COLUMBIA BANKING SYSTEM, INC.: diluted earnings per share

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 2009-01-01 to 2025-12-31. The SEC response was captured on 2026-09-20.

Selected filing history

Related financial histories

• COLUMBIA BANKING SYSTEM, INC.: total assets
• COLUMBIA BANKING SYSTEM, INC.: total liabilities
• COLUMBIA BANKING SYSTEM, INC.: stockholders equity
• COLUMBIA BANKING SYSTEM, INC.: cash and cash equivalents
• COLUMBIA BANKING SYSTEM, INC.: net income or loss
• COLUMBIA BANKING SYSTEM, INC.: operating cash flow
• COLUMBIA BANKING SYSTEM, INC.: capital expenditure payments
• COLUMBIA BANKING SYSTEM, INC.: contract revenue excluding tax
• COLUMBIA BANKING SYSTEM, INC.: financing cash flow
• COLUMBIA BANKING SYSTEM, INC.: investing cash flow
• COLUMBIA BANKING SYSTEM, INC.: retained earnings or deficit
• COLUMBIA BANKING SYSTEM, INC.: basic weighted-average shares
• COLUMBIA BANKING SYSTEM, INC.: diluted weighted-average shares
• COLUMBIA BANKING SYSTEM, INC.: basic earnings per share
• COLUMBIA BANKING SYSTEM, INC.: income tax expense or benefit
• COLUMBIA BANKING SYSTEM, INC.: net property, plant and equipment
• COLUMBIA BANKING SYSTEM, INC.: share-based compensation expense
• COLUMBIA BANKING SYSTEM, INC.: interest expense
• COLUMBIA BANKING SYSTEM, INC.: goodwill carrying amount
• COLUMBIA BANKING SYSTEM, INC.: net finite-lived intangible assets
• COLUMBIA BANKING SYSTEM, INC.: common-stock repurchase payments

Inspect the source

Entity

COLUMBIA BANKING SYSTEM, INC. / CIK 0000887343

Captured

2026-09-20T05:03:10.774Z

SEC response SHA-256

a43d34b107e84b141677482596b089267bbc53027b8ee1e57408c82b94e1ee98

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.

• Get an API key and run your first validation
• Connect the MCP server to your coding assistant
• Inspect the ALPHAC engine on GitHub
• Read the MCP server source and integration examples

import json
from urllib.request import urlopen

with urlopen("https://canlicapital.com/company-data/0000887343.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"])))