,733,000USD2011-05-3110-K · 0001193125-11-154707

Related financial histories

Inspect the source

Entity
EnerSys / CIK 0001289308
Captured
2026-09-20T07:49:49.967Z
SEC response SHA-256
3cb2af95344377d0dbf4379b817fa22403afe2707ed97d402ad3f32bcf38d3cf

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/0001289308.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"])))