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NBT BANCORP INC: diluted earnings per share

Diluted earnings per share for NBT BANCORP INC. Inspect selected reporting periods, original units and SEC filing links; download the financial history.

All NBT BANCORP INC financial histories

What this measure means

Reported earnings or loss per share under dilution rules. Antidilutive instruments may be excluded. A diluted value can equal the basic value without implying no potential dilution.

Exact concept: us-gaap:EarningsPerShareDiluted. 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 2008-01-01 to 2025-12-31. The SEC response was captured on 2026-09-19.

Selected filing history

Diluted earnings per share in original reported units, latest-filed observation per period
Period startPeriod endValueUnitFiledSource filing
2025-01-012025-12-313.33USD/shares2026-02-2710-K · 0001140361-26-007179
2024-01-012024-12-312.97USD/shares2026-02-2710-K · 0001140361-26-007179
2023-01-012023-12-312.65USD/shares2026-02-2710-K · 0001140361-26-007179
2022-01-012022-12-313.52USD/shares2025-02-2810-K · 0001140361-25-006528
2021-01-012021-12-313.54USD/shares2024-02-2910-K · 0001140361-24-010464
2020-01-012020-12-312.37USD/shares2023-03-0110-K · 0001140361-23-009417
2019-01-012019-12-312.74USD/shares2022-03-0110-K · 0001140361-22-007333
2018-01-012018-12-312.56USD/shares2021-03-0110-K · 0001140361-21-006657
2017-01-012017-12-311.87USD/shares2020-03-0210-K · 0001140361-20-004533
2016-01-012016-12-311.8USD/shares2019-03-0110-K · 0001140361-19-004221
2015-01-012015-12-311.72USD/shares2018-03-0110-K · 0001140361-18-011238
2014-01-012014-12-311.69USD/shares2017-03-0110-K · 0001140361-17-009954
2013-01-012013-12-311.46USD/shares2016-02-2910-K · 0001140361-16-055455
2012-01-012012-12-311.62USD/shares2015-03-0210-K · 0001140361-15-009684
2011-01-012011-12-311.71USD/shares2014-03-0310-K · 0001140361-14-010514
2010-01-012010-12-311.66USD/shares2013-03-0110-K · 0001140361-13-010069
2009-01-012009-12-311.53USD/shares2012-02-2910-K · 0001140361-12-011572
2008-01-012008-12-311.8USD/shares2011-03-0110-K · 0001140361-11-013082

Related financial histories

Inspect the source

Entity
NBT BANCORP INC / CIK 0000790359
Captured
2026-09-19T15:04:13.478Z
SEC response SHA-256
a3ca4cd88104e5391c71e3c365067d886a7b9ad4c319f0f8b81ee87fbb579d9d

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/0000790359.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"])))